BACKGROUND: The purpose of this study was to identify morphomic factors on standard, pretransplantation computed tomography (CT) scans associated with outcomes after lung transplantation.

METHODS: A retrospective review of 200 patients undergoing lung transplantation at a single institution from 2003 to 2014 was performed. CT scans obtained within 1 year before transplantation underwent morphomic analysis. Morphomic characteristics included lung, dorsal muscle group, bone, and subcutaneous and visceral fat area and density. Patient data were gathered from institutional and United Network for Organ Sharing databases. Outcomes, including initial ventilator support greater than 48 hours, length of stay, and survival, were evaluated using univariate and multivariable analyses.

RESULTS: On multivariable Cox regression, subcutaneous fat/total body area (hazard ratio [HR] 0.60, p = 0.001), lung density 3 volume (HR 0.67, p = 0.013), and creatinine (HR 4.37, p = 0.010) were independent predictors of survival. Initial ventilator support more than 48 hours was associated with decreased vertebral body to linea alba distance (odds ratio [OR] 0.49, p = 0.002) and Zubrod score 4 (OR 14.0, p < 0.001). Increased bone mineral density (p < 0.001) and increased cross-sectional body area (p < 0.001) were associated with decreased length of stay, whereas supplemental oxygen (p < 0.001), bilateral transplantation (p = 0.002), cardiopulmonary bypass (p < 0.001), and Zubrod score 3 (p < 0.001) or 4 (p = 0.040) were associated with increased length of stay.

CONCLUSIONS: Morphomic factors associated with lower metabolic reserve and frailty, including decreased subcutaneous fat, bone density, and body dimensions were independent predictors of survival, prolonged ventilation, and increased length of stay. Analytic morphomics using pretransplantation CT scans may improve recipient selection and risk stratification.

BACKGROUND: The purpose of this study was to identify morphomic factors on standard, pretransplantation computed tomography (CT) scans associated with outcomes after lung transplantation.

METHODS: A retrospective review of 200 patients undergoing lung transplantation at a single institution from 2003 to 2014 was performed. CT scans obtained within 1 year before transplantation underwent morphomic analysis. Morphomic characteristics included lung, dorsal muscle group, bone, and subcutaneous and visceral fat area and density. Patient data were gathered from institutional and United Network for Organ Sharing databases. Outcomes, including initial ventilator support greater than 48 hours, length of stay, and survival, were evaluated using univariate and multivariable analyses.

RESULTS: On multivariable Cox regression, subcutaneous fat/total body area (hazard ratio [HR] 0.60, p = 0.001), lung density 3 volume (HR 0.67, p = 0.013), and creatinine (HR 4.37, p = 0.010) were independent predictors of survival. Initial ventilator support more than 48 hours was associated with decreased vertebral body to linea alba distance (odds ratio [OR] 0.49, p = 0.002) and Zubrod score 4 (OR 14.0, p < 0.001). Increased bone mineral density (p < 0.001) and increased cross-sectional body area (p < 0.001) were associated with decreased length of stay, whereas supplemental oxygen (p < 0.001), bilateral transplantation (p = 0.002), cardiopulmonary bypass (p < 0.001), and Zubrod score 3 (p < 0.001) or 4 (p = 0.040) were associated with increased length of stay.

CONCLUSIONS: Morphomic factors associated with lower metabolic reserve and frailty, including decreased subcutaneous fat, bone density, and body dimensions were independent predictors of survival, prolonged ventilation, and increased length of stay. Analytic morphomics using pretransplantation CT scans may improve recipient selection and risk stratification.

Abstract

Antibiotics such as vancomycin are empirically dosed on the basis of body weight, which may not be optimal across the expanding adult body size distribution. Our aim was to compare the relationships between morphomic parameters generated from computed tomography images to conventional body size metrics as predictors of vancomycin pharmacokinetics (PK). This single-center retrospective study included 300 patients with 1,622 vancomycin concentration (52% trough) measurements. Bayesian estimation was used to compute individual vancomycin volume of distribution of the central compartment (Vc) and clearance (CL). Approximately 45% of patients were obese with an overall median (5th, 95th percentile) weight and body mass index of 87.2 (54.7, 123) kg and 28.8 (18.9, 43.7) kg/m2, respectively. Morphomic parameters of body size such as body depth, total body area, and torso volume of the twelfth thoracic through fourth lumbar vertebrae (T12 to L4) correlated with Vc. The relationship of vancomycin Vc was poorly predicted by body size but was stronger with T12-to-L4 torso volume (coefficient of determination [R2] = 0.11) than weight (R2 = 0.04). No relationships between vancomycin CL and traditional body size metrics could be discerned; however, relationships with skeletal muscle volume and total psoas area were found. Vancomycin CL independently correlated with total psoas area and inversely correlated with age. Thus, vancomycin CL was significantly related to total psoas area over age (R2 = 0.23, P < 0.0001). This proof-of-concept study suggests a potential role for translation of radiographic information into parameters predictive of drug pharmacokinetics. Prediction of individual antimicrobial pharmacokinetic parameters using analytic morphomics has the potential to improve antimicrobial dose selection and outcomes of obese patients.

BACKGROUND: As patients with chronic kidney disease become older, there is greater need to identify who will most benefit from kidney transplantation. Analytic morphomics has emerged as an objective risk assessment tool distinct from chronologic age. We hypothesize that morphometric age is a significant predictor of survival following transplantation.

METHODS: A retrospective cohort of 158 kidney transplant patients from 2005 to 2014 with 1-year preoperative imaging was identified. Based on a control population comprising of trauma patients and kidney donors, morphometric age was calculated using the validated characteristics of psoas area, psoas density, and abdominal aortic calcification. The primary outcome was post-transplant survival.

RESULTS: Cox regression showed morphometric age was a significant predictor of survival (hazard ratio, 1.06 per morphometric year [95% confidence interval, 1.03-1.08]; P < .001). Chronological age was not significant (hazard ratio, 1.03 per year [0.98-1.07]; P = .22). Among the chronologically oldest patients, those with younger morphometric age had greater survival rates compared to those with older morphometric age.

CONCLUSIONS: Morphometric age predicts survival following kidney transplantation. Particularly for older patients, it offers improved risk stratification compared to chronologic age. Morphomics may improve the transplant selection process and provide a greater assessment of prospective survival benefits.

BACKGROUND: Better risk assessment tools are needed to predict post-transplantation diabetes mellitus (PTDM). Using analytic morphomic measurements from computed tomography (CT) scans, we aimed to identify specific measures of body composition associated with PTDM.

METHODS: We retrospectively reviewed 99 non-diabetic kidney transplant recipients who received pre-transplant CT scans at a single institution between 1/2005 and 5/2014. Analytic morphomic techniques were used to measure abdominal adiposity, abdominal size, and psoas muscle area and density, standardized by gender. We measured the associations of these morphomic factors with PTDM.

RESULTS: One-year incidence of PTDM was 18%. The morphomic factors significantly associated with PTDM included visceral fat area (OR=1.84 per standard deviation increase, P=.020), body depth (OR=1.79, P=.035), and total body area (OR=1.67, P=.049). Clinical factors significantly associated with PTDM included African American race (OR=3.01, P=.044), hypertension (OR=2.97, P=.041), and dialysis vintage (OR=1.24 per year on dialysis, P=.048). Body mass index was not associated with PTDM (OR=1.05, P=.188). On multivariate modeling, visceral fat area was an independent predictor of PTDM (OR=1.91, P=.035).

CONCLUSIONS: Analytic morphomics can identify pre-transplant measurements of body composition that are predictive of PTDM in kidney transplant recipients. Pre-transplant imaging contains a wealth of underutilized data that may inform PTDM prevention strategies.

RATIONALE AND OBJECTIVES: To explore whether the sarcopenia body type can help predict response to interleukin-2 (IL-2) therapy in metastatic renal cell carcinoma (RCC).

MATERIALS AND METHODS: Institutional review board approval was obtained for this Health Insurance Portability and Accountability Act-compliant retrospective cohort study of 75 subjects with metastatic RCC who underwent pretreatment contrast-enhanced computed tomography within 1 year of initiating IL-2 therapy. Cross-sectional area and attenuation of normal-density (31-100 Hounsfield units [HU]) and low-density (0-30 HU) dorsal muscles were obtained at the T11 vertebral level. The primary outcome was partial or complete response to IL-2 using RECIST 1.1 criteria at 6 weeks. A conditional inference tree was used to determine an optimal HU cutoff for predicting outcome. Bonferroni-adjusted multivariate logistic regression was conducted to investigate the independent associations between imaging features and response after controlling for demographics, doses of IL-2, and RCC prognostic scales (eg, Heng and the Memorial Sloan Kettering Cancer Center [MSKCC]).

RESULTS: Most subjects had intermediate prognosis by Heng (65% [49 of 75]) and the MSKCC (63% [47 of 75]) criteria; 7% had complete response and 12% had partial response. Mean attenuation of low-density dorsal muscles was a significant univariate predictor of IL-2 response after Bonferroni correction (P = 0.03). The odds of responding to treatment were 5.8 times higher for subjects with higher-attenuation low-density dorsal muscles (optimal cutoff: 18.1 HU). This persisted in multivariate analysis (P = 0.02). Body mass index (P = 0.67) and the Heng (P = 0.22) and MSKCC (P = 0.08) clinical prognostic scales were not significant predictors of response.

CONCLUSIONS: Lean cross-sectional attenuation of low-density dorsal muscles (ie, sarcopenia) may predict IL-2 response in metastatic RCC. Clinical variables are poor predictors of response.

Elderly populations have a higher risk of rib fractures and other associated thoracic injuries than younger adults, and the changes in body morphology that occur with age are a potential cause of this increased risk. Rib centroidal path geometry for 20,627 ribs was extracted from computed tomography (CT) scans of 1042 live adult subjects, then fitted to a six-parameter mathematical model that accurately characterizes rib size and shape, and a three-parameter model of rib orientation within the body. Multivariable regression characterized the independent effect of age, height, weight, and sex on the rib shape and orientation across the adult population, and statistically significant effects were seen from all demographic factors (P < 0.0001). This study reports a novel aging effect whereby both the rib end-to-end separation and rib aspect ratio are seen to increase with age, producing elongated and flatter overall rib shapes in elderly populations, with age alone explaining up to 20 percent of population variability in the aspect ratio of mid-level ribs. Age was not strongly associated with overall rib arc length, indicating that age effects were related to shape change rather than overall bone length. The rib shape effect was found to be more strongly and directly associated with age than previously documented age-related changes in rib angulation. Other demographic results showed height and sex being most strongly associated with rib size, and weight most strongly associated with rib pump-handle angle. Results from the study provide a statistical model for building rib shapes typical of any given demographic by age, height, weight, and sex, and can be used to help build population-specific computational models of the thoracic rib cage. Furthermore, results also quantify normal population ranges for rib shape parameters which can be used to improve the assessment and treatment of rib skeletal deformity and disease.

We aimed to determine whether comprehensive imaging analysis with analytic morphomics (AM) enhances or replaces geriatric assessment (GA) in risk-stratifying pancreatic surgery patients. One hundred thirty-four pancreatic surgery patients were identified from a prospective cohort. Sixty-three patients in the cohort had preoperative CT scans in addition to comprehensive geriatric assessments. CT scans were processed using AM. Associations with National Surgical Quality Improvement Program (NSQIP) serious complications were evaluated using univariate analysis and robust elastic net modeling to obtain AUROC curves by adding AM and GA measures to our previously defined clinical base risk model (age, body mass index, American Society of Anesthesiologists classification, and Charlson comorbidity index). NSQIP serious complications were associated with low psoas Hounsfield units (HUs) (p = 0.002), low-density (0 to 30 HU) psoas area (p = 0.01), visceral fat HU (p ≤ 0.001), visceral fat area (p = 0.009), subcutaneous fat HU (p = 0.023), and total body area (p = 0.012) on univariate analysis. Elastic net models incorporating the base model with geriatric assessment and psoas HU (AUC = 0.751), and AM alone (AUC = 0.739) have greater predictive value than the base model alone (AUC = 0.601). The model utilizing AM and GA in combination had the highest predictive value (AUC = 0.841). When combined, AM and GA improve prediction of NSQIP serious complications compared to either technique alone. The additive nature of these two modalities suggests they likely capture unique aspects of a patient's fitness for surgery.

Surgery causes physiologic stress similar to intense exercise. When the body's aerobic and metabolic demands are not met, organ dysfunction may occur and lead to unfavorable complications, or worse, potential deaths. The severity of this outcome is largely determined by a patient's cardiopulmonary reserve. Current preoperative workup focuses mainly on screening and identifying risk factors. Little attention has been devoted to improve cardiopulmonary reserve beyond counseling. We propose that patients could be optimized for a "surgical marathon" similar to preparing an athlete for a sports competition.

Retrospective demographic, (first hour) intra-operative and post-operative data were obtained from patients who underwent colectomy from 2014-2015 and divided into three observational groups: (1) Emergency; (2) Elective Non-Prehabilitation and (3) Elective with Prehabilitation. Enrollment into the prehabilitation program was completely voluntary for both physicians and patients, and referrals were made 4-6 weeks prior to scheduled operation. This program consisted in the following components: 1) MOVE, physical activity measured by a pedometer; 2) BREATHE, pulmonary rehabilitation using an incentive spirometer; 3) EAT, a dietary and 4) RELAX, a stress-reducing - coaching program. Progress was followed by nurse coordinators and compliance was measured by the frequency of engagement into the web portal.

Age, gender, ASA-grade, BMI, operative time, IV fluids and blood loss were similar in all three groups. At 1-hour post-anesthesia, positive physiologic responses characterized by higher systolic and diastolic blood pressure(s) and lower heart rate were observed in the prehabilitation cohort. Mortality was similar in all three groups (~3 %). However, the rate of complications was significantly reduced [14.2 vs. 45%; RR: 0.31 (95% CI: 0.13 - 0.71); p = 0.0082] in the prehabilitation group as compared to non-prehabilitation elective patients. This further allowed a significant reduction in the length of stay [5 days vs. emergency (p < 0.05) and 2 days vs. other elective surgery (p=0.11)]. Hospital savings averaged $6800, which amply offset any cost incurred with the program ($600/patient). In addition, the prehabilitation program was viewed favorably by patients, with a compliance rate of 70%.

Prehabilitation showed positive physiologic effects during first hour of surgery in colectomy patients. Patients engaged in a systematic optimization program experienced an improvement in their clinical outcomes with hospitals being benefited by a shorter length of stay and a reduction in costs.

Frostbite remains a challenging clinical scenario with multiple treatment algorithms and variable results. Currently, frostbite management often follows a conservative approach with rewarming followed by wound care and delayed amputation. We review seven patients where single-photon emission computed tomography (SPECT) fused with conventional computed tomography was used to evaluate tissue viability for earlier directed debridement and limb salvage. The goal of this report is to evaluate SPECT/CT as an appropriate modality for the screening of necrotic bone for earlier amputation in patients with frostbite. We retrospectively analyzed the records of seven patients (19 extremities) with frostbite who received SPECT/CT scans to evaluate deep tissue necrosis before digit amputation. All patients who presented within the first 24 hr following their injury without contraindications were initially treated with tissue plasminogen activator. Three patients met criteria and were treated with tissue plasminogen activator. Of the seven patients analyzed, none required revision amputation beyond the level predicted on SPECT/CT scan. No patients had viable tissue distal to the most distal extent of bone perfusion. In six of the patients, the SPECT/CT scan led to more distal amputation with proximal debridement of soft tissues thus maintaining extremity length. Frostbite remains a challenging clinical scenario for which there are a wide number of clinical algorithms. SPECT/CT appears to be valuable in the evaluation of frostbite to determine the need for amputation. Fusion of the nuclear images with the CT allows for more exact delineation of the level of amputation than a bone scan alone.

Abstract unavailible

Accurate sagittal alignment of the femoral component in total knee arthroplasty is crucial for prosthesis longevity, improved function, and patient satisfaction. However, there is variation in the techniques used to attain optimal sagittal femoral component placement in total knee arthroplasty. Femoral component flexion in imageless navigation is based on the mechanical axis rather than the distal femoral anatomy, and there is significant variability in the anatomy of the distal femur. The purpose of this study was to accurately determine the mean distal femoral flexion angle of a representative population and whether variability of the distal femoral flexion angle correlates with race, femur length, or radius of curvature. The mean degree of distal femoral flexion was determined by assessing distal femoral anatomy on computed tomography scans of paired femurs of 1235 patients without evidence of previous fracture, deformity, or surgical implants. The mean±SD distal femoral flexion angle was 2.90º±1.52º, with 80.2% of knees within 3º±2º. Therefore, placing the component in 3º of flexion from the mechanical axis would attain a satisfactory position in most cases. However, further analysis of the patient data revealed 11.4% of Asians, 7.3% of African Americans, and 8.3% of whites had a distal femoral flexion angle greater than 5º. Additionally, the data revealed a moderately strong negative correlation between the distal femoral flexion and the overall radius of curvature of the femur. This preliminary study highlights the need for improved methods for selecting femoral component position in the sagittal plane when using navigation for total knee arthroplasty. [Orthopedics. 201x; xx(x):xxx-xxx.].

This study investigates the isolated effect of rib shape on the mechanical characteristics of ribs subjected to multiple forms of loading. It aims to measure the variation in stiffness due to shape that is seen throughout the population and, in particular, provide a tool for researchers to better understand the influence of shape on resulting stiffness. A previously published six-parameter shape model of the central axis of human ribs was used. It has been shown to accurately model the overall rib path using intrinsic geometric properties such as size, aspect ratio, and skewness, through shapes based on logarithmic spirals with high curvature continuity. In this study the model was fitted to 19,500 ribs from 989 adult female and male CT scans having demographic distributions matching the US adult population. Mechanical loading was simulated through a simplified finite element model aimed at isolating rib shape from other factors influencing mechanical response. Four loading scenarios were used representing idealized free and constrained loading conditions in axial (body-anterior) and lateral directions. Characteristic rib stiffness and maximum stress location were tracked as simulation output measures. Regression models of rib stiffness found that all shape model parameters added information when predicting stiffness under each loading condition, with their linear combination able to account for 95% of the population stiffness variation due to shape in midlevel ribs for free axial loading, and 92%-98% in other conditions. Full regression models including interactive terms explained up to 99% of population variability. Results allow researchers to better evaluate the differences in stiffness results that are obtained from physical testing by providing a framework with which to explain variation due to rib shape.

In this study, we used analytic morphomics to understand the mechanisms of rib fracture for older occupants in frontal crashes. Analytic morphomics extracts body features from computered tomography scans of people involved in vehicle crashes who have been treated at the University of Michigan, a Level-1 trauma center. Chest injury and rib fracture patterns were examined in belted, front row occupants involved in frontal crashes from the International Center for Automotive Medicine database. Among these occupants, two age groups (younger and older) with the maximum abbreviated injury scale of chest region ≥ 3(MAIS_thx3+) were categorized. The location of each rib fracture was compared between the groups. Regression analyses were conducted to investigate fracture outcomes considering risk factors including vehicle, demographics, and morphomics. The rib fractures of belted occupants were mainly located under the path of the shoulder belt. For the older group, fracture patterns tended to be located in the anterior region but also bilaterally. Moreover, morphomic factors related to rib shape are the major driver of rib fracture for the older group. The current results for rib shape can highlight the importance of considering these morphomics characteristics when assessing chest injury and creating elderly computer models.

Body mass index does not account for body mass distribution. This study tested the hypothesis that subcutaneous fat thickness is a better indicator than body mass index of the risk of surgical site infection in lumbar spine procedures performed through a midline posterior approach. Charts were reviewed for previously identified risk factors for surgical site infection (age, diabetes, smoking, obesity, albumin level, multilevel procedures, previous surgery, and operative time) in 149 adult patients who underwent lumbar spine procedures through a midline posterior approach. Subcutaneous fat thickness was measured with a novel automated technique. Regression analysis was used to determine associations between risk factors and fat thickness with surgical site infection. In the study group, 15 surgical site infections occurred (10.1%). Bivariate analysis showed a significant association between surgical site infection and body mass index (P=.01), obesity (P=.02), and fat thickness (P=.002). With multivariate analysis, body mass index and obesity did not show significance, but fat thickness remained significant (P=.026). For every 1-mm thickness of subcutaneous fat there was a 6% (odds ratio, 1.06; 95% confidence interval, 1.02-1.10) increase in the odds of surgical site infection, and patients with fat thickness of greater than 50 mm had a 4-fold increase in the odds of surgical site infection compared with those with fat thickness of less than 50 mm. Body mass index and fat thickness were moderately correlated (r2=0.44). These results confirm the hypothesis that local subcutaneous fat thickness is a better indicator than body mass index of the risk of surgical site infection in lumbar spine procedures. [Orthopedics. 201x; xx(x):exxx-exxx.].

In this study we present a novel six-parameter shape model of the human rib centroidal path using logarithmic spirals. It provides a reduction in parameter space from previous models of overall rib shape, while simultaneously reducing fitting error by 34% and increasing curvature continuity. Furthermore, the model directly utilizes geometric properties such as rib end-to-end span, aspect ratio, rib "skewness", and inner angle with the spine in its parameterization, making the effects of each parameter on overall shape intuitive and easy to visualize. The model was tested against 2197 rib geometries extracted from CT scans from a population of 100 adult females and males of uniformly distributed ages between 20 and 70. Significant size and shape differences between genders were identified, and shape model utility is demonstrated by the production of statistically average male and female rib shapes for all rib levels. Simulated mechanical loading of the resulting model rib shapes showed that the stiffness of statistically average male and female ribs matched well with the average rib stiffness from each separate population. This in-plane rib shape model can be used to characterize variation in human rib geometry seen throughout the population, including investigation of the overall changes in shape and resultant mechanical properties that ribs undergo during aging or disease progression.

Existing prognostic models for patients with hepatocellular carcinoma (HCC) have limitations. Analytic morphomics, a novel process to measure body composition using computational image-processing algorithms, may offer further prognostic information. The aim of this study was to develop and validate a prognostic model for HCC patients using body composition features and objective clinical information.

Using computed tomography scans from a cohort of HCC patients at the VA Ann Arbor Healthcare System between January 2006 and December 2013, we developed a prognostic model using analytic morphomics and routine clinical data based on multivariate Cox regression and regularization methods. We assessed model performance using C-statistics and validated predicted survival probabilities. We validated model performance in an external cohort of HCC patients from Parkland Hospital, a safety-net health system in Dallas County.

The derivation cohort consisted of 204 HCC patients (20.1% Barcelona Clinic Liver Cancer classification (BCLC) 0/A), and the validation cohort had 225 patients (22.2% BCLC 0/A). The analytic morphomics model had good prognostic accuracy in the derivation cohort (C-statistic 0.80, 95% confidence interval (CI) 0.71-0.89) and external validation cohort (C-statistic 0.75, 95% CI 0.68-0.82). The accuracy of the analytic morphomics model was significantly higher than that of TNM and BCLC staging systems in derivation (P=0.001 for both) and validation (P=0.001 for both) cohorts. For calibration, mean absolute errors in predicted 1-year survival probabilities were 5.3% (90% quantile of 7.5%) and 7.6% (90% quantile of 12.5%) in the derivation and validation cohorts, respectively.

Body composition features, combined with readily available clinical data, can provide valuable prognostic information for patients with newly diagnosed HCC.

Analytical morphomics focuses on extracting objective and quantifiable data from clinical computered tomography (CT) scans to measure patients' frailty. Studies are currently retrospective in nature; therefore, it would be beneficial to develop animal models for well-controlled, prospective studies. The aim of this study is to develop an in vivo microCT protocaol for the longitudinal acquisition of whole-body images suitable for morphomic analyses of bone.

The authors performed phantom studies on 2 microCT systems (Inveon and CT120) to study tissue radiodensity and further characterize system performance for collecting animal data. The authors also describe their design of a phantom-immobilization device using phantoms and an ovariectomized (OVX) mouse.

The authors discovered increased consistency along the z-axis for scans acquired on the Inveon compared with CT120, and calibration by individual slice reduces variability. Objects in the field of view had more impact on measurement acquired using the CT120 compared with the Inveon. The authors also found that using the middle 80% of slices for data analysis further decreased variability, on both systems. Moreover, bone-mineral-density calibration using the QCT Pro Mini phantom improved bone-mineral-density estimates across energy spectra, which helped confirm our technique. Comparison of weekly body weights and terminal uterine mass between sham and OVX groups validated our model.

The authors present a refined microCT protocol to collect reliable and objective data. This data will be used to establish a platform for research animal morphomics that can be used to test hypotheses developed from clinical human morphomics.

To improve the accuracy of Injury Severity Prediction in the event of vehicle crash, a new methodology is proposed using the US vehicle accident database (NASS-CDS). This proposed method is an extension of the base algorithm introduced by Kononen et al. in which, some of the additional variables were introduced and branched logistic regression methodology was used. Results suggest that the proposed branching method has some advantage over the base algorithm due to better linearization of the complex multidimensional non-linear relationship of the input and output variables.

Hepatocellular carcinoma (HCC) is the most common primary liver malignancy and is one of the leading causes of cancer-related death in the United States. Prognosis of HCC remains poor, driven by advanced tumor burden at diagnosis in two-thirds of cases.

Cancer staging systems are important for prognostication and determination of therapy. HCC has unique characteristics for which it is more difficult to use standard cancer staging strategies. First, there is enormous heterogeneity with regard to patient characteristics and HCC biology. Second, in the Western world, the majority of HCC occurs in patients with significant underlying liver disease, making liver function and functional status important in determining outcome. Lastly, tissue diagnosis is not often required, and radiological diagnosis is often the standard. Various staging systems (Table 1) have been proposed to incorporate these variables, but there is no universal worldwide consensus. Two of these staging systems [Barcelona Clinic Liver Cancer (BCLC) and Groupe d'ETUDE et de Traitement du Carcinome Hepatocellulaire (GRETCH)] include performance status, with the BCLC being validated in various geographical settings and with very large data sets. As a result, the BCLC staging system is the most accepted system in the United States, having received the endorsement of both the American Association for the Study of Liver Diseases and the European Association for the Study of Liver Diseases and the European Association for the Study of Liver diseases (Figure 1). Its main advantage is the unique way in which it provides therapy guidelines based on staging, making it a very useful clinical tool.

This publication does not have an abstract.

Factors predictive of response to immunotherapy are needed to select appropriate patients. As morphometric analysis can be an objective surrogate for underlying physiology, we explored the possibility that morphomics may predict response among stage IV melanoma patients treated with ipilimumab.

We identified stage IV melanoma patients treated with ipilimumab who had an appropriate CT scan within a 6 month window. Using semi-automated algorithms, we acquired several morphomic measurements. Toxicity and response rate compared by quartile using Fisher's exact test or chi-square, while survival after initiation of ipilimumab was compared by quartile using the log-rank test.

While there was a significant correlation between toxicity and response (P < .003), morphomics failed to predict either severity of toxicity or specific side effects. Psoas density was significantly associated with response rate, both excluding stable disease (36.4% vs 9.1%, P = .054), and including stable disease (54.5% versus 18.2%, P = 0.045). Survival after initiation of ipilimumab was significantly associated with psoas density (P = 0.04) and visceral fat distance (P = 0.022).

In an exploratory study of patients with metastatic melanoma being treated with ipilimumab, psoas density and spine-fascia distance correlated with response and survival. Pre-treatment morphomic analysis, as a correlate of underlying physiology, may help predict response to immunotherapy.

Sarcopenia is associated with treatment-related complications and shorter overall survival in patients with cancer. Psoas area indices were calculated for 121 patients with lymphoma who underwent autologous transplant. Controlling for age, body mass index, comorbidities and performance status for the 73 men included, the hazard ratio (95% confidence interval, CI) for non-relapse mortality was 2.37 (1.01, 5.58), p = 0.048 for every 100 unit decrease in total psoas index and 2.67 (1.04, 6.86), p = 0.041 for every 100 unit decrease in lean psoas index. Men with a lower total psoas index experienced more complications (p = 0.001) and spent more days in hospital (p = 0.03) during the transplant admission. A strong association existed between sarcopenia and number of hospital days in the 100 days following transplant among both men (p < 0.0001) and women (p < 0.0001). Sarcopenia may impact negative outcomes after autologous transplant thereby serving as a potentially modifiable predictor of outcomes and aiding in treatment selection.

Motor vehicle crashes are the leading cause of injury-related mortality in children, with a higher rate of multiorgan injuries than in adults. This may be related to increased solid organ volume relative to abdominal cavity and decreased protection of an underdeveloped cartilaginous rib cage in young children. To date, these anatomic relationships have not been fully described. Our study used analytic morphomics to obtain precise measures of the pediatric liver, spleen, kidneys, and ribs.

This pilot study included 215 trauma patients (aged 0-18 years) with anonymized computed tomography (CT) scans. Liver, spleen, and kidney volumes were modeled using semiautomatic algorithms (MATLAB 2013a, MathWorks Inc., Natick, MA). Thirty-one scans were adequate to model the rib cage. Pearson's r was used to correlate absolute organ volume, fractional organ volume, and organ exposure with age and weight.

Spleen, right and left kidney, and liver volumes increased with age and weight (p < 0.01). Right/left kidney and liver fractional volumes decreased with age (p < 0.01), whereas spleen fractional volume remained relatively constant. Exposed surface area of the liver only significantly decreased with age in the anterior (p < 0.01), right (p < 0.01), and posterior views (p = 0.02).

With this study, we have demonstrated the ability to model solid organ and rib cage anatomy of children using cross-sectional imaging. In younger children, there may be a decrease in fractional organ volume and increase in liver surface exposure, although analysis of a larger sample size is warranted. In the future, this information may be used to improve the design of safety restraints in motor vehicles.

Wound complications – such as incisional hernia, ventral hernia, and wound dehiscence– are common following major abdominal surgery. Despite advances in surgical care, these complications remain prevalent. We hypothesized that analytic morphomics, a novel objective risk assessment tool, would explain the relationship between preoperative tissue composition and postoperative wound complications.

This is an observational study of 1,409 patients undergoing major abdominal surgery and who had a preoperative CT scan, all selected from the Michigan Surgical Quality Collaborative Database. The primary outcome is a composite of local wound complications, including incisional hernia, ventral hernia, wound dehiscence and major wound complications. Analytic morphomic measures of a single slice at the L4 vertebral level were investigated, along with variables related to patient demographics, medical history, admissions status, and comorbid disease. A p < 0.05 threshold in univariate analysis was employed for considering variables to be included in multivariable analysis.

Wound complications occurred in 11.9% of patients. Analytic morphomic variables associated with wound complications are detailed in the figure. The final, single-slice model was assembled via backwards stepwise selection, and included 4 preoperative variables: subcutaneous fat area @ L4 (odds ratio [OR] = 1.67, 95% confidence interval [Cl] 1.03-2.78, P = 0.040), pack-years (OR = 1.18, 95% CI 0.99-1.38, P = 0.046), albumin (OR = 0.84, 95% CI 0.72-1.00, P = 0.044), and immunosuppressive therapy (OR = 1.97, 95% CI 1.15-3.26, P = 0.010).

Patients with a large subcutaneous fat area have a higher risk of wound complication. This may inform surgeon decision-making in the operating room.

Patients undergoing major head and neck cancer surgery (MHNCS) may develop significant postoperative complications. To minimize the risk of complications, clinicians often assess multiple measures of preoperative health in terms of medical comorbidities. One emerging method to decrease surgical complications is preoperative assessment of patient frailty measured by specific tissue characteristics. We hypothesize that morphomic characteristics of the temporalis region serve as predictive markers for the development of complications after MHNCS.

We performed a retrospective review of 69 patients with available computed tomography (CT) imaging who underwent MHNCS from 2006-2012. To measure temporalis region characteristics, we used morphomic analysis of available preoperative CT scans to map out the region. All available CT scans had been performed as part of the patient's routine work-up and were not ordered for morphomic analysis. We describe the correlation among temporalis fat pad volume (TFPV), mean zygomatic arch thickness, and incidence of postoperative complications.

We noted significant difference in the zygomatic bone thickness and TFPV between patients who had medical complications, surgical complications, or total major complications and those who did not. Furthermore, by use of binary logistic regression, our data suggest decreased TFPV and zygomatic arch thickness are stronger predictors of developing postoperative complications than previously studies preoperative characteristics.

We describe morphomic analysis of the temporalis region in patients undergoing MHNCS to identify patients at risk for complications. Regional anatomic morphology may serve as a marker to objectively determine a patient's overall health. Use of the temporalis region is appropriate in patients undergoing MHNCS because of the availability of preoperative scans as part of routine work up for head and/or neck cancer.

A diagnosis of cirrhosis can be made on the basis of findings from imaging studies, but these are subjective. Analytic morphomics uses computational image processing algorithms to provide precise and detailed measurements of organs and body tissues. We investigated whether morphomic parameters can be used to identify patients with cirrhosis.

In a retrospective study, we performed analytic morphomics on data collected from 357 patients evaluated at the University of Michigan from 2004 to 2012 who had a liver biopsy within 6 months of a computed tomography scan for any reason. We used logistic regression with elastic net regularization and cross-validation to develop predictive models for cirrhosis, within 80% randomly selected internal training set. The other 20% data were used as internal test set to ensure that model overfitting did not occur. In validation studies, we tested the performance of our models on an external cohort of patients from a different health system.

Our predictive models, which were based on analytic morphomics and demographics (morphomics model) or analytic morphomics, demographics, and laboratory studies (full model), identified patients with cirrhosis with area under the receiver operating characteristic curve (AUROC) values of 0.91 and 0.90, respectively, compared with 0.69, 0.77, and 0.76 for aspartate aminotransferase-to-platelet ratio, Lok Score, and FIB-4, respectively, by using the same data set. In the validation set, our morphomics model identified patients who developed cirrhosis with AUROC value of 0.97, and the full model identified them with AUROC value of 0.90.

We used analytic morphomics to demonstrate that cirrhosis can be objectively quantified by using medical imaging. In a retrospective analysis of multi-protocol scans, we found that it is possible to identify patients who have cirrhosis on the basis of analyses of preexisting scans, without significant additional risk or cost.

Motor vehicle crashes (MVCs) are a major cause of traumatic injury in the US, and in- hospital cardiac complications are associated with increased morbidity and mortality in this population. Risk of cardiovascular complications is often difficult to predict using only injury severity and vital signs upon presentation to the trauma center. The utility of analytic morphomics have previously been established in perioperative risk assessment and may provide improved clinical insight in the trauma setting. We hypothesized that morphomic factors may serve as significant predictors of in-hospital cardiac complications for patients involved in MVCs.

Our study included 3,187 MVC adult patients admitted to the University of Michigan Health System who underwent an abdominal CT scan near the time of injury. Exclusion criteria include ISS less than 5 or head-and-neck AIS of 5 or greater. Morphomic factors were measured at the L4 vertebral level using established algorithms. We utilized univariate analysis to determine the relationship of patient demographics, comorbidities, morphomics, and vital signs upon hospital admission with the development of cardiac complications, defined as myocardial infarction (MI), cerebrovascular accident (CVA), and other cardiac events. Injury severity was stratified by mild (5<ISS<16), moderate (16<ISS<25), and severe (ISS>25) trauma.

Of the 3,187 eligible patients in our study, 121 (3.8%) developed cardiovascular complications. CVA and MI history, bone mineral density, and BMI were significant predictors of cardiovascular events (p<0.05) in mild trauma. Decreased average psoas radiodensity and increased age were found to be significant predictors for cardiovascular events (p<0.01) in moderate trauma. Glasgow Coma Scale and increased anterior body depth were the two most significant predictors of cardiovascular events in severe trauma (p<0.05). Table 1 shows the results of the univariate analysis between the complications and non- complications group for all three levels of trauma. Non-significant predictors of cardiovascular complications across all trauma levels include gender (p=0.17, 1.0, 0.11) and history of diabetes (p=0.37, 0.65, 0.19) or hypertension (p=0.50, 0.07, 0.35).

Following a MVC, in-hospital cardiovascular events are serious, life-threatening complications. Psoas radiodensity, bone mineral density, and anterior body depth are significant factors associated with cardiovascular complications. Thus, morphomic factors obtained from cross-sectional imaging are significant predictors of cardiovascular events and may aid clinical decision making for higher risk patients.

Acute kidney injury (AKI) occurs in approximately 20% of hospitalized adults and costs the US $10 billion annually. Prolonged hospital stay, cost, and mortality have been shown to be increased in these patients and those requiring renal replacement therapy have an even higher mortality rate. In the setting of colon surgery, a recent large scale study found several associated factors with postoperative AKI including advanced age, chronic renal failure, and total colectomy. However, a surgical decision informed by standard clinical data alone may not be sufficient. We set out to study the relationship between AKI and quantitative kidney morphomic factors from cross-sectional preoperative imaging for patients undergoing colectomies and comparing the results with demographic and intra-operative data. We hypothesized that individualized kidney characteristics would correlate with the risk of postoperative AKI development.

A retrospective review of prospectively gathered data from adult patients undergoing colectomies from 2006-2012 at the University of Michigan was conducted. 390 initial subjects without elevated baseline creatinine values, ESRD, a prior nephrectomy, or renal injury were included. Polycystic kidneys or other kidney abnormalities identified on imaging were excluded resulting in 326 subjects. AKI was defined by the KDIGO criteria within 30 days of injury. Demographic and intraoperative factors were evaluated along with measurements of pertinent kidney morphomic data including volume, surface area, and average Hounsfield Units (HU) which were subjected to univariate analyses.

Of the 326 patients, 60 developed AKI (18.4%). Of demographic factors, advanced age (p=0.0002) and a higher BMI (p=0.02) were associated with AKI. Comorbidities associated with AKI included hypertension (p=0.008) and diabetes (p=0.013). Interestingly, intraoperative factors including surgical time (p=0.13), blood transfusions (p=0.14), blood loss (p=0.42), and hypotensive episodes (p=0.17) were not significantly associated with AKI. Table 1 shows the results of the univariate analysis of the morphomic factors.

AKI is a serious complication and the prevalence after colorectal surgery at our institution was 18.4%. Our analysis shows that a lower average parenchymal HU was the most significant morphomic factor associated with postoperative AKI. This study is the first to provide information that morphomic analysis can be useful in clinical practice to determine which patients are at risk for developing AKI after a colectomy.

The objective of this study was to create a computer-aided design (CAD) geometric dataset of a 10-year-old (10 YO) child. The study includes two phases of efforts. At Phase One, the 10 YO whole body CAD was developed from component computed tomography and magnetic resonance imaging scans of 12 pediatric subjects. Geometrical scaling methods were used to convert all component parts to the average size for a 10 YO child, based on available anthropometric data. Then the component surfaces were compiled and integrated into a complete body. The bony structures and flesh were adjusted as symmetrical to minimize the bias from a single subject while maintaining anthropometrical measurements. Internal organs including the liver, spleen, and kidney were further verified by literature data. At Phase Two, internal characteristics for the cervical spine disc, wrist, hand, pelvis, femur, and tibia were verified with data measured from additional 94 10 YO children. The CAD dataset developed through these processes was mostly within the corridor of one standard deviation (SD) of the mean. In conclusion, a geometric dataset for an average size 10 YO child was created. The dataset serves as a foundation to develop computational 10 YO whole body models for enhanced pediatric injury prevention.

The cervical anatomy has been shown to affect injury patterns in vehicle crashes. Characterizing the spine anatomy and changes associated with growth and gender is important when assessing occupant protection. In this study, selected cervical characteristics were quantified.

Computed tomography (CT) scans of 750 patients were selected from the University of Michigan trauma database&59; 314 were children and 436 were adults. Four variables were obtained: the maximum spinal canal radius, vertebral body depth, facet angles, and retroversion angles.

The cervical spine measurements varied with age and gender. The body depth increased nonlinearly with age. The average vertebral body depth at C4 was 9.2 ± 0.38 mm in the 0-3 age group, 15.7 ± 0.29 mm in the 18-29 age group, and 17.2 ± 0.46 mm in the 60+ age group. Pediatric and adult males had larger vertebral body depth than females overall, irrespective of vertebral level (P <.001). Compared to females, the vertebral body depth was 8-9 percent greater in male children and 13-16 percent greater in adult males. The average radius varied with gender, with male children generally having a larger radius than females irrespective of vertebral level (P <.001). Overall, spinal canal radius was smallest in the 0-3 and 60+ age groups and largest in the 18-29 age group. The C4 radius was 5.91 ± 0.17, 6.28 ± 0.14, and 6.73 ± 0.17 mm respectively. The radius was larger in the 4-7 age group than in the 0-3 age group, irrespective of vertebral level (P <.0001). There were nonsignificant radius changes between the 4-7 and 8-11 age groups and the 8-11 and age 12-17 groups, suggesting that the size of the spinal cord reaches near maturation by the age of 7. Facet angles decreased with age in children and increased with age in adults. The average facet angles were largest in the 0-3 age group (P <.1, C2-C6). Adult facet angles were greater in the 60+ age group than in the 18-29 age group (P <.0001, C2-C6). Males had larger facet angles than females overall (P <.01 at C2, C5-C7). The retroversion angles were largest at C6 and C7. They increased with age in children and decreased in the adult population; they were larger (5-22%) in the 18-29 age group than in the 60+ age group (P <.0001, C2-C6).

The results obtained in this study help explain variations in cervical anatomical changes associated with age and gender. The information is useful when assessing differences in injury patterns between different segments of the population. Anatomical measurements of the cervical spine should be considered for the development of models used to assess injury mechanisms for various occupant age groups.

Estimates of blood loss during craniosynostosis surgeries have ranged from 42 to 126 percent of infant's total blood volume. Currently, no risk model has been developed to determine the likelihood of needing a blood transfusion. The authors propose an objective model, based on patients' three-dimensional anatomical characteristics, to stratify the likelihood of needing perioperative packed red blood cells.

High-throughput image analysis from already ordered preoperative computed tomographic scans was used to reconstruct the three-dimensional anatomy of the temporalis muscle and overlying temporal fat pad. Using these morphomic measurements, the authors created a risk assessment model of the amount of packed red blood cells infused based on morphomic variations in temporal soft tissue.

The authors evaluated 139 infants with nonsyndromic craniosynostosis from the University of Michigan Health System. Results show the need for blood transfusion ranged from 94.1 percent among patients in the smallest quartile for temporal fat pad volume compared with 65.7 percent among the group with the largest quartile for temporal fat pad volume (p = 0.0057). Using multivariable linear regression, temporal fat pad volume (p = 0.012) and fat pad thickness (p = 0.036) were independent predictors for amount of packed red blood cells required.

The authors demonstrate that patients with diminished temporal fat pad volume are significantly more likely to need increased packed red blood cell transfusions. In addition, by use of multivariable linear regression, their data suggest that temporal fat pad volume and thickness were independent predictors for the amount of required transfusion of packed red blood cells.

Patients with mandibular fracture often have comorbidities and concomitant injuries making the decision for when and how to operate a challenge. Physicians describe "temporalis wasting" as a finding that indicates frailty; however, this is a subjective finding without quantitative values. In this study, we demonstrate that decreased morphomic values of the temporalis muscle and zygomatic bone are an objective measure of frailty associated with increased injury-induced morbidity as well as negative impact on overall hospital-based clinical outcomes in patients with mandible fracture.

Computed tomographic (CT) scans from all patients with a diagnosis of a mandible fracture in the University of Michigan trauma registry and with a hospital admission were collected from the years 2004 to 2011. Automated, high-throughput CT analysis was used to reconstruct the anatomy and quantify morphomic values (temporalis volume, area and thickness, and zygomatic thickness) in these patients using MATLAB v13.0 (MathWorks Inc, Natick, MA, USA). Subsequently, a subset of 16 individuals with a Glasgow Coma Scale of 14 or 15 was analyzed to control for brain injury. Clinical data were obtained, and the association between morphomic measurements and clinical outcomes was evaluated using Pearson correlation for unadjusted analysis and multiple regression for adjusted analysis.

The mean age of patients in the study was 47.1 years. Unadjusted analysis using Pearson correlation revealed that decreases in zygomatic bone thickness correlated strongly with increases in hospital, intensive care unit, and ventilator days (P < 0.0001, P = 0.0003, and P < 0.0017, respectively). Furthermore, we found that decreases in temporalis mean thickness correlated with increases in hospital and ventilator days (P = 0.0264 and P = 0.0306, respectively). Similarly, decreases in temporalis local mean thickness are significantly correlated with increases in hospital and ventilator days (P = 0.0232 and P = 0.0472, respectively).

Decreased thicknesses of the zygomatic bone and temporalis muscle are significantly correlated with higher hospital, ventilator, and intensive care unit days in patients with mandibular fracture receiving reconstructive operations. This morphomic methodology provides an accurate, quantitative means to evaluate craniofacial trauma patient frailty, injury, and outcomes using routinely obtained CT scans. In the future, we plan to apply this approach to determine preoperative risk stratification and assist in surgical planning.

The human body changes as it becomes older. The automotive safety community has been interested in understanding the effect of aging on restraint performance. Recent research has been focused on assessing the structural and material changes associated with age. In this study, structural tissue distribution was determined using the computed tomography (CT) scan data of more than 19,000 patients, aged 16 and up. The data consisted of subcutaneous fat cross-sectional area, visceral fat cross-sectional area, and trabecular bone density taken at each vertebral level. The data was quantified as a function of five age groups with the youngest group defined as 16-29 years old and the oldest group as 75 and up. An additional analysis stratified on gender was carried out. Overall, visceral fat increased with age. Compared to the 16-29 group, the visceral fat measured at the L1 level was 1.97 in the 30-44 group, 2.55 in the 45-59 group, 3.33 in the 60-74 group and 3.21 times greater in the 75+ group. Subcutaneous fat also increased with age up to the 60-74-year-old group. The subcutaneous fat measured at L1 level was 1.34 in the 30-44 group, 1.39 in the 45-59 group, 1.38 in the 60-74 group and 1.09 times greater in the 75+ group than in the 16-29 group. A significant association between trabecular bone density and age was found. Trabecular bone density in Hounsfield units (HU) decreased as a function of age, by 2.57*age +0.0056*age₂ for females and 2.57*age +0.0082*age₂ for males. Gender differences were also observed. Females had 1.43 times more subcutaneous fat and 1.10 times higher trabecular bone density than males at L1, while males had 1.88 times more visceral fat than females. Females gained more subcutaneous fat at L1 as they increased in age up to the 45-59 group and then progressively lost subcutaneous fat. Males and females gained more visceral fat at L1 as they aged up to the 60-74 group. Both consistently lost bone density at L1 as they grew older. The data was also analyzed for a male subgroup approximating the height and weight of a 50^th percentile male dummy. Visceral fat increased with age while trabecular bone density decreased. There was an overall-trend for an increase in subcutaneous fat with age. The results obtained in this study provide insight on the quantified effect of bone and fat distribution as a function of age, gender, and vertebral level. Fat and bone distribution needs to be considered in human mathematical models used to develop safety countermeasures for the older population.