Reference values of liver volume in Caucasian population and factors influencing liver size

Liver shape analysis using statistical parametric maps at population scale

BACKGROUND

Morphometric image analysis enables the quantification of differences in the shape and size of organs between individuals.

METHODS

Here we have applied morphometric methods to the study of the liver by constructing surface meshes from liver segmentations from abdominal MRI images in 33,434 participants in the UK Biobank. Based on these three dimensional mesh vertices, we evaluated local shape variations and modelled their association with anthropometric, phenotypic and clinical conditions, including liver disease and type-2 diabetes.

RESULTS

We found that age, body mass index, hepatic fat and iron content, as well as, health traits were significantly associated with regional liver shape and size. Interaction models in groups with specific clinical conditions showed that the presence of type-2 diabetes accelerates age-related changes in the liver, while presence of liver fat further increased shape variations in both type-2 diabetes and liver disease.

CONCLUSIONS

The results suggest that this novel approach may greatly benefit studies aiming at better categorisation of pathologies associated with acute and chronic clinical conditions.

Artificial Intelligence for Improved Hepatosplenomegaly Diagnosis

Hepatosplenomegaly is commonly diagnosed by radiologists based on single dimension measurements and heuristic cut-offs. Volumetric measurements may be more accurate for diagnosing organ enlargement. Artificial intelligence techniques may be able to automatically calculate liver and spleen volume and facilitate more accurate diagnosis. After IRB approval, 2 convolutional neural networks (CNN) were developed to automatically segment the liver and spleen on a training dataset comprised of 500 single-phase, contrast-enhanced CT abdomen and pelvis examinations. A separate dataset of ten thousand sequential examinations at a single institution was segmented with these CNNs. Performance was evaluated on a 1% subset and compared with manual segmentations using Sorensen-Dice coefficients and Pearson correlation coefficients. Radiologist reports were reviewed for diagnosis of hepatomegaly and splenomegaly and compared with calculated volumes. Abnormal enlargement was defined as greater than 2 standard deviations above the mean. Median Dice coefficients for liver and spleen segmentation were 0.988 and 0.981, respectively. Pearson correlation coefficients of CNN-derived estimates of organ volume against the gold-standard manual annotation were 0.999 for the liver and spleen (P < 0.001). Average liver volume was 1556.8 ± 498.7 cc and average spleen volume was 194.6 ± 123.0 cc. There were significant differences in average liver and spleen volumes between male and female patients. Thus, the volume thresholds for ground-truth determination of hepatomegaly and splenomegaly were determined separately for each sex. Radiologist classification of hepatomegaly was 65% sensitive, 91% specific, with a positive predictive value (PPV) of 23% and an negative predictive value (NPV) of 98%. Radiologist classification of splenomegaly was 68% sensitive, 97% specific, with a positive predictive value (PPV) of 50% and a negative predictive value (NPV) of 99%. Convolutional neural networks can accurately segment the liver and spleen and may be helpful to improve radiologist accuracy in the diagnosis of hepatomegaly and splenomegaly.

The effect of hepatic steatosis on liver volume determined by proton density fat fraction and deep learning-measured liver volume

OBJECTIVES

We aimed to evaluate the effect of hepatic steatosis (HS) on liver volume and to develop a formula to estimate lean liver volume correcting the HS effect.

METHODS

This retrospective study included healthy adult liver donors who underwent gadoxetic acid-enhanced MRI and proton density fat fraction (PDFF) measurement from 2015 to 2019. The degree of HS was graded at 5% PDFF intervals from grade 0 (no HS; PDFF < 5.5%). Liver volume was measured with hepatobiliary phase MRI using deep learning algorithm, and standard liver volume (SLV) was calculated as the reference lean liver volume. The association between liver volume and SLV ratio with PDFF grades was evaluated using Spearman's correlation (ρ). The effect of PDFF grades on liver volume was evaluated using the multivariable linear regression model.

RESULTS

The study population included 1038 donors (mean age, 31 ± 9 years; 689 men). Mean liver volume to SLV ratio increased according to PDFF grades (ρ = 0.234, p < 0.001). The multivariable analysis indicated that SLV (β = 1.004, p < 0.001) and PDFF grade*SLV (β = 0.044, p < 0.001) independently affected liver volume, suggesting a 4.4% increase in liver volume per one-point increment in the PDFF grade. PDFF-adjusted lean liver volume was estimated using the formula, liver volume/[1.004 + 0.044 × PDFF grade]. The mean estimated lean liver volume to SLV ratio approximated to one for all PDFF grades, with no significant association with PDFF grades (p = 0.851).

CONCLUSION

HS increases liver volume. The formula to estimate lean liver volume may be useful to adjust for the effect of HS on liver volume.

KEY POINTS

• Hepatic steatosis increases liver volume. • The presented formula to estimate lean liver volume using MRI-measured proton density fat fraction and liver volume may be useful to adjust for the effect of hepatic steatosis on measured liver volume.

Computed tomography-based measurements of normative liver and spleen volumes in children

BACKGROUND

Quantification of organ size has utility in clinical care and research for diagnostics, prognostics and surgical planning. Volumetry is regarded as the best measure of organ size and change in size over time. Scarce reference values exist for liver and spleen volumes in healthy children.

OBJECTIVE

To report liver and spleen volumes for a sample of children defined by manual segmentation of contrast-enhanced CT images with the goal of defining normal values and thresholds that might indicate disease.

MATERIALS AND METHODS

This retrospective study included clinically acquired contrast-enhanced CTs of the abdomen/pelvis for children and adolescents imaged between January 2018 and July 2021. Liver and spleen volumes were derived through manual segmentation of CTs reconstructed at 2.5-, 3- or 5-mm slice thickness. A subset of images (5%, n=16) was also segmented using 0.5-mm slice thickness reconstructions to define agreement based on image slice thickness. We used Pearson correlation and multivariable regression to assess associations between organ volumes and patient characteristics. We generated reference intervals for the 5th, 25th, 50th (median), 75th and 95th percentiles for organ volumes as a function of age and weight using quantile regression models. Finally, we calculated Bland-Altman plots and intraclass correlation coefficients (ICC) to quantify agreement.

RESULTS

We included a total of 320 children (mean age ± standard deviation [SD] = 9±4.6 years; mean weight 38.1±18.8 kg; 160 female). Liver volume ranged from 340-2,002 mL, and spleen volume ranged from 28-480 mL. Patient weight (kg) (β=12.5), age (months) (β=1.7) and sex (female) (β = -35.3) were independent predictors of liver volume, whereas patient weight (kg) (β=2.4) and age (months) (β=0.3) were independent predictors of spleen volume. There was excellent absolute agreement (ICC=0.99) and minimal absolute difference (4 mL) in organ volumes based on reconstructed slice thickness.

CONCLUSION

We report reference liver and spleen volumes for children without liver or spleen disease. These results provide reference ranges and potential thresholds to identify liver and spleen size abnormalities that might reflect disease in children.

Population Based Average Parotid Gland Volume and Prevalence of Incidental Tumors in T1-MRI

Representative epidemiologic data on the average volume of the parotid gland in a large population-based MRI survey is non-existent. Within the Study of Health in Pomerania (SHIP), we examined the parotid gland in 1725 non-contrast MRI-scans in T1 weighted sequence of axial layers. Thus, a reliable standard operating procedure (Intraclass Correlation Coefficient > 0.8) could be established. In this study, we found an average, single sided parotid gland volume of 27.82 cm3 (95% confidence interval (CI) 27.15 to 28.50) in male and 21.60 cm3 (95% CI 21.16 to 22.05) in female subjects. We observed positive associations for age, body mass index (BMI), as well as male sex with parotid gland size in a multivariate model. The prevalence of incidental tumors within the parotid gland regardless of dignity was 3.94% in the Northeast German population, slightly higher than assumed. Further epidemiologic investigations regarding primary salivary gland diseases are necessary.

Liver and spleen volumes are associated with prognosis of compensated and decompensated cirrhosis and parallel its natural history

Objective

Cirrhosis is characterized by the complex interplay among biological, histological and haemodynamic events. Liver and spleen remodelling occur throughout its natural history, but the prognostic role of these volumetric changes is unclear. We evaluated the relationship between volumetric changes assessed by multidetector computerised tomography (MDCT) and landmark features of cirrhosis.

Methods

We included consecutive cirrhotic patients who underwent liver transplantation (LT) or hepatocellular carcinoma (HCC) resection in whom dynamic MDCT was available. Different volumetric indices were calculated. Fibrosis was evaluated by the collagen proportional area and Laennec sub‐stages. Correlation and logistic regression analysis were performed to explore associations of volumetric indexes and fibrosis with key prognostic features across the clinical stages of cirrhosis.

Results

185 patients were included (146 LT; 39 HCC); the predominant aetiology was viral hepatitis (51.35%); 65.9% had decompensated disease and 85.08% clinically significant portal hypertension (CSPH). The standardised liver volume and liver‐spleen volume ratio negatively correlated with Model for End‐stage Liver Disease (MELD), albumin and hepatic venous pressure gradient (HVPG) and were significantly lower in decompensated patients. The liver segmental volume ratio (segments I–III/segments IV–VIII) best captured the characteristic features of the compensated phase, showing a positive correlation with HVPG and a good discrimination between patients with and without CSPH and varices. Volumetric changes and fibrosis severity were independently associated with key prognostic events, with no association between these two parameters.

Conclusions

Liver and spleen volumetric indices evolve differently along the natural history of cirrhosis and are associated with key prognostic factors in each phase, regardless of fibrosis severity and portal hypertension.

Application of machine learning in liver transplantation: a review

BACKGROUND

Machine learning (ML) has been increasingly applied in the health-care and liver transplant setting. The demand for liver transplantation continues to expand on an international scale, and with advanced aging and complex comorbidities, many challenges throughout the transplantation decision-making process must be better addressed. There exist massive datasets with hidden, non-linear relationships between demographic, clinical, laboratory, genetic, and imaging parameters that conventional methods fail to capitalize on when reviewing their predictive potential. Pre-transplant challenges include addressing efficacies of liver segmentation, hepatic steatosis assessment, and graft allocation. Post-transplant applications include predicting patient survival, graft rejection and failure, and post-operative morbidity risk.

AIM

In this review, we describe a comprehensive summary of ML applications in liver transplantation including the clinical context and how to overcome challenges for clinical implementation.

METHODS

Twenty-nine articles were identified from Ovid MEDLINE, MEDLINE Epub Ahead of Print and In-Process and Other Non-Indexed Citations, Embase, Cochrane Database of Systematic Reviews, and Cochrane Central Register of Controlled Trials.

CONCLUSION

ML is vastly interrogated in liver transplantation with promising applications in pre- and post-transplant settings. Although challenges exist including site-specific training requirements, the demand for more multi-center studies, and optimization hurdles for clinical interpretability, the powerful potential of ML merits further exploration to enhance patient care.

Associations of liver volume and other markers of hepatic steatosis with all-cause mortality in the general population

AIMS

We examined the associations between liver volume and other quantitative and qualitative markers of hepatic steatosis with all-cause mortality in the general population.

METHODS

We included 2769 German middle-aged individuals with a median follow-up of 8.9 years (23,898 person-years). Quantitative markers used were serum liver enzymes and FIB-4 score, while qualitative markers of hepatic steatosis included magnetic resonance imaging (MRI) measurements of liver fat content and total liver volume. Cox proportional hazards models, adjusted for confounding factors, were undertaken to investigate the associations of liver volume and other markers of hepatic steatosis with all-cause mortality.

RESULTS

A larger MRI-assessed liver volume was associated with a nearly three-fold increased risk of all-cause mortality (Hazard Ratio = 3.16; 95% confidence interval 1.88; 5.30), independent of age, sex, body mass index, food frequency score, alcohol consumption and education level. This association was consistent in all subgroups considered (men vs. women; presence or absence of overweight/obesity, metabolic syndrome or diabetes). Higher serum liver enzyme levels and FIB-4 score were also significantly associated with higher all-cause mortality in the total population and in all subgroups. No independent associations were found between other quantitative and qualitative markers of hepatic steatosis and the risk of all-cause mortality.

CONCLUSIONS

We showed for the first time that larger liver volume was associated with a three-fold increase in long-term risk of all-cause mortality. This association remained significant after adjustment for age, sex, alcohol consumption, obesity and other coexisting metabolic disorders.

Correlation between anthropometric data and preparatory maneuvers difficulties during laparoscopic right liver resections: a single center prospective study

PURPOSE

The difficulty of laparoscopic right liver resections (LRLR) is mainly associated with their poor accessibility. Anthropometric data rather than BMI was reported to predict transection time and blood loss. Aim of the study was to evaluate the correlation between anthropometric data and preparatory manoeuvres difficulties during LRLR.

METHODS

All patients who underwent LRLR requiring full right liver mobilization from November 2019 to March 2021 were prospectively included in the study. Data on surgeons' difficulty perceptions on liver mobilization (LM), isolation of right hepatic vein (RHVI), liver manageability and visibility were rated with a 5-point scale. Data on cranio-caudal liver diameters (CCliv), CHALLENGE Index (CCliv/latero-lateral abdomen diameter), times needed to LM and RHVI were collected.

RESULTS

Sixty-five patients (29 wedge and 36 anatomical resections) with a median BMI of 25.5 were analysed. One patient required open conversion due to oncological reason. No correlations between BMI and CCliv or CHALLENGE Index were found. Larger CCliv diameter correlated with longer time for both RHVI (r = 0.589, p = 0.002) and LM (r = 0.222, p = 0.049). Higher CHALLENGE index correlated with longer time for RHVI (r = 0.589, p = 0.002). The CHALLENGE index showed a linear correlation with difficulty to the isolation of RHV (r = 0.327, p = 0.045), whilst the liver manipulation difficulty increased with latero-lateral liver diameter (r = 0.244, p = 0.033). BMI had no correlation with the duration of preparatory maneuvers neither with surgeons' difficulties.

CONCLUSIONS

Anthropometric data can help to anticipate the difficulty of preparatory maneuvers during laparoscopic right liver resections.

Efficacy and Safety of Trans-Arterial Yttrium-90 Radioembolization in Patients with Unresectable Liver-Dominant Metastatic or Primary Hepatic Soft Tissue Sarcomas

Simple Summary

Sarcomas of the liver are a rare and aggressive group of malignancies for which surgery is the preferred treatment modality even though most patients are not surgical candidates and receive chemotherapy with poor outcomes. In these cases, trans-arterial liver-directed therapies are emerging as a new treatment option. Among these, radioembolization is a promising but understudied treatment option. In radioembolization, microbeads conjugated to a radioactive drug are injected into the blood vessels, nourishing the cancers and leading to cell death and tumor shrinkage. In this study, we retrospectively analyzed 35 patients with liver sarcomas receiving radioembolization at our institution. We found that those with disease control in the liver 6 months after the procedure had longer overall survival as well as patients with a liver progression-free interval post-procedure equal to or greater than 9 months. Patients with good performance status and normal liver function at baseline also had longer survival. The most common adverse reactions were nausea, fatigue, abdominal pain, and mild reversible abnormalities in liver function tests. Overall, our results suggest that radioembolization might be a safe and effective treatment option for patients with unresectable liver sarcomas.

Abstract

Patients with liver-dominant metastatic or primary hepatic soft tissue sarcomas (STS) have poor prognosis. Surgery can prolong survival, but most patients are not surgical candidates, and treatment response is limited with systemic chemotherapy. Liver-directed therapies have been increasingly employed in this setting, and Yttrium-90 trans-arterial radioembolization (TARE) is an understudied yet promising treatment option. This is a retrospective analysis of 35 patients with metastatic or primary hepatic STS who underwent TARE at a single institution between 2006 and 2020. The primary outcomes that were measured were overall survival (OS), liver progression-free survival (LPFS), and radiologic tumor response. Clinical and biochemical toxicities were assessed 3 months after the procedure. Median OS was 20 months (95% CI: 13.9–26.1 months), while median LPFS was 9 months (95% CI: 6.2–11.8 months). The objective response rate was 56.7%, and the disease control rate was 80.0% by mRECIST at 3 months. The following correlated with better OS post-TARE: liver disease control (DC) at 6 months (median OS: 40 vs. 17 months, p = 0.007); LPFS ≥ 9 months (median OS: 50 vs. 8 months, p < 0.0001); ECOG status 0–1 vs. 2 (median OS: 22 vs. 6 months, p = 0.042); CTP class A vs. B (median OS: 22 vs. 6 months, p = 0.018); and TACE post-progression (median OS: 99 vs. 16 months, p = 0.003). The absence of metastases at diagnosis was correlated with higher median LPFS (7 vs. 1 months, p = 0.036). Two grade 4 (5.7%) and ten grade 3 (28.6%) laboratory toxicities were identified at 3 months. There was one case of radioembolization-induced liver disease and two cases of radiation-induced peptic ulcer disease. We concluded that TARE could be an effective and safe treatment option for patients with metastatic or primary hepatic STS with good tumor response rates, low incidence of severe toxicity, and longer survival in patients with liver disease control post-TARE.

SHIP-MR and Radiology: 12 Years of Whole-Body Magnetic Resonance Imaging in a Single Center

The Study of Health in Pomerania (SHIP), a population-based study from a rural state in northeastern Germany with a relatively poor life expectancy, supplemented its comprehensive examination program in 2008 with whole-body MR imaging at 1.5 T (SHIP-MR). We reviewed more than 100 publications that used the SHIP-MR data and analyzed which sequences already produced fruitful scientific outputs and which manuscripts have been referenced frequently. Upon reviewing the publications about imaging sequences, those that used T1-weighted structured imaging of the brain and a gradient-echo sequence for R2* mapping obtained the highest scientific output; regarding specific body parts examined, most scientific publications focused on MR sequences involving the brain and the (upper) abdomen. We conclude that population-based MR imaging in cohort studies should define more precise goals when allocating imaging time. In addition, quality control measures might include recording the number and impact of published work, preferably on a bi-annual basis and starting 2 years after initiation of the study. Structured teaching courses may enhance the desired output in areas that appear underrepresented.

Physiologically based pharmacokinetic (PBPK) modeling of meloxicam in different CYP2C9 genotypes

Meloxicam, a non-steroidal anti-inflammatory drug, is used for the treatment of rheumatoid arthritis and osteoarthritis. Cytochrome P450 (CYP) 2C9 and CYP3A4 are major and minor enzymes involved in the metabolism of meloxicam. Impaired enzyme activity of CYP2C9 variants increases the plasma exposures of meloxicam and the risk of adverse events. The objective of our study is to develop and validate the physiologically based pharmacokinetic (PBPK) model of meloxicam related to CYP2C9 genetic polymorphism using the PK-Sim^® software. In vitro k_cat of CYP2C9 was optimized in different CYP2C9 genotypes. The demographic and pharmacokinetic dataset for the development of the PBPK model was extracted from two previous clinical pharmacokinetic studies. Thirty-one clinical datasets, representing different dose regimens and demographic characteristics, were utilized to validate the PBPK model. The shapes of simulated plasma concentration-time profiles in each CYP2C9 genotype were visually similar to observed profiles. The predicted exposures (AUC_inf) of meloxicam in CYP2C9*1/*3, CYP2C9*1/*13, and CYP2C9*3/*3 genotypes were increased by 1.77-, 2.91-, and 8.35-fold compared to CYP2C9*1/*1 genotype, respectively. In all datasets for the development and validations, fold errors between predicted and observed pharmacokinetic parameters were within the two-fold error criteria. As a result, the PBPK model was appropriately established and properly described the pharmacokinetics of meloxicam in different CYP2C9 genotypes. This study is expected to contribute to reducing the risk of adverse events of meloxicam through optimization of meloxicam dosing in different CYP2C9 genotypes.

Standard liver weight model in adult deceased donors with fatty liver: A prospective cohort study

BACKGROUND

Standard liver weight (SLW) is frequently used in deceased donor liver transplantation to avoid size mismatches with the recipient. However, some deceased donors (DDs) have fatty liver (FL). A few studies have reported that FL could impact liver size. To the best of our knowledge, there are no relevant SLW models for predicting liver size.

AIM

To demonstrate the relationship between FL and total liver weight (TLW) in detail and present a related SLW formula.

METHODS

We prospectively enrolled 212 adult DDs from West China Hospital of Sichuan University from June 2019 to February 2021, recorded their basic information, such as sex, age, body height (BH) and body weight (BW), and performed abdominal ultrasound (US) and pathological biopsy (PB). The chi-square test and kappa consistency score were used to assess the consistency in terms of FL diagnosed by US relative to PB. Simple linear regression analysis was used to explore the variables related to TLW. Multiple linear regression analysis was used to formulate SLW models, and the root mean standard error and interclass correlation coefficient were used to test the fitting efficiency and accuracy of the model, respectively. Furthermore, the optimal formula was compared with previous formulas.

RESULTS

Approximately 28.8% of DDs had FL. US had a high diagnostic ability (sensitivity and specificity were 86.2% and 92.9%, respectively; kappa value was 0.70, P < 0.001) for livers with more than a 5% fatty change. Simple linear regression analysis showed that sex (R², 0.226; P < 0.001), BH (R², 0.241; P < 0.001), BW (R², 0.441; P < 0.001), BMI (R², 0.224; P < 0.001), BSA (R², 0.454; P < 0.001) and FL (R², 0.130; P < 0.001) significantly impacted TLW. In addition, multiple linear regression analysis showed that there was no significant difference in liver weight between the DDs with no steatosis and those with steatosis within 5%. Furthermore, in the context of hepatic steatosis, TLW increased positively (non-linear); compared with the TLW of the non-FL group, the TLW of the groups with hepatic steatosis within 5%, between 5% and 20% and more than 20% increased by 0 g, 90 g, and 340 g, respectively. A novel formula, namely, -348.6 + (110.7 x Sex [0 = Female, 1 = Male]) + 958.0 x BSA + (179.8 x FL_US [0 = No, 1 = Yes]), where FL was diagnosed by US, was more convenient and accurate than any other formula for predicting SLW.

CONCLUSION

FL is positively correlated with TLW. The novel formula deduced using sex, BSA and FL_US is the optimal formula for predicting SLW in adult DDs.

Genetic Evidence for Different Adiposity Phenotypes and Their Opposing Influences on Ectopic Fat and Risk of Cardiometabolic Disease

To understand the causal role of adiposity and ectopic fat in type 2 diabetes and cardiometabolic diseases, we aimed to identify two clusters of adiposity genetic variants: one with "adverse" metabolic effects (UFA) and the other with, paradoxically, "favorable" metabolic effects (FA). We performed a multivariate genome-wide association study using body fat percentage and metabolic biomarkers from UK Biobank and identified 38 UFA and 36 FA variants. Adiposity-increasing alleles were associated with an adverse metabolic profile, higher risk of disease, higher CRP, and higher fat in subcutaneous and visceral adipose tissue, liver, and pancreas for UFA and a favorable metabolic profile, lower risk of disease, higher CRP and higher subcutaneous adipose tissue but lower liver fat for FA. We detected no sexual dimorphism. The Mendelian randomization studies provided evidence for a risk-increasing effect of UFA and protective effect of FA for type 2 diabetes, heart disease, hypertension, stroke, nonalcoholic fatty liver disease, and polycystic ovary syndrome. FA is distinct from UFA by its association with lower liver fat and protection from cardiometabolic diseases; it was not associated with visceral or pancreatic fat. Understanding the difference in FA and UFA may lead to new insights in preventing, predicting, and treating cardiometabolic diseases.

Analysis of factors associated with discrepancies between predicted and observed liver weight in liver transplantation

BACKGROUND

Even using predictive formulas based on anthropometrics in about 30% of subjects, liver weight (LW) cannot be predicted with a ≤20% margin of error. We aimed to identify factors associated with discrepancies between predicted and observed LW.

METHODS

In 500 consecutive liver grafts, we tested LW predictive performance using 17 formulas based on anthropometric characteristics. Hashimoto's formula (961.3 × BSA_D-404.8) was associated with the lowest mean absolute error and used to predict LW for the entire cohort. Clinical factors associated with a ≥20% margin of error were identified in a multivariable analysis after propensity score matching (PSM) of donors with similar anthropometric characteristics.

RESULTS

The total LW was underestimated with a ≥20% margin of error in 53/500 (10.6%) donors and overestimated in 62/500 (12%) donors. After PSM analysis, ages ≥ 65, (OR = 3.21; CI95% = 1.63-6.31; P = .0007), age ≤ 30 years, (OR = 2.92; CI95% = 1.15-7.40; P = .02), and elevated gamma-glutamyltransferase (GGT) levels (OR = 0.98; CI95% = 0.97-0.99; P = .006), influenced the risk of LW overestimation. Age ≥ 65 years, (OR = 5.98; CI95% = 2.28-15.6; P = .0002), intensive care unit (ICU) stay with ventilation > 7 days, (OR = 0.32; CI95% = 0.12-0.85; P = .02) and waist circumference increase (OR = 1.02; CI95% = 1.00-1.04; P = .04) were factors associated with LW underestimation.

CONCLUSIONS

Increased waist circumference, age, prolonged ICU stay with ventilation, elevated GGT were associated with an increase in the margin of error in LW prediction. These factors and anthropometric characteristics could help transplant surgeons during the donor-recipient matching process.

Predicting the available space for liver transplantation in cirrhotic patients: a computed tomography-based volumetric study

BACKGROUND

Anthropometric parameters (weight, height) are usually used for quick matching between two individuals (donor and recipient) in liver transplantation (LT). This study aimed to evaluate clinical factors influencing the overall available space for implanting a liver graft in cirrhotic patients.

METHODS

In a cohort of 275 cirrhotic patients undergoing LT, we calculated the liver volume (LV), cavity volume (CV), which is considered the additional space between the liver and the right hypocondrium, and the overall volume (OV = LV + CV) using a computed tomography (CT)-based volumetric system. We then chose the formula based on anthropometric parameters that showed the best predictive value for LV. This formula was used to predict the OV in the same population. Factors influencing OV variations were identified by multivariable logistic analysis.

RESULTS

The Hashimoto formula (961.3 × BSA_D-404.8) yielded the lowest median absolute percentage error (21.7%) in predicting the LV. The median LV was 1531 ml. One-hundred eighty-five patients (67.2%) had a median CV of 1156 ml (range: 70-7006), and the median OV was 2240 ml (range: 592-8537). Forty-nine patients (17%) had an OV lower than that predicted by the Hashimoto formula. Independent factors influencing the OV included the number of portosystemic shunts, right anteroposterior abdominal diameter, model for end-stage liver disease (MELD) score > 25, high albumin value, and BMI > 30.

CONCLUSIONS

Additional anthropometric characteristics (right anteroposterior diameter, body mass index) clinical (number of portosystemic shunts), and biological (MELD, albumin) factors might influence the overall volume available for liver graft implantation. Knowledge of these factors might be helpful during the donor-recipient matching.

Impact of anthropometric data on technical difficulty of laparoscopic liver of resections of segments 7 and 8: the CHALLENGE index

BACKGROUND

The high technical difficulty of using a laparoscopic approach to reach the posterosuperior liver segments is mainly associated with their poor accessibility. This study was performed to analyze correlations between anthropometric data and intraoperative outcomes.

STUDY DESIGN

All patients who underwent segmentectomy or wedge laparoscopic liver resection (LLR) of segments seven and/or eight from June 2012 to November 2019 were retrospectively analyzed. The exclusion criteria were intrahepatic cholangiocarcinoma, associated resection, multiple concomitant LLR, redo resection, and lack of preoperative imaging. Anthropometric data were correlated with intraoperative outcomes.

RESULTS

Forty-one patients (wedge resection, n = 32; segmentectomy, n = 9) were analyzed. A strong correlation was found between the craniocaudal liver diameter (CCliv) and liver volume (r = 0.655, p < 0.001). The anteroposterior liver diameter was moderately correlated with both the laterolateral abdominal diameter (LLabd) (r = 0.372, p = 0.008) and anteroposterior abdominal diameter (r = 0.371, p = 0.008). The body mass index (BMI) was not correlated with liver diameters. Women had a longer CCliv (p = 0.002) and shorter LLabd (p < 0.001) than men. The liver and abdominal measurements were combined to reduce this sex-related disparity. The CCliv/LLabd ratio (CHALLENGE index) was significantly correlated with the time of transection (r = 0.382, p = 0.037) and blood loss (r = 0.352, p = 0.029). The association between the CHALLENGE index and intraoperative blood loss was even stronger when considering only anatomical resection (r = 0.577, p = 0.048). A CHALLENGE index of > 0.4 (area under the curve, 0.757; p = 0.046) indicated a higher bleeding risk. The BMI predicted no intraoperative outcomes.

CONCLUSION

Anthropometric data rather than the BMI can help anticipate the difficulty of LLR of segments seven and eight.

Comparison of semi-automatic and deep learning-based automatic methods for liver segmentation in living liver transplant donors

PURPOSE

To compare the accuracy and repeatability of emerging machine learning based (i.e. deep) automatic segmentation algorithms with those of well-established semi-automatic (interactive) methods for determining liver volume in living liver transplant donors at computerized tomography (CT) imaging.

METHODS

A total of 12 (6 semi-, 6 full-automatic) methods are evaluated. The semi-automatic segmentation algorithms are based on both traditional iterative models including watershed, fast marching, region growing, active contours and modern techniques including robust statistical segmenter and super-pixels. These methods entail some sort of interaction mechanism such as placing initialization seeds on images or determining a parameter range. The automatic methods are based on deep learning and they include three framework templates (DeepMedic, NiftyNet and U-Net) the first two of which are applied with default parameter sets and the last two involve adapted novel model designs. For 20 living donors (6 training and 12 test datasets), a group of imaging scientists and radiologists created ground truths by performing manual segmentations on contrast material-enhanced CT images. Each segmentation is evaluated using five metrics (i.e. volume overlap and relative volume errors, average/RMS/maximum symmetrical surface distances). The results are mapped to a scoring system and a final grade is calculated by taking their average. Accuracy and repeatability were evaluated using slice by slice comparisons and volumetric analysis. Diversity and complementarity are observed through heatmaps. Majority voting and Simultaneous Truth and Performance Level Estimation (STAPLE) algorithms are utilized to obtain the fusion of the individual results.

RESULTS

The top four methods are determined to be automatic deep models having 79.63, 79.46 and 77.15 and 74.50 scores. Intra-user score is determined as 95.14. Overall, deep automatic segmentation outperformed interactive techniques on all metrics. The mean volume of liver of ground truth is found to be 1409.93 mL ± 271.28 mL, while it is calculated as 1342.21 mL ± 231.24 mL using automatic and 1201.26 mL ± 258.13 mL using interactive methods, showing higher accuracy and less variation on behalf of automatic methods. The qualitative analysis of segmentation results showed significant diversity and complementarity enabling the idea of using ensembles to obtain superior results. The fusion of automatic methods reached 83.87 with majority voting and 86.20 using STAPLE that are only slightly less than fusion of all methods that achieved 86.70 (majority voting) and 88.74 (STAPLE).

CONCLUSION

Use of the new deep learning based automatic segmentation algorithms substantially increases the accuracy and repeatability for segmentation and volumetric measurements of liver. Fusion of automatic methods based on ensemble approaches exhibits best results almost without any additional time cost due to potential parallel execution of multiple models.