Variability of standard liver volume estimation versus software-assisted total liver volume measurement

Living Donor Liver Transplantation for Adults With High Model for End-stage Liver Disease Score: The US Experience

BACKGROUND

Outcomes after living-donor liver transplantation (LDLT) at high Model for End-stage Liver Disease (MELD) scores are not well characterized in the United States.

METHODS

This was a retrospective cohort study using Organ Procurement and Transplantation Network data in adults listed for their first liver transplant alone between 2002 and 2021. Cox proportional hazards models evaluated the association of MELD score (<20, 20-24, 25-29, and ≥30) and patient/graft survival after LDLT and the association of donor type (living versus deceased) on outcomes stratified by MELD.

RESULTS

There were 4495 LDLTs included with 5.9% at MELD 25-29 and 1.9% at MELD ≥30. LDLTs at MELD 25-29 and ≥30 LDLT have substantially increased since 2010 and 2015, respectively. Patient survival at MELD ≥30 was not different versus MELD <20: adjusted hazard ratio 1.67 (95% confidence interval, 0.96-2.88). However, graft survival was worse: adjusted hazard ratio (aHR) 1.69 (95% confidence interval, 1.07-2.68). Compared with deceased-donor liver transplant, LDLT led to superior patient survival at MELD <20 (aHR 0.92; P = 0.024) and 20-24 (aHR 0.70; P < 0.001), equivalent patient survival at MELD 25-29 (aHR 0.97; P = 0.843), but worse graft survival at MELD ≥30 (aHR 1.68, P = 0.009).

CONCLUSIONS

Although patient survival remains acceptable, the benefits of LDLT may be lost at MELD ≥30.

Liver volumetric and anatomic assessment in living donor liver transplantation: The role of modern imaging and artificial intelligence

The shortage of deceased donor organs has prompted the development of alternative liver grafts for transplantation. Living-donor liver transplantation (LDLT) has emerged as a viable option, expanding the donor pool and enabling timely transplantation with favorable graft function and improved long-term outcomes. An accurate evaluation of the donor liver's volumetry (LV) and anatomical study is crucial to ensure adequate future liver remnant, graft volume and precise liver resection. Thus, ensuring donor safety and an appropriate graft-to-recipient weight ratio. Manual LV (MLV) using computed tomography has traditionally been considered the gold standard for assessing liver volume. However, the method has been limited by cost, subjectivity, and variability. Automated LV techniques employing advanced segmentation algorithms offer improved reproducibility, reduced variability, and enhanced efficiency compared to manual measurements. However, the accuracy of automated LV requires further investigation. The study provides a comprehensive review of traditional and emerging LV methods, including semi-automated image processing, automated LV techniques, and machine learning-based approaches. Additionally, the study discusses the respective strengths and weaknesses of each of the aforementioned techniques. The use of artificial intelligence (AI) technologies, including machine learning and deep learning, is expected to become a routine part of surgical planning in the near future. The implementation of AI is expected to enable faster and more accurate image study interpretations, improve workflow efficiency, and enhance the safety, speed, and cost-effectiveness of the procedures. Accurate preoperative assessment of the liver plays a crucial role in ensuring safe donor selection and improved outcomes in LDLT. MLV has inherent limitations that have led to the adoption of semi-automated and automated software solutions. Moreover, AI has tremendous potential for LV and segmentation; however, its widespread use is hindered by cost and availability. Therefore, the integration of multiple specialties is necessary to embrace technology and explore its possibilities, ranging from patient counseling to intraoperative decision-making through automation and AI.

Role of intelligent/interactive qualitative and quantitative analysis-three-dimensional estimated model in donor-recipient size mismatch following deceased donor liver transplantation

BACKGROUND

Donor-recipient size mismatch (DRSM) is considered a crucial factor for poor outcomes in liver transplantation (LT) because of complications, such as massive intraoperative blood loss (IBL) and early allograft dysfunction (EAD). Liver volumetry is performed routinely in living donor LT, but rarely in deceased donor LT (DDLT), which amplifies the adverse effects of DRSM in DDLT. Due to the various shortcomings of traditional manual liver volumetry and formula methods, a feasible model based on intelligent/interactive qualitative and quantitative analysis-three-dimensional (IQQA-3D) for estimating the degree of DRSM is needed.

AIM

To identify benefits of IQQA-3D liver volumetry in DDLT and establish an estimation model to guide perioperative management.

METHODS

We retrospectively determined the accuracy of IQQA-3D liver volumetry for standard total liver volume (TLV) (sTLV) and established an estimation TLV (eTLV) index (eTLVi) model. Receiver operating characteristic (ROC) curves were drawn to detect the optimal cut-off values for predicting massive IBL and EAD in DDLT using donor sTLV to recipient sTLV (called sTLVi). The factors influencing the occurrence of massive IBL and EAD were explored through logistic regression analysis. Finally, the eTLVi model was compared with the sTLVi model through the ROC curve for verification.

RESULTS

A total of 133 patients were included in the analysis. The Changzheng formula was accurate for calculating donor sTLV (P = 0.083) but not for recipient sTLV (P = 0.036). Recipient eTLV calculated using IQQA-3D highly matched with recipient sTLV (P = 0.221). Alcoholic liver disease, gastrointestinal bleeding, and sTLVi > 1.24 were independent risk factors for massive IBL, and drug-induced liver failure was an independent protective factor for massive IBL. Male donor-female recipient combination, model for end-stage liver disease score, sTLVi ≤ 0.85, and sTLVi ≥ 1.32 were independent risk factors for EAD, and viral hepatitis was an independent protective factor for EAD. The overall survival of patients in the 0.85 < sTLVi < 1.32 group was better compared to the sTLVi ≤ 0.85 group and sTLVi ≥ 1.32 group (P < 0.001). There was no statistically significant difference in the area under the curve of the sTLVi model and IQQA-3D eTLVi model in the detection of massive IBL and EAD (all P > 0.05).

CONCLUSION

IQQA-3D eTLVi model has high accuracy in predicting massive IBL and EAD in DDLT. We should follow the guidance of the IQQA-3D eTLVi model in perioperative management.

Distribution of non-ceruloplasmin-bound copper after i.v. 64Cu injection studied with PET/CT in patients with Wilson disease

Background & Aims

In Wilson disease (WD), copper accumulation and increased non-ceruloplasmin-bound copper in plasma lead to liver and brain pathology. To better understand the fate of non-ceruloplasmin-bound copper, we used PET/CT to examine the whole-body distribution of intravenously injected 64-copper (64Cu).

Methods

Eight patients with WD, five heterozygotes, and nine healthy controls were examined by dynamic PET/CT for 90 min and static PET/CT up to 20 h after injection. We measured 64Cu activity in blood and tissue and quantified the kinetics by compartmental analysis.

Results

Initially, a large fraction of injected 64Cu was distributed to extrahepatic tissues, especially skeletal muscle. Thus, across groups, extrahepatic tissues accounted for 45-58% of the injected dose (%ID) after 10 min, and 45-55% after 1 h. Kinetic analysis showed rapid exchange of 64Cu between blood and muscle as well as adipose tissue, with 64Cu retention in a secondary compartment, possibly mitochondria. This way, muscle and adipose tissue may protect the brain from spikes in non-ceruloplasmin-bound copper. Tiny amounts of cerebral 64Cu were detected (0.2%ID after 90 min and 0.3%ID after 6 h), suggesting tight control of cerebral copper in accordance with a cerebral clearance that is 2-3-fold lower than in muscle. Compared to controls, patients with WD accumulated more hepatic copper 6-20 h after injection, and also renal copper at 6 h.

Conclusion

Non-ceruloplasmin-bound copper is initially distributed into a number of tissues before being redistributed slowly to the eliminating organ, the liver. Cerebral uptake of copper is extremely slow and likely highly regulated. Our findings provide new insights into the mechanisms of copper control.

Impact and implications

Maintaining non-ceruloplasmin-bound copper within the normal range is an important treatment goal in WD as this "free" copper is considered toxic to the liver and brain. We found that intravenously injected non-ceruloplasmin-bound copper quickly distributed to a number of tissues, especially skeletal muscle, subcutaneous fat, and the liver, while uptake into the brain was slow. This study offers new insights into the mechanisms of copper control, which may encourage further research into potential new treatment targets.

Clinical trial number

2016-001975-59.

Hemodynamic changes in the portal vein with age: evaluation using four-dimensional flow MRI

Aging process is associated with gradual change of liver function and structure. The goal of this study was to evaluate age-related hemodynamic changes in the portal vein (PV) using four-dimensional (4D) flow MRI in healthy adults. A total of 120 healthy subjects were enrolled and categorized into groups A (n = 25, 30-39 years), B (n = 31, 40-49 years), C (n = 34, 50-59 years), and D (n = 30, 60-69 years). All subjects underwent 4D flow data acquisition using a 3-T MRI system to measure the hemodynamic parameters in the main PV. The clinical characteristics and 4D flow parameters were compared among the groups using analysis of variance and analysis of covariance after controlling for significant covariates, accordingly. The outcome metric applying the age-related quadratic model to estimate the age at which 4D flow parameters are the highest (the peak age) as well as the rates of age-related 4D flow changes was estimated. The average area, average through-plane velocity, peak velocity magnitude, average net flow, peak flow, and net forward volume in group D were significantly lower than those in groups A, B and C (P < 0.05). Group C showed significantly lower values of the average through-plane velocity and peak velocity magnitude than those of group B (P < 0.05). The peak age computed was approximately 43-44 years of age for all 4D flow parameters. The rates of age-related 4D flow changes for all 4D flow parameters were negatively correlated with age (P < 0.05). The volume and velocity of the blood flow through the PV peaked at approximately 43-44 years of age and decreased significantly after 60 years of age.

Preoperative estimation of hemi-liver volume using standard liver volume and portal vein diameter ratio in living donor liver transplantation

Backgrounds/Aims

Although body surface area (BSA)-based standard liver volume (SLV) formulae have been used for living donor liver transplantation and hepatic resection, hemi-liver volume (HLV) is needed more frequently. HLV can be assessed using right or left portal vein diameter (RPVD or LPVD). The aim of this study was to validate the reliability of using portal vein diameter ratio (PVDR) for assessing HLV in living liver donors.

Methods

This study included 92 living liver donors (59 males and 33 females) who underwent surgery between January 2020 and December 2020. Computed tomography (CT) images were used for measurements.

Results

Mean age of donors was 35.5 ± 7.2 years. CT volumetry-measured total liver volume (TLV), right HLV, left HLV, and percentage of right HLV in TLV were 1,442.9 ± 314.2 mL, 931.5 ± 206.4 mL, 551.4 ± 126.5 mL, and 64.6% ± 3.6%, respectively. RPVD, LPVD, and main portal vein diameter were 12.2 ± 1.5 mm, 10.0 ± 1.3 mm, and 15.3 ± 1.7 mm, respectively (corresponding square values: 149.9 ± 36.9 mm², 101.5 ± 25.2 mm², and 237.2 ± 52.2 mm², respectively). The sum of RPVD² and LPVD² was 251.1 ± 56.9 mm². BSA-based SLV was 1,279.5 ± 188.7 mL (error rate: 9.1% ± 14.4%). SLV formula- and PVDR-based right HLV was 760.0 ± 130.7 mL (error rate: 16.2% ± 13.3%).

Conclusions

Combining BSA-based SLV and PVDR appears to be a simple method to predict right or left HLV in living donors or split liver transplantation.

Shulan Estimation Model: A New Formula for Estimation of Standard Liver Volume In Chinese Adults

BACKGROUND

To establish a new and accurate model for standard liver volume (SLV) estimation and graft size prediction in liver transplantation for Chinese adults.

METHODS

In this study, the data of morphologic indices and liver volume (LV) were retrospectively obtained on 507 cadaveric liver transplantation donors between June 2017 and September 2020 in Shulan (Hangzhou) Hospital. Linear regression analysis was performed to evaluate the impact of each parameter and develop a new SLV formula. The new formula was then validated prospectively on 97 donors between October 2020 and June 2021, and the prediction accuracy was compared with previous formulas.

RESULTS

The average LV in all subjects was 1445.68 ± 309.94 mL. Body weight (BW) showing the strongest correlation (r = 0.453, P < .001). By stepwise multiple linear regression analysis, BW and age were the only 2 independent correlation factors for LV. Shulan estimation model derived: SLV (mL) = 13.266 × BW (kg) - 4.693 × age + 797.16 (R2 = 0.236, P < .001). In the validation cohort, our new model achieved no significant differences between the estimated SLV and the actual LV (P > .05), and showed the lowest mean percentage error of 0.33%. The proportions of estimated SLV within the actual LV ± 20%, ± 15%, and ± 10% percentage errors were 69.1%, 55.7%, and 40.2%, respectively.

DISCUSSION

The Shulan SLV estimation model predicted LV more accurately than previous formulas on Chinese adults, which could serve as a simple screening tool during the initial assessment of graft volume for potential donors.

Effect of oral zinc regimens on human hepatic copper content: a randomized intervention study

Zinc inhibits intestinal copper uptake, an effect utilized for treating Wilson’s disease (WD). We used copper-64 (⁶⁴Cu) PET/CT to examine how much four weeks of treatment with different zinc regimens reduced the hepatic ⁶⁴Cu content after oral ⁶⁴Cu administration and test if alternative regimens were noninferior to the standard regimen of zinc acetate 50 mg × 3 daily. Forty healthy persons were randomized to four different zinc protocols. The WD standard treatment zinc acetate 50 mg × 3 reduced the hepatic ⁶⁴Cu content from 26.9 ± 7.5% to 13.3 ± 5.6% of the administered ⁶⁴Cu. Zinc gluconate 50 mg × 3 was noninferior (P = 0.02) (35.8 ± 9.0% to 17.4 ± 7.5%). Zinc acetate 150 mg × 1 (33.1 ± 9.9% to 17.4 ± 7.5%) and zinc gluconate 150 mg × 1 (28.1 ± 6.7% to 22.0 ± 6.7%) were less effective. These effects were intra- and inter-individually highly variable, and 14% had no effect of any zinc regimen, which may explain disparities in zinc treatment efficacy in WD patients.

nnU-Net Deep Learning Method for Segmenting Parenchyma and Determining Liver Volume From Computed Tomography Images

Background

Recipient donor matching in liver transplantation can require precise estimations of liver volume. Currently utilized demographic-based organ volume estimates are imprecise and nonspecific. Manual image organ annotation from medical imaging is effective; however, this process is cumbersome, often taking an undesirable length of time to complete. Additionally, manual organ segmentation and volume measurement incurs additional direct costs to payers for either a clinician or trained technician to complete. Deep learning-based image automatic segmentation tools are well positioned to address this clinical need.

Objectives

To build a deep learning model that could accurately estimate liver volumes and create 3D organ renderings from computed tomography (CT) medical images.

Methods

We trained a nnU-Net deep learning model to identify liver borders in images of the abdominal cavity. We used 151 publicly available CT scans. For each CT scan, a board-certified radiologist annotated the liver margins (ground truth annotations). We split our image dataset into training, validation, and test sets. We trained our nnU-Net model on these data to identify liver borders in 3D voxels and integrated these to reconstruct a total organ volume estimate.

Results

The nnU-Net model accurately identified the border of the liver with a mean overlap accuracy of 97.5% compared with ground truth annotations. Our calculated volume estimates achieved a mean percent error of 1.92% + 1.54% on the test set.

Conclusions

Precise volume estimation of livers from CT scans is accurate using a nnU-Net deep learning architecture. Appropriately deployed, a nnU-Net algorithm is accurate and quick, making it suitable for incorporation into the pretransplant clinical decision-making workflow.

Are body surface area based estimates of liver volume applicable to children with overweight or obesity? An in vivo validation study

The liver is the primary organ responsible for clearing most drugs from the body and thus determines systemic drug concentrations over time. Drug clearance by the liver appears to be directly related to organ size. In children, organ size changes as children age and grow. Liver volume has been correlated with body surface area (BSA) in healthy children and adults and has been estimated by functions of BSA. However, these relationships were derived from "typical" populations and it is unknown whether they extend to estimations of liver volumes for population "outliers," such as children with overweight or obesity, who today represent one-third of the pediatric population. Using computerized tomography or magnetic resonance imaging, this study measured liver volumes in 99 children (2-21 years) with normal weight, overweight, or obesity and compared organ measurements with estimates calculated using an established liver volume equation. A previously developed equation relating BSA to liver volume adequately estimates liver volumes in children, regardless of weight status.

Comparison of skeletal muscle index-based formula and body surface area-based formula for calculating standard liver volume

Backgrounds/Aims

Formula-derived standard liver volume (SLV) has been clinically used for living donor liver transplantation and hepatic resection. The majority of currently available SLV formulae are based on body surface are (BSA). However, they often show a wide range of error. Skeletal muscle index measured at the third lumbar vertebra level (L3SMI) appears to reflect lean body mass. The objective of this study was to compare the accuracy of L3SMI-based formula and BSA-based formula for calculating SLV.

Methods

The study cohort was 500 hundred living liver donors who underwent surgery between January 2010 and December 2013. Computed tomography images were used for liver volumetry and skeletal muscle area measurement.

Results

The study cohort included 250 male and 250 female donors. Their age, BSA, L3SMI, and body mass index were 26.8±8.7 years, 1.68±0.16 m², 45.6±9.0 cm²/m², and 21.7±2.5 kg/m², respectively. The BSA-based SLV formula was “SLV (ml)=−362.3+901.5×BSA (m²) (r=0.71, r²=0.50, p<0.001)”. The L3SMI-based SLV formula was “SLV (ml)=471.9+14.9×L3SMI (cm²/m²) (r=0.65, r²=0.42, p<0.001)”. Correlation coefficients were similar in subgroup analyses with 250 male donors and 250 female donors. There was a crude correlation between L3SMI and body mass index (r=0.51, r²=0.27, p<0.001).

Conclusions

The results of this study suggest that SLV calculation with L3SMI-based formula does not appear to be superior to the currently available BSA-based formulae.

[Role of the radiologist in surgery of colorectal liver metastases : What should be removed and what must remain]

BACKGROUND

The radical resection of colorectal liver metastases is the only curative option for affected patients. If properly performed, surgery provides the chance of long-term tumor-free survival.

OBJECTIVE

Summary of the critical interaction points between radiology and surgery in the planning and performance of (complex) liver resections.

RESULTS

There are many interaction points between radiology and surgery in the treatment of patients with colorectal liver metastases. Radiology supports surgery by providing detailed information of the localization of metastases, information on liver inflow and outflow as well as basic information on liver quality and function. Perioperatively, it provides interventional treatment options for postoperative complications as well as ablation of non-resectable metastases.

CONCLUSION

Complex liver resections can only be performed properly and successfully after thorough planning by an interdisciplinary board of surgeons, radiologists and associated disciplines.

Accuracy of estimated total liver volume formulas before liver resection

BACKGROUND

Future remnant liver volume is used to predict the risk for liver failure in patients who will undergo major liver resection. Formulas to estimate total liver volume based on biometric data are widely used to calculate future remnant liver volume; however, it remains unclear which formula is most accurate. This study evaluated published estimate total liver volume formulas to determine which formula best predicts the actual future remnant liver volume based on measurements in a large number of patients who underwent associating liver partition and portal vein ligation for staged hepatectomy surgery.

METHODS

All patients with complete liver volume data in the associating liver partition and portal vein ligation for staged hepatectomy registry were included in this study. Estimate total liver volume and estimated future remnant liver volume were calculated for 16 published formulas. The median over- or underestimation compared with actual measured volumes were determined for estimate total liver volume and future remnant liver volume. The proportion of patients with an under- or overestimated future remnant liver volume for each formula were compared with each other using a 25% cut-off for each formula.

RESULTS

Among 529 studied patients, the formulas ranged from a 19% underestimation to a 63% overestimation of estimate total liver volume. Estimation of future remnant liver volume lead to a 10% underestimation to a 5% overestimation among the formulas. Of all studied formulas, the Vauthey1 formula was the most accurate, generating underestimation of future remnant liver volume in 20% and overestimation of future remnant liver volume in 6% of patients.

CONCLUSION

Validation of 16 published total liver volume formulas in a multicenter international cohort of 529 patients that underwent staged hepatectomy revealed that the Vauthey formula (estimate total liver volume = 18.51 × body weight + 191.8) provides the most accurate prediction of the actual future remnant liver volume.

Estimation of Standard Liver Volume Using CT Volume, Body Composition, and Abdominal Geometry Measurements

PURPOSE

The present study developed formulas for estimation of standard liver volume (SLV) with high accuracy for the Korean population.

MATERIALS AND METHODS

SLV estimation formulas were established using gender-balanced and gender-unbalanced measurements of anthropometric variables, body composition variables, and abdominal geometry of healthy Koreans (n=790). Total liver volume excluding blood volume, was measured based on CT volumetry.

RESULTS

SLV estimation formulas as preferred in various conditions of data availability were suggested in the present study. The suggested SLV estimation formulas in the present study were found superior to existing formulas, with an increased accuracy of 4.0-217.5 mL for absolute error and 0.2-18.7% for percentage of absolute error.

CONCLUSION

SLV estimation formulas using gender-balanced measurements showed better performance than those using gender-unbalanced measurements. Inclusion of body composition and abdominal geometry variables contributed to improved performance of SLV estimation.

Assessing the Non-tumorous Liver: Implications for Patient Management and Surgical Therapy

INTRODUCTION

Hepatic resection is performed for various benign and malignant liver tumors. Over the last several decades, there have been improvements in the surgical technique and postoperative care of patients undergoing liver surgery. Despite this, liver failure following an extended hepatic resection remains a critical potential postoperative complication. Patients with underlying parenchymal liver diseases are at particular risk of liver failure due to impaired liver regeneration with an associated mortality risk as high as 60 to 90%. In addition, live donor liver transplantation requires a thorough presurgical assessment of the donor liver to minimize the risk of postoperative complications.

RESULTS AND CONCLUSION

Recently, cross-sectional imaging assessment of diffuse liver diseases has gained momentum due to its ability to provide both anatomical and functional assessments of normal and abnormal tissues. Various imaging techniques are being employed to assess diffuse liver diseases including magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound (US). MRI has the ability to detect abnormal intracellular and molecular processes and tissue architecture. CT has a high spatial resolution, while US provides real-time imaging, is inexpensive, and readily available. We herein review current state-of-the-art techniques to assess the underlying non-tumorous liver. Specifically, we summarize current approaches to evaluating diffuse liver diseases including fatty liver alcoholic or non-alcoholic (NAFLD, AFLD), hepatic fibrosis (HF), and iron deposition (ID) with a focus on advanced imaging techniques for non-invasive assessment along with their implications for patient management. In addition, the role of and techniques to assess hepatic volume in hepatic surgery are discussed.

Resection for Klatskin tumors: technical complexities and results

Klatskin's tumors, actually-redefined as perihilar cholangiocarcinoma (phCCA) do represent 50-70% of all CCAs and develop in a context of chronic inflammation and cholestasis of bile ducts. Surgical resection provides the only chance of cure for this disease but is technically challenging because of the complex, intimate and variable relationship between biliary and vascular structures at this location. Five years survival rates range between 25-45% (median 27-58 months) in case of R0 resection and 0-23% (median 12-21 months) in case of R1 resection respectively. It should be noted that the major costs of high radicality are represented by relative high morbidity and mortality rates (i.e., 20-66% and 0-9% respectively). Considering the fact that radical resection may represent the only curative treatment of phCCA, we focused our review on surgical planning and techniques that may improve resectability rates and outcomes for locally advanced phCCA. The surgical treatment of phCCA can be successful when following aspects have been fulfilled: (I) accurate preoperative diagnostic aimed to identify the tumor in all its details (localization and extension) and to study all the risk factors influencing a posthepatectomy liver failure (PHLF): i.e., liver volume, liver function, liver quality, haemodynamics and patient characteristics; (II) High end surgical skills taking in consideration the local extension of the tumor and the vascular invasion which usually require an extended hepatic resection and often a vascular resection; (III) adequate postoperative management aimed to avoid major complications (i.e., PHLF and biliary complications). These are technically challenging operations and must be performed in a high volume centres by hepato-biliary-pancreas (HBP)-surgeons with experience in microsurgical vascular techniques.

New formula for predicting standard liver volume in Chinese adults

AIM

To obtain a reference range of morphological indices and establish a formula to accurately predict standard liver volume (SLV) in Chinese adults.

METHODS

Computed tomography (CT)-estimated total liver volume (CTLV) was determined in 369 Chinese adults. Age, sex, body weight, body height, body mass index, and body surface area (BSA) were recorded using CT. Total splenic volume, portal venous diameter (PVD), splenic venous diameter (SVD), and portal venous cross-sectional area (PVCSA) were also measured by CT. Stepwise multiple linear regression analysis was performed to evaluate the impact of each parameter on CTLV and to develop a new SLV formula. The accuracy of the new formula was compared with the existing formulas in a validation group.

RESULTS

The average CTLV was 1205.41 ± 257.53 cm³ (range, 593.80-2250.10 cm³). The average of PVD, SVD and PVCSA was 9.34 ± 1.51 mm, 7.40 ± 1.31 mm and 173.22 ± 48.11 mm², respectively. The CT-estimated splenic volume of healthy adults varied markedly (range, 46.60-2892.30 cm³). Sex, age, body height, body weight, body mass index, and BSA were significantly correlated with CTLV. BSA showed the strongest correlation (r = 0.546, P < 0.001), and was used to establish a new model for calculating SLV: SLV (cm³) = 758.259 × BSA (m²)-124.272 (R² = 0.299, P < 0.001). This formula also predicted CTLV more accurately than the existing formulas, but overestimated CTLV in elderly subjects > 70 years of age, and underestimated liver volume when CTLV was > 1800 cm³.

CONCLUSION

Our new BSA-based formula is more accurate than other formulas in estimating SLV in Chinese adults.

Summary of the British Transplantation Society UK Guidelines for Living Donor Liver Transplantation

The British Transplantation Society Guidelines for Living Donor Liver Transplantation was published in July 2015 and is the first national guideline in the field of living donor liver transplantation. The guideline aims to review the evidence relating to the evaluation process of both recipient and donor candidates; address the moral and ethical issues surrounding the procedure; outline the technical aspects of the procedure, including the middle hepatic vein controversy and the "small for size syndrome"; review donor and recipient outcomes and complications including donor mortality; and examine evidence relating to the advantages and disadvantages of living donor liver transplantation. In line with previous guidelines published by the BTS, the guideline has used the Grading of Recommendations Assessment, Development and Evaluation system to rate the strength of evidence and recommendations. This article summarizes the Statements of Recommendation contained in the guideline, which provide a framework for the delivery of living liver donation in the United Kingdom and may be of wide international interest. It is recommended that the full guideline document is consulted for details of the relevant references and evidence base. This may be accessed at http://www.bts.org.uk/BTS/Guidelines_Standards/Current/BTS/Guidelines_Standards/Current_Guidelines.aspx?hkey=e285ca32-5920-4613-ac08-fa9fd90915b5.

Prediction of the Total Liver Weight using anthropological clinical parameters: does complexity result in better accuracy?

BACKGROUND

The performance of linear models predicting Total Liver Weight (TLW) remains moderate. The use of more complex models such as Artificial Neural Network (ANN) and Generalized Additive Model (GAM) or including the variable "steatosis" may improve TLW prediction. This study aimed to assess the value of ANN and GAM and the influence of steatosis for predicting TLW.

METHODS

Basic clinical and morphological variables of 1560 cadaveric donors for liver transplantation were randomly split into a training (2/3) and validation set (1/3). Linear models, ANN and GAM were built by using the training cohort and evaluated with the validation cohort.

RESULTS

The TLW is subject to major variations among donors with similar morphological parameters. The performance of ANN and GAM were moderate and similar to that of linear models (concordance coefficient from 0.36 to 0.44). In 28-30% of cases, TLW cannot be predicted with a margin of error ≤20%. The addition of the variable "steatosis" to each model did not improve their performance.

CONCLUSION

TLW prediction based on anthropological parameters carry a significant risk of error despite the use of more complex models. Others determinants of TLW need to be identified and imaging-based volumetric measurements should be preferred when feasible.

The correlation between preoperative volumetry and real graft weight: comparison of two volumetry programs

Purpose

Liver volumetry is a vital component in living donor liver transplantation to determine an adequate graft volume that meets the metabolic demands of the recipient and at the same time ensures donor safety. Most institutions use preoperative contrast-enhanced CT image-based software programs to estimate graft volume. The objective of this study was to evaluate the accuracy of 2 liver volumetry programs (Rapidia vs. Dr. Liver) in preoperative right liver graft estimation compared with real graft weight.

Methods

Data from 215 consecutive right lobe living donors between October 2013 and August 2015 were retrospectively reviewed. One hundred seven patients were enrolled in Rapidia group and 108 patients were included in the Dr. Liver group. Estimated graft volumes generated by both software programs were compared with real graft weight measured during surgery, and further classified into minimal difference (≤15%) and big difference (>15%). Correlation coefficients and degree of difference were determined. Linear regressions were calculated and results depicted as scatterplots.

Results

Minimal difference was observed in 69.4% of cases from Dr. Liver group and big difference was seen in 44.9% of cases from Rapidia group (P = 0.035). Linear regression analysis showed positive correlation in both groups (P < 0.01). However, the correlation coefficient was better for the Dr. Liver group (R² = 0.719), than for the Rapidia group (R² = 0.688).

Conclusion

Dr. Liver can accurately predict right liver graft size better and faster than Rapidia, and can facilitate preoperative planning in living donor liver transplantation.

Prediction of liver volume - a population-based approach to meta-analysis of paediatric, adult and geriatric populations - an update

Liver volume is a critical scaling factor for predicting drug clearance in physiologically based pharmacokinetic modelling and for both donor/recipient graft size estimation in liver transplantation. The accurate and precise estimation of liver volume is therefore essential. The objective here was to extend an existing meta-analysis using a non-linear mixed effects modelling approach for the estimation of liver volume to other race groups and paediatric and geriatric populations. Interrogation of the PubMed® database was undertaken using a text string query to ensure as objective a retrieval of liver volume data for the modelling exercise as possible. Missing body size parameters were estimated using simulations from the Simcyp Simulator V13R1 for an age and ethnically appropriate population. Non-linear mixed effect modelling was undertaken in Phoenix 1.3 (Certara) utilizing backward deletion and forward inclusion of covariates from fully parameterized models. Existing liver volume models based on body surface area (BSA) and body weight and height were implemented for comparison. The extension of a structural model using a BSA equation and incorporating the Japanese race and age as covariates and exponents on LV0 (θ_Baseline ) and body surface area (θ_BSA ), respectively, delivered a comparatively low objective function value. Bootstrapping of the original dataset revealed that the confidence intervals (2.5-97.5%) for the fitted (theta) parameter estimates were bounded by the bootstrapped estimates of the same. In conclusion, extension and re-parameterization of the existing Johnson model adequately describes changes in liver volume using the body surface area in all investigated populations. Copyright © 2017 John Wiley & Sons, Ltd.

Calculation of standard liver volume in Korean adults with analysis of confounding variables

Backgrounds/Aims

Standard liver volume (SLV) is an important parameter that has been used as a reference value to estimate the graft matching in living donor liver transplantation (LDLT). This study aimed to determine a reliable SLV formula for Korean adult patients as compared with the 15 SLV formulae from other studies and further estimate SLV formula by gender and body mass index (BMI).

Methods

Computed tomography liver volumetry was performed in 1,000 living donors for LDLT and regression formulae for SLV was calculated. Individual donor data were applied to the 15 previously published SLV formulae, as compared with the SLV formula derived in this study. Analysis for confounding variables of BMI and gender was also performed.

Results

Two formulae, "SLV (ml)=908.204×BSA-464.728" with DuBois body surface area (BSA) formula and "SLV (ml)=893.485×BSA-439.169" with Monsteller BSA formula, were derived by using the profiles of the 1,000 living donors included in the study. Comparison with other 15 other formulae, all except for Chouker formula showed the mean volume percentage errors of 4.8-5.4%. The gender showed no significant effect on total liver volume (TLV), but there was a significant increase in TLV as BMI increased.

Conclusions

Our study suggested that most SLV formulae showed a crudely applicable range of SLV estimation for Korean adults. Considering the volume error in estimating SLV, further SLV studies with larger population from multiple centers should be performed to enhance its predictability. Our results suggested that classifying SLV formulae by BMI and gender is unnecessary.

A new formula for calculating standard liver volume for living donor liver transplantation without using body weight

BACKGROUND & AIMS

The standard liver volume (SLV) is widely used in liver surgery, especially for living donor liver transplantation (LDLT). All the reported formulas for SLV use body surface area or body weight, which can be influenced strongly by the general condition of the patient.

METHODS

We analyzed the liver volumes of 180 Japanese donor candidates and 160 Swiss patients with normal livers to develop a new formula. The dataset was randomly divided into two subsets, the test and validation sample, stratified by race. The new formula was validated using 50 LDLT recipients.

RESULTS

Without using body weight-related variables, age, thoracic width measured using computed tomography, and race independently predicted the total liver volume (TLV). A new formula: 203.3-(3.61×age)+(58.7×thoracic width)-(463.7×race [1=Asian, 0=Caucasian]), most accurately predicted the TLV in the validation dataset as compared with any other formulas. The graft volume for LDLT was correlated with the postoperative prothrombin time, and the graft volume/SLV ratio calculated using the new formula was significantly better correlated with the postoperative prothrombin time than the graft volume/SLV ratio calculated using the other formulas or the graft volume/body weight ratio.

CONCLUSIONS

The new formula derived using the age, thoracic width and race predicted both the TLV in the healthy patient group and the SLV in LDLT recipients more accurately than any other previously reported formulas.

Quantified Risk Assessment for Major Hepatectomy via the Indocyanine Green Clearance Rate and Liver Volumetry Combined with Standard Liver Volume

BACKGROUND

Preoperative risk assessment for post-hepatectomy liver failure (PHLF) is essential for major hepatectomy. We intended to establish a standard liver volume (SLV) formula for Korean patients and validate the predictive power of the indocyanine green clearance rate constant (ICG-K) fraction of future remnant liver (FRL) (FRL-kICG) to total liver volume (TLV).

METHODS

This study comprised 2 retrospective studies. Part I established SLV formula and acquired ICG pharmacokinetic data from 2155 living donors. In part II, FRL-kICG cutoff was determined using 723 patients who underwent right liver resection for hepatocellular carcinoma.

RESULTS

In part I, the formula SLV (mL) = -456.3 + 969.8 × BSA (m(2)) (r = 0.707, r (2) = 0.500, p = 0.000) was derived with mean volume error of 10.5%. There was no correlation between TLV and ICG retention rate at 15 min. With a cutoff of 0.04 with hepatic parenchymal resection rate (PHRR) limit of 70%, 99.0% of our living donors were permissible for left or right hepatectomy. In part II, 25 hepatocellular carcinoma patients (3.5%) showed an FRL-kICG or SLV-corrected FRL-kICG <0.05. Of these, 4 (16 %) died of PHLF, whereas only 2 (0.3%) died in the other patient group with both an FRL-kICG and SLV-corrected FRL-kICG ≥ 0.05 (P = 0.000).

CONCLUSIONS

The FRL-kICG appears to reliably predict PHLF risk quantitatively. We suggest FRL-kICG cutoffs of 0.04 and 0.05 with PHRR limits of 70% and 65% for normal and diseased livers, respectively. Further validation with large patient population in multicenter studies is necessary to improve FRL-kICG predictability.

Impact of non-alcoholic fatty liver disease on liver volume in humans

AIM

Knowledge of liver volume is needed in the preoperative screening of liver transplant donors and in pharmacokinetic studies. In previous studies, bodyweight, surface area, age and sex have been identified as predictors of total liver volume, but the impact of non-alcoholic fatty liver disease (NAFLD) independent of body size on liver volume has not been determined. We examined whether and to what extent liver fat due to NAFLD influences liver volume.

METHODS

We quantified the percentage of liver fat by proton magnetic resonance spectroscopy ((1) H-MRS) and liver total, lean and fat volumes using magnetic resonance imaging (MRI) in 112 subjects (62 women, 50 men), who were characterized with respect to metabolic parameters associated with NAFLD.

RESULTS

Of the subjects, 45% had NAFLD (liver fat 12.5 ± 4.5% vs 1.8 ± 1.6%, NAFLD vs no NAFLD, P < 0.001). Total liver volume was 29% higher in subjects with NAFLD (1.91 ± 0.45 L) than in those with no NAFLD (1.49 ± 0.31 L, P < 0.001). In multiple linear regression analysis, the percentage of liver fat and bodyweight independently explained variation in total liver volume (r(2)  = 0.42, P < 0.001). The r-values for the relationship between metabolic parameters and the total liver fat volume were not significantly better than those between metabolic parameters and the percentage of liver fat.

CONCLUSION

Both bodyweight and NAFLD increase liver volume independent of each other. Measurement of liver fat by (1) H-MRS allows accurate quantification of NAFLD and calculation of total liver volume.

Liver regeneration after living donor transplantation: adult-to-adult living donor liver transplantation cohort study

Adult-to-adult living donors and recipients were studied to characterize patterns of liver growth and identify associated factors in a multicenter study. Three hundred and fifty donors and 353 recipients in the Adult-to-Adult Living Donor Liver Transplantation Cohort Study (A2ALL) receiving transplants between March 2003 and February 2010 were included. Potential predictors of 3-month liver volume included total and standard liver volumes (TLV and SLV), Model for End-Stage Liver Disease (MELD) score (in recipients), the remnant and graft size, remnant-to-donor and graft-to-recipient weight ratios (RDWR and GRWR), remnant/TLV, and graft/SLV. Among donors, 3-month absolute growth was 676 ± 251 g (mean ± SD), and percentage reconstitution was 80% ± 13%. Among recipients, GRWR was 1.3% ± 0.4% (8 < 0.8%). Graft weight was 60% ± 13% of SLV. Three-month absolute growth was 549 ± 267 g, and percentage reconstitution was 93% ± 18%. Predictors of greater 3-month liver volume included larger patient size (donors and recipients), larger graft volume (recipients), and larger TLV (donors). Donors with the smallest remnant/TLV ratios had larger than expected growth but also had higher postoperative bilirubin and international normalized ratio at 7 and 30 days. In a combined donor-recipient analysis, donors had smaller 3-month liver volumes than recipients adjusted for patient size, remnant or graft volume, and TLV or SLV (P = 0.004). Recipient graft failure in the first 90 days was predicted by poor graft function at day 7 (HR = 4.50, P = 0.001) but not by GRWR or graft fraction (P > 0.90 for each). Both donors and recipients had rapid yet incomplete restoration of tissue mass in the first 3 months, and this confirmed previous reports. Recipients achieved a greater percentage of expected total volume. Patient size and recipient graft volume significantly influenced 3-month volumes. Importantly, donor liver volume is a critical predictor of the rate of regeneration, and donor remnant fraction affects postresection function. Liver Transpl 21:79-88, 2015. © 2014 AASLD.

Evaluation of computer-assisted quantitative volumetric analysis for pre-operative resectability assessment of huge hepatocellular carcinoma

PURPOSE

Hepatic resection is arguably the preferred treatment for huge hepatocellular carcinoma (H-HCC). Estimating the remnant liver volume is therefore essential. This study aimed to evaluate the feasibility of using computer-assisted volumetric analysis for this purpose.

METHODS

The study involved 40 patients with H-HCC. Laboratory examinations were conducted, and a contrast CT-scan revealed that 30 cases out of the participating 40 had single-lesion tumors. The remaining 10 had less than three satellite tumors. With the consensus of the team, two physicians conducted computer-assisted 3D segmentation of the liver, tumor, and vessels in each case. Volume was automatically computed from each segmented/labeled anatomical field. To estimate the resection volume, virtual lobectomy was applied to the main tumor. A margin greater than 1 cm was applied to the satellite tumors. Resectability was predicted by computing a ratio of functional liver resection (R) as (Vresected- Vtumor)/(Vtotal-Vtumor) x 100%, applying a threshold of 50% and 60% for cirrhotic and non-cirrhotic cases, respectively. This estimation was then compared with surgical findings.

RESULTS

Out of the 22 patients who had undergone hepatectomies, only one had an R that exceeded the threshold. Among the remaining 18 patients with non-resectable H-HCC, 12 had Rs that exceeded the specified ratio and the remaining 6 had Rs that were < 50%. Four of the patients who had Rs less than 50% underwent incomplete surgery due to operative findings of more extensive satellite tumors, vascular invasion, or metastasis. The other two cases did not undergo surgery because of the high risk involved in removing the tumor. Overall, the ratio of functional liver resection for estimating resectability correlated well with the other surgical findings.

CONCLUSION

Efficient pre-operative resectability assessment of H-HCC using computer-assisted volumetric analysis is feasible.

A formula to calculate the standard liver volume in children and its application in pediatric liver transplantation

Due to a lack of available size-matched liver grafts from children, most pediatric recipients are transplanted with technical variant grafts from adult donors. Size requirements for these grafts are not well defined, and consequences of mismatched graft sizes in pediatric liver transplantation are not known. Existing formulas for calculation of a standard liver volume are mostly derived from adults disregarding the age-related percentual liver weight changes in children. In this study, we aimed to establish a formula for general use in children to calculate the standard liver volume. In a second step, the formula was applied in pediatric patients undergoing liver transplantation at our institution between 2000 and 2010 (n = 377). Analysis of a large number (n = 388) of autopsy data from children by regression analysis revealed a best fit for two formulas: "Formula 1," children 0 to ≤1 year (n = 246): standard liver volume [ml] = -143.062973 +4.274603051 * body length [cm] + 14.78817631 * body weight [kg]; "Formula 2," children >1 to <16 years (n = 142): standard liver volume [ml] = -20.2472281 + 3.339056437 * body length [cm] + 13.11312561 * body weight [kg]. In comparison with children receiving size-matched organs, we found an elevated risk of liver graft failure in children transplanted with a small-for-size graft, whereas large-for-size organs seem to have no negative impact.