Preoperative volume prediction in adult living donor liver transplantation: how much can we rely on it?

Global practice patterns of preoperative image reconstruction for liver surgery

BACKGROUND

Three-dimensional (3-D) liver modeling is used globally; however, its actual practice is limited to a few centers. This study aimed to assess practice patterns and barriers to the use of 3-D modeling among liver surgeons worldwide.

METHODS

A survey approved by the International Hepato-Pancreato-Biliary Association research council consisting of 27 questions was conducted using an online questionnaire. Incomplete responses were excluded.

RESULTS

Of 235 respondents from 46 countries, 81.3% reported experience with 3-D modeling; however, only 21% used it in > 75% of cases. Surgeons using 3-D reconstruction were older (P = .025), worked more frequently at academic facilities (P = .007), and had more years of experience (P = .001), especially in minimally invasive liver surgery (MILS) (P = .038). In addition, 3-D rendering was performed by surgeons in 50.8% of cases. Liver volumetry was the most frequent indication (80.1%), and decreased postoperative complications were the main perceived benefit (53.6%).

CONCLUSIONS

More experience in liver surgery because of seniority, case volume, and openness to novel technology (MILS) is associated with a greater appreciation for the value of 3-D modeling. Our results suggest the need for senior surgeons to help early-career surgeons consider 3-D modeling for the reported benefit of reduced intra- and postoperative complications.

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.

Development of a model to predict the risk of early graft failure after adult-to-adult living donor liver transplantation: An ELTR study

Graft survival is a critical end point in adult-to-adult living donor liver transplantation (ALDLT), where graft procurement endangers the lives of healthy individuals. Therefore, ALDLT must be responsibly performed in the perspective of a positive harm-to-benefit ratio. This study aimed to develop a risk prediction model for early (3 months) graft failure (EGF) following ALDLT. Donor and recipient factors associated with EGF in ALDLT were studied using data from the European Liver Transplant Registry. An artificial neural network classification algorithm was trained on a set of 2073 ALDLTs, validated using cross-validation, tested on an independent random-split sample (n=518), and externally validated on United Network for Organ Sharing Standard Transplant Analysis and Research data. Model performance was assessed using the AUC, calibration plots, and decision curve analysis. Graft type, graft weight, level of hospitalization, and the severity of liver disease were associated with EGF. The model ( http://ldlt.shinyapps.io/eltr_app ) presented AUC values at cross-validation, in the independent test set, and at external validation of 0.69, 0.70, and 0.68, respectively. Model calibration was fair. The decision curve analysis indicated a positive net benefit of the model, with an estimated net reduction of 5-15 EGF per 100 ALDLTs. Estimated risks>40% and<5% had a specificity of 0.96 and sensitivity of 0.99 in predicting and excluding EGF, respectively. The model also stratified long-term graft survival ( p <0.001), which ranged from 87% in the low-risk group to 60% in the high-risk group. In conclusion, based on a panel of donor and recipient variables, an artificial neural network can contribute to decision-making in ALDLT by predicting EGF risk.

Estimation of right lobe graft weight for living donor liver transplantation using deep learning-based fully automatic computed tomographic volumetry

This study aimed at developing a fully automatic technique for right lobe graft weight estimation using deep learning algorithms. The proposed method consists of segmentation of the full liver region from computed tomography (CT) images, classification of the entire liver region into the right and left lobes, and estimation of the right lobe graft weight from the CT-measured right lobe graft volume using a volume-to-weight conversion formula. The first two steps were performed with a transformer-based deep learning model. To train and evaluate the model, a total of 248 CT datasets (188 for training, 40 for validation, and 20 for testing and clinical evaluation) were used. The Dice similarity coefficient (DSC), mean surface distance (MSD), and the 95th percentile Hausdorff distance (HD95) were used for evaluating the segmentation accuracy of the full liver region and the right liver lobe. The correlation coefficient (CC), percentage error (PE), and percentage absolute error (PAE) were used for the clinical evaluation of the estimated right lobe graft weight. The proposed method achieved high accuracy in segmentation for DSC, MSD, and HD95 (95.9% ± 1.0%, 1.2 ± 0.4 mm, and 5.2 ± 1.9 mm for the entire liver region; 92.4% ± 2.7%, 2.0 ± 0.7 mm, and 8.8 ± 2.9 mm for the right lobe) and in clinical evaluation for CC, PE, and PAE (0.859, - 1.8% ± 9.6%, and 8.6% ± 4.7%). For the right lobe graft weight estimation, the present study underestimated the graft weight by - 1.8% on average. A mean difference of - 21.3 g (95% confidence interval: - 55.7 to 13.1, p = 0.211) between the estimated graft weight and the actual graft weight was achieved in this study. The proposed method is effective for clinical application.

Machine learning improves the accuracy of graft weight prediction in living donor liver transplantation

Precise graft weight (GW) estimation is essential for planning living donor liver transplantation to select grafts of adequate size for the recipient. This study aimed to investigate whether a machine-learning model can improve the accuracy of GW estimation. Data from 872 consecutive living donors of a left lateral sector, left lobe, or right lobe to adults or children for living-related liver transplantation were collected from January 2011 to December 2019. Supervised machine-learning models were trained (80% of observations) to predict GW using the following information: donor's age, sex, height, weight, and body mass index; graft type (left, right, or left lateral lobe); computed tomography estimated graft volume and total liver volume. Model performance was measured in a random independent set (20% of observations) and in an external validation cohort using the mean absolute error (MAE) and the mean absolute percentage error and compared with methods currently available for GW estimation. The best-performing machine-learning model showed an MAE value of 50 ± 62 g in predicting GW, with a mean error of 10.3%. These errors were significantly lower than those observed with alternative methods. In addition, 62% of predictions had errors <10%, whereas errors >15% were observed in only 18.4% of the cases compared with the 34.6% of the predictions obtained with the best alternative method ( p  < 0.001). The machine-learning model is made available as a web application ( http://graftweight.shinyapps.io/prediction ). Machine learning can improve the precision of GW estimation compared with currently available methods by reducing the frequency of significant errors. The coupling of anthropometric variables to the preoperatively estimated graft volume seems necessary to improve the accuracy of GW estimation.

Volumetric assessment of hepatic grafts using a light detection and ranging system for 3D scanning: Preliminary data

BACKGROUND

Liver transplantation has evolved into a safe life-saving operation and remains the golden standard in the treatment of end stage liver disease. The main limiting factor in the application of liver transplantation is graft shortage. Many strategies have been developed in order to alleviate graft shortage, such as living donor partial liver transplantation and split liver transplantation for adult and pediatric patients. In these strategies, liver volume assessment is of paramount importance, as size mismatch can have severe consequences in the success of liver transplantation.

AIM

To evaluate the safety, feasibility, and accuracy of light detection and ranging (LIDAR) 3D photography in the prediction of whole liver graft volume and mass.

METHODS

Seven liver grafts procured for orthotopic liver transplantation from brain deceased donors were prospectively measured with an LIDAR handheld camera and their mass was calculated and compared to their actual weight.

RESULTS

The mean error of all measurements was 17.03 g (range 3.56-59.33 g). Statistical analysis of the data yielded a Pearson correlation coefficient index of 0.9968, indicating a strong correlation between the values and a Student’s t-test P value of 0.26. Mean accuracy of the measurements was calculated at 97.88%.

CONCLUSION

Our preliminary data indicate that LIDAR scanning of liver grafts is a safe, cost-effective, and feasible method of ex vivo determination of whole liver volume and mass. More data are needed to determine the precision and accuracy of this method.

Accuracy and Efficiency of Right-Lobe Graft Weight Estimation Using Deep-Learning-Assisted CT Volumetry for Living-Donor Liver Transplantation

CT volumetry (CTV) has been widely used for pre-operative graft weight (GW) estimation in living-donor liver transplantation (LDLT), and the use of a deep-learning algorithm (DLA) may further improve its efficiency. However, its accuracy has not been well determined. To evaluate the efficiency and accuracy of DLA-assisted CTV in GW estimation, we performed a retrospective study including 581 consecutive LDLT donors who donated a right-lobe graft. Right-lobe graft volume (GV) was measured on CT using the software implemented with the DLA for automated liver segmentation. In the development group (n = 207), a volume-to-weight conversion formula was constructed by linear regression analysis between the CTV-measured GV and the intraoperative GW. In the validation group (n = 374), the agreement between the estimated and measured GWs was assessed using the Bland–Altman 95% limit-of-agreement (LOA). The mean process time for GV measurement was 1.8 ± 0.6 min (range, 1.3–8.0 min). In the validation group, the GW was estimated using the volume-to-weight conversion formula (estimated GW [g] = 206.3 + 0.653 × CTV-measured GV [mL]), and the Bland–Altman 95% LOA between the estimated and measured GWs was −1.7% ± 17.1%. The DLA-assisted CT volumetry allows for time-efficient and accurate estimation of GW in LDLT.

Intra- inter-observer repeatability in liver computed tomography volumetry in patients undergoing radioembolization simulation

PURPOSE

The careful evaluation of MDCT is an essential step for the treatment planning in pre-treatment imaging work-up for Trans-Arterial Radio Embolization (TARE). It may provide unique volumetric data (CTVs), which are information useful for an effective and safe TARE. The purpose of this study is to demonstrate that the radiographer is able to calculate CTVs of TARE simulation with the same precision as the interventional radiologist.

METHODS

This study retrospectively considers 17 consecutive patients (8 males, 9 females; mean age 66.3 ± 13.2 years) who underwent pre-treatment work-up for TARE, between May 2019 and February 2020 (trial ID:2234 - protocol). For each patient, four specific parameters are evaluated from MDCT achieved during treatment simulation: healthy liver volume (HLV), the whole hepatic parenchyma (THV = healthy liver and TTV = tumour) involved by TARE, and whole liver volume (WLV). Four independent observers-R1 (expert interventional radiologist), T1, T2, and T3 (radiographers, with different experiences in the field of interventional radiology)-are involved in the imaging analysed.

RESULTS

All the 4 observers detected the same number of hepatic lesion(s) per patient. Regarding the three radiographers, the intra-observer reliability for CTVs is very high 0.997 to 1.000 (95%CI). Also inter-observer reproducibility between radiographers is excellent regarding CTVs, 0.965 to 0.999 (95%CI). The accuracy of radiographer evaluation is very high 0.964 to 0.999 (95%CI).

CONCLUSIONS AND IMPLICATIONS FOR PRACTICE

The high intra- and inter-observer reproducibility shows that a properly trained radiographers might have the same accuracy as interventional radiologists, in assessing liver CTV data for planning TARE.

Impact of Graft Weight Change During Perfusion on Hepatocellular Carcinoma Recurrence After Living Donor Liver Transplantation

BACKGROUNDS

Inadequate liver volume and weight is a major source of morbidity and mortality after adult living donor liver transplantation (LDLT). The purpose of our study was to investigate HCC recurrence, graft failure, and patient survival according to change in right liver graft weight after histidine-tryptophan-ketoglutarate (HTK) solution perfusion in LDLT.

METHODS

Two hundred twenty-eight patients underwent LDLT between 2013 and 2017. We calculated the change in graft weight by subtracting pre-perfusion graft weight from post-perfusion graft weight. Patients with increased graft weight were defined as the positive group, and patients with decreased graft weight were defined as the negative group.

RESULTS

After excluding patients who did not meet study criteria, 148 patients underwent right or extended right hepatectomy. The negative group included 89 patients (60.1%), and the positive group included 59 patients (39.9%). Median graft weight change was -28 g (range; -132-0 g) in the negative group and 21 g (range; 1-63 g) in the positive group (P<0.001). Median hospitalization time was longer for the positive group than the negative group (27 days vs. 23 days; P=0.048). There were no statistical differences in tumor characteristics, postoperative complications, early allograft dysfunction, or acute rejection between the two groups. Disease-free survival, death-censored graft survival, and patient survival were lower in the positive group than the negative group. Additionally, the positive group showed strong association with HCC recurrence, death-censored graft survival, and patient survival in multivariate analysis.

CONCLUSION

This study suggests that positive graft weight change during HTK solution perfusion indicates poor prognosis in LDLT.

Effects of laparoscopy, laparotomy, and respiratory phase on liver volume in a live porcine model for liver resection

Background

Hepatectomy, living donor liver transplantations and other major hepatic interventions rely on precise calculation of the total, remnant and graft liver volume. However, liver volume might differ between the pre- and intraoperative situation. To model liver volume changes and develop and validate such pre- and intraoperative assistance systems, exact information about the influence of lung ventilation and intraoperative surgical state on liver volume is essential.

Methods

This study assessed the effects of respiratory phase, pneumoperitoneum for laparoscopy, and laparotomy on liver volume in a live porcine model. Nine CT scans were conducted per pig (N = 10), each for all possible combinations of the three operative (native, pneumoperitoneum and laparotomy) and respiratory states (expiration, middle inspiration and deep inspiration). Manual segmentations of the liver were generated and converted to a mesh model, and the corresponding liver volumes were calculated.

Results

With pneumoperitoneum the liver volume decreased on average by 13.2% (112.7 ml ± 63.8 ml, p < 0.0001) and after laparotomy by 7.3% (62.0 ml ± 65.7 ml, p = 0.0001) compared to native state. From expiration to middle inspiration the liver volume increased on average by 4.1% (31.1 ml ± 55.8 ml, p = 0.166) and from expiration to deep inspiration by 7.2% (54.7 ml ± 51.8 ml, p = 0.007).

Conclusions

Considerable changes in liver volume change were caused by pneumoperitoneum, laparotomy and respiration. These findings provide knowledge for the refinement of available preoperative simulation and operation planning and help to adjust preoperative imaging parameters to best suit the intraoperative situation.

Evaluation of Liver Function and the Role of Biliary Drainage before Major Hepatic Resections

Background

Prevention of posthepatectomy liver failure is a prerequisite for improving the postoperative outcome of perihilar cholangiocarcinoma. From this perspective, appropriate assessment of future liver remnant (FLR) function and the optimized preparation are mandatory.

Summary

FLR volume ratio using CT volumetry based on 3-dimensional vascular imaging is the current assessment yardstick and is sufficient for assessing a normal liver. However, in a liver with underling parenchymal disease such as fibrosis or prolonged jaundice, weighing up the degree of liver damage against the FLR volume ratio is necessary to know the real FLR function. For this purpose, the indocyanine green (ICG) clearance test, monoethylglycinexylidide (MEGX) test, liver maximum capacity (LiMAX) test, ^99mTc-labeled galactosyl human serum albumin (^99mTc-GSA) scintigraphy, albumin-bilirubin (ALBI) grade, and ALPlat (albumin × platelets) criterion are used. After the optimization of FLR function by means of portal vein embolization or associating liver partition and PVL (portal vein ligation) for staged hepatectomy (ALPPS), SPECT scintigraphy with either ^99mTc-GSA or ^99mTc-mebrofenin compensates for misestimation due to the regional heterogeneity of liver function. The role of preoperative biliary drainage has long been debated, with the associated complications having led to a lack of approval. However, the recent establishment of safety and an improvement in success rates of endoscopic biliary drainage seem to be changing the awareness of the importance of biliary drainage.

Key Messages

Appropriate selection of an assessment method is of prime importance to predict the FLR function according to the preoperative condition of the liver. Preoperative biliary drainage in patients with perihilar cholangiocarcinoma is gaining support due to the increasing safety and success rate, especially in patients who need optimization of their liver function before hepatectomy.

Small-for-size graft, small-for-size syndrome and inflow modulation in living donor liver transplantation

The extended application of living donor liver transplantation (LDLT) has revealed the problem of graft size mismatching called "small-for-size syndrome (SFSS)." The initial trials to resolve this problem involved increasing the procured graft size, from left to right, and even extending to include a right lobe graft. Clinical cases of living right lobe donations have been reported since then, drawing attention to the risks of increasing the liver volume procured from a living donor. However, not only other modes of increasing graft volume (GV) such as auxiliary or dual liver transplantation, but also control of the increased portal pressure caused by a small-for-size graft (SFSG), such as a porto-systemic shunt or splenectomy and optimal outflow reconstruction, have been trialed with some positive results. To establish an effective strategy for transplanting SFSG and preventing SFSS, it is essential to have precise knowledge and tactics to evaluate graft quality and GV, when performing these LDLTs with portal pressure control and good venous outflow. Thus, we reviewed the updated literature on the pathogenesis of and strategies for using SFSG.

Reproducibility and reliability of computed tomography volumetry in estimation of the right-lobe graft weight in adult-to-adult living donor liver transplantation: Cantlie's line vs portal vein territorialization

BACKGROUND/PURPOSE

In living-donor liver transplantation (LDLT), liver volume assessment is a mandatory step in determining donor appropriateness. This study aimed to compare reliability and reproducibility between two major methods to define virtual hepatectomy plane, based on Cantlie's line (CTV-Cantlie) and portal vein territorialization (CTV-PVT) for right-lobe graft weight estimation in LDLT.

METHODS

A total of 188 donors who underwent preoperative CT scans were included. The liver was divided into right and left lobes using CTV-Cantlie and CTV-PTV measurements by two readers. Intraclass correlation coefficient (ICC) was used to determine interreader variability of hepatic weight measured using each CTV method. Intraoperative graft weight (IOW) was used as reference standard of right-lobe graft weight. Pearson correlation test was performed to determine correlation coefficients between presumed graft weight by each CTV method and IOW.

RESULTS

Intraclass correlation coefficients for total liver weight were roughly equivalent between the two CTV methods (CTV-Cantlie: 0.965 [95% CI, 0.954-0.974], CTV-PVT: 0.977 [0.970-0.983]). However, ICCs of right-and left-lobe weights between two readers were higher with CTV-PVT (0.997 and 0.850) than with CTV-Cantlie (0.829 and 0.668). The IOW was 716.0 ± 162.0 g. Correlation coefficients between presumed graft weight by CTV-Cantlie or CTV-PVT and IOW were 0.722 and 0.807, respectively (both P < .001).

CONCLUSIONS

For estimation of the right-lobe graft weight in LDLT, CTV-PVT may provide higher reliability and reproducibility than CTV-Cantlie.

Estimation of the Right Posterior Section Volume in Live Liver Donors: Semiautomated CT Volumetry Using Portal Vein Segmentation

RATIONALE AND OBJECTIVES

To determine the accuracy of semiautomated CT volumetry using portal vein (PV) segmentation to estimate volume of the right posterior section (RPS) graft compared to intraoperative measured weight (W) in live liver donors.

MATERIALS AND METHODS

Among 23 donors who donated RPS grafts for liver transplantation in our institution from April 2003 to August 2016, 17 donors with CT scans within 3 months of liver procurement and PV anatomy of type I-III were included. RPS volumes were retrospectively evaluated by semiautomated CT volumetry (RPSV_CTV) and by measurement of standard liver volume (SLV) and PV area ratio (RPSV_SLV). RPS volumes were compared to W for correlation coefficients, (absolute) difference, and (absolute) percentage deviation. Linear fitting was performed to identify the method that yielded the greatest correlation with W.

RESULTS

Mean values of RPSV_CTV, RPSV_SLV, and W were 503.4 ± 97.8 mL (346.6-686.0), 516.54 ± 146.20 (274.06-776.32), and 518.8 ± 122.4 (370.0-789.0), respectively. RPSV_CTV was strongly correlated with W (r = 0.9414; p < 0.0001), whereas RPSV_SLV was only moderately did (r = 0.5899; p = 0.0127). RPSV_CTV showed a significantly smaller absolute difference (35.20 ± 30.82 vs. 104.79 ± 60.27, p = 0.004) and absolute percentage deviation (6.61 ± 4.90 vs. 19.92 ± 10.37, p < 0.0001) from W. Equation correlating RPSV_CTV and W was W = -74.7191 + 1.1791 RPSV_CTV (R² = 0.8862; p < 0.001).

CONCLUSION

RPSV_CTV yields smaller absolute difference than RPSV_SLV for estimating intraoperative measured weight of RPS in live liver donors. Semiautomated CT volumetry using PV segmentation is feasible for the estimation of the volume of the RPS of the liver, and RPSV_CTV was strongly correlated with W (r = 0.9414; p < 0.0001).

Conceptual changes in small-for-size graft and small-for-size syndrome in living donor liver transplantation

Early series in living donor liver transplantation (LDLT) in adults demonstrated a lower safe limit of graft volume standard liver volume ratio 25%–45%. A subsequent worldwide large LDLT series proposed a 0.8 graft recipient weight ratio (GRWR) to define small-for-size graft (SFSG) in adult LDLT. Thereafter, researchers identified innate and inevitable factors including changes in liver volume during imaging studies and graft shrinkage due to perfusion solution. Although the definition of small-for-size syndrome (SFSS) advocated in the 2000s was mainly based on prolonged cholestasis and ascites output, the term SFSS was inadequate to describe clinical manifestations possibly caused by multiple factors. Thus, the term “early allograft dysfunction (EAD),” characterized by total bilirubin >10 mg/dL or coagulopathy with international normalized ratio >1.6 on day 7, has become prevalent to describe graft dysfunction including SFSS after LDLT. Although various efforts have been made to overcome EAD in LDLT, graft selection to maintain an expected GRWR >0.8 and full venous drainage, as well as inflow modulation using splenic artery ligation, have become standard in recent LDLT.

Remnant Liver-to-Standard Liver Volume Ratio Below 40% is Safe in Ex Vivo Liver Resection and Autotransplantation

BACKGROUND

The successful application of ex vivo liver resection and autotransplantation (ERAT) has gained widespread attention for the treatment of end-stage hepatic alveolar echinococcosis, which is considered to be unresectable by conventional methods due to extensive invasion of the extra- and intrahepatic vasculature. However, data on remnant liver volume (RLV) are limited, and the safe volume limit of remnant liver is still unclear.

METHODS

To determine the effect of liver volume in the technically developed era, we investigated the impact of the remnant liver-to-standard liver volume ratio (RLV/SLV) on the outcomes of ERAT.

RESULTS

From February 2014 to May 2018, 56 ERAT procedures were performed. Eleven patients with an RLV/SLV < 40% (group S) were compared with 45 patients with an RLV/SLV ≥ 40% (group L). Serial changes in postoperative serum total bilirubin, alanine aminotransferase, aspartate aminotransferase, and international normalized ratio were comparable in both groups. The incidences of postoperative complications did not significantly differ between the two groups. Three patients died of intra-abdominal bleeding, acute cerebral hemorrhage, and severe liver dysfunction. In RLV estimation analysis, the actual RLV and RLV/SLV were significantly smaller than the expected RLV and RLV/SLV as determined by preoperative three-dimensional reconstruction software in patients with hepatic venous outflow obstruction.

CONCLUSION

Patients with a smaller RLV/SLV did not have outcomes inferior to those with a larger RLV/SLV. Further studies are warranted to clarify the factors that contribute to preoperative volumetric estimation and the safe lower limits for ERAT.

[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.

Semi-automated computed tomography Volumetry can predict hemihepatectomy specimens' volumes in patients with hepatic malignancy

Background

One of the major causes of perioperative mortality of patients undergoing major hepatic resections is post-hepatectomy liver failure (PHLF). For preoperative appraisal of the risk of PHLF it is important to accurately predict resectate volume and future liver remnant volume (FLRV). The objective of our study is to prospectively evaluate the accuracy of hemihepatectomy resectate volumes that are determined by computed tomography volumetry (CTV) when compared with intraoperatively measured volumes and weights as gold standard in patients undergoing hemihepatectomy.

Methods

Twenty four patients (13 women, 11 men) scheduled for hemihepatectomy due to histologically proven primary or secondary hepatic malignancies were included in our study. CTV was performed using a semi-automated module (S, hereinafter) (syngo.CT Liver Analysis VA30, Siemens Healthcare, Germany). Conversion factors between CT volumes on the one side and intraoperative volumes and weights on the other side were calculated using the method of least squares. Absolute and relative disagreements between CT volumes and intraoperative volumes were determined.

Results

A conversion factor of c = 0.906 most precisely predicted intraoperative volumes of exsanguinated hemihepatectomy specimens from CT volumes in all patients with mean absolute and relative disagreements between CT volumes and intraoperative volumes of 57 ml and 6.3%. The use of operation-specific conversion factors yielded even better results.

Conclusions

CTV performed with S accurately predicts intraoperative volumes of hemihepatectomy specimens when applying conversion factors which compensate for exsanguination. This allows to precisely estimate the FLRV and thus minimize the risk of PHLF in patients undergoing major hepatic resections.

Use of Computed Tomography Volumetry to Assess Liver Weight in Patients With Cirrhosis During Evaluation Before Living-Donor Liver Transplant

OBJECTIVES

Computed tomography liver volumetry has been widely used to detect total and segmental liver volume in living-donor liver transplantation. However, use of this technique to evaluate the cirrhotic liver remains unclear. In this study, we evaluated the accuracy of freehand computed tomography volumetry to assess total liver volume by comparing weights of total hepatectomy specimens in patients with cirrhosis. For our analyses, we considered the density of a cirrhotic liver to be 1.1 kg/L.

MATERIALS AND METHODS

Liver volume was measured using a freehand computed tomography technique in 52 patients with cirrhosis from different causes and who had no solid lesions before transplant. Measurements were made with a 16-slice multidetector computed tomography scanner (Siemens Somatom Sensation 16, Erlangen, Germany). For volumetric measurements, 10-mm-thick slices with 10-mm reconstruction intervals were preferred. Total hepatectomy weights of explant livers and computed tomography volumetry data were compared.

RESULTS

We excluded 3 cirrhotic patients with Budd-Chiari syndrome due to wide variations in scatterplot results. In the 49 patients included in the final analyses, average estimated liver volume by computed tomography was 721 ± 398 mL and actual cirrhotic liver weight was 727.8 ± 415 g. No significant differences were shown between these measurements. A simple regression analysis used to analyze correlations between estimated liver volume by computed tomography and real cirrhotic liver weight showed correlation of 0.957 (P < .001). When computed tomography liver volumetry as the independent variable and cirrhotic liver weight as dependent variable were considered, regression analyses showed R2 = 0.915.

CONCLUSIONS

Freehand computed tomography liver volumetry can be confidently used to evaluate liver volume in cirrhotic liver patients similar to use of this technique to estimate actual weights in normal livers. This technique can also be valuable during pretransplant and liver resection evaluations to ensure a more successful outcome.

Computed tomography donor liver volumetry before liver transplantation in infants ≤10 kg: does the estimated graft diameter affect the outcome?

Aim of the study

Living donor liver transplantation (LDLT) is regularly performed in small-sized infants. Computed tomography (CT)-based donor liver volumetry is used to estimate the graft size. The aim of our study was to assess the results of CT liver volumetry and their impact on the clinical outcome after LDLT in extremely small-sized infants.

Patients and methods

In this study, we included all patients with a body weight of ≤10 kg who underwent living related liver transplantation at our centre between January 2004 and December 2014. In all cases of LDLT, a preoperative CT scan of the donor liver was performed, and the total liver and graft volumes were calculated. The graft shape was estimated by measuring the ventro-dorsal (thickness), cranio-caudal, and transversal (width) diameter of segment II/III. We assessed the impact of CT donor liver volumetry and other risk factors on the outcome, defined as patient and graft survival.

Results

In the study period, a total of 48 living related liver transplantations were performed at our centre in infants ≤10 kg [20 male (42%), 28 female (58%)]. The mean weight was 7.3 kg (range 4.4–10 kg). Among the recipients, 33 (69%) received primary abdominal closure and 15 (31%) had temporary abdominal closure. The patient and graft survival rates were 85% and 81%, respectively. In CT volumetry, the mean estimated graft volume was 255 mL (range 140–485 mL) and the actual measured mean graft weight was 307 g (range 127–463 g). The mean ventro-dorsal diameter of segment II/III was 6.9 cm (range 4.3–11.2 cm), the mean cranio-caudal diameter was 9 cm (range 5–14 cm), and the mean width was 10.5 cm (range 6–14.7 cm). The mean graft-body weight ratio (GBWR) was 4.38% (range 1.41–8.04%). A high graft weight, a GBWR >4%, and a large ventro-dorsal diameter of segment II/III were risk factors for poorer patient survival.

Conclusion

Preoperative assessment of the graft size is a crucial investigation before LDLT. For extremely small-sized recipients, not only the graft weight but also the graft shape seems to affect the outcome.

Accuracy of preoperative CT liver volumetry in living donor hepatectomy and its clinical implications

Background

An accurate preoperative volumetric assessment of donor liver is essential for successful living donor liver transplant by ensuring adequate remnant and graft recipient weight ratio (GRWR).

Methods

The study cohort consisted of 744 right lobe (RL), 65 left lobe (LL) and 33 left lateral sector (LLS) grafts from July 2010 to January 2014. A semi-automated interactive commercial software called AW Volume share 6 was used for volumetry. Bland Altman plot was used for assessing the agreement between estimated graft weight (EGW) and actual graft weight (AGW).

Results

There was no statistically significant difference between EGW and AGW for RL graft weight (722±134 vs. 717±126 gm; P=0.06). Although Bland Altman graph showed that 95% limits of agreement was more in LL (-164 to +110) than RL (-156 to +147) and LLS grafts (-137 to +239), CT scan significantly overestimated LL graft weight (EGW =460±118 gm vs. AGW =433±102 gm; P=0.003) and underestimated LLS graft weight (EGW =203±48 gm vs. AGW =254±49 gm; P<0.001).

Conclusions

CT volumetry overestimate LL graft and underestimate LLS graft weight. This should be factored in when selecting LL graft by taking higher GRWR.

Resection plane-dependent error in computed tomography volumetry of the right hepatic lobe in living liver donors

Background/Aims

Computed tomography (CT) hepatic volumetry is currently accepted as the most reliable method for preoperative estimation of graft weight in living donor liver transplantation (LDLT). However, several factors can cause inaccuracies in CT volumetry compared to real graft weight. The purpose of this study was to determine the frequency and degree of resection plane-dependent error in CT volumetry of the right hepatic lobe in LDLT.

Methods

Forty-six living liver donors underwent CT before donor surgery and on postoperative day 7. Prospective CT volumetry (V_P) was measured via the assumptive hepatectomy plane. Retrospective liver volume (V_R) was measured using the actual plane by comparing preoperative and postoperative CT. Compared with intraoperatively measured weight (W), errors in percentage (%) V_P and V_R were evaluated. Plane-dependent error in V_P was defined as the absolute difference between V_P and V_R. % plane-dependent error was defined as follows: |V_P–V_R|/W∙100.

Results

Mean V_P, V_R, and W were 761.9 mL, 755.0 mL, and 696.9 g. Mean and % errors in V_P were 73.3 mL and 10.7%. Mean error and % error in V_R were 64.4 mL and 9.3%. Mean plane-dependent error in V_P was 32.4 mL. Mean % plane-dependent error was 4.7%. Plane-dependent error in V_P exceeded 10% of W in approximately 10% of the subjects in our study.

Conclusions

There was approximately 5% plane-dependent error in liver V_P on CT volumetry. Plane-dependent error in V_P exceeded 10% of W in approximately 10% of LDLT donors in our study. This error should be considered, especially when CT volumetry is performed by a less experienced operator who is not well acquainted with the donor hepatectomy plane.

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.

Preoperative evaluation of liver volume in living donor liver transplantation

OBJECTIVE:

The aim of the present study was to retrospectively evaluate the difference between the preoperative estimated volume and the actual intraoperative graft volume determined in donor right hepatectomies and to evaluate the possible effect of age, gender, and body mass index on the difference.

METHODS:

A total of 225 donor hepatectomies performed at the center between 2016 and 2017 were evaluated for the study. Left hepatectomies and left lateral segmentectomies were excluded from the analysis. As a result, 174 donor right hepatectomies were included in the study. Volumetric analysis was performed with dynamic hepatic computed tomography (CT), including non-contrast analysis, followed by non-ionic, contrast-enhanced arterial, portal, and hepatic-phase, thin-slice scanning. Volumetric analysis was performed based on the CT images using automatic volume calculating software.

RESULTS:

The mean preoperatively estimated graft volume was 800±112 g and the mean intraoperatively measured actual graft volume was 750±131 g. There was a statistically significant difference (p=0.003). Age and body mass index had a significant impact on the discrepancy between the predicted and actual graft volume, while gender did not.

CONCLUSION:

A thorough preoperative evaluation of the donor graft volume should be performed in order to prevent donor morbidity and mortality, as well as small-for-size and large-for-size phenomena in the implanted grafts. Physicians working in the field of transplantation should be aware of the fact that a difference of 10% between the predicted and the actual graft volume is usually encountered.

Fully automated MR liver volumetry using watershed segmentation coupled with active contouring

PURPOSE

Our purpose is to develop a fully automated scheme for liver volume measurement in abdominal MR images, without requiring any user input or interaction.

METHODS

The proposed scheme is fully automatic for liver volumetry from 3D abdominal MR images, and it consists of three main stages: preprocessing, rough liver shape generation, and liver extraction. The preprocessing stage reduced noise and enhanced the liver boundaries in 3D abdominal MR images. The rough liver shape was revealed fully automatically by using the watershed segmentation, thresholding transform, morphological operations, and statistical properties of the liver. An active contour model was applied to refine the rough liver shape to precisely obtain the liver boundaries. The liver volumes calculated by the proposed scheme were compared to the "gold standard" references which were estimated by an expert abdominal radiologist.

RESULTS

The liver volumes computed by using our developed scheme excellently agreed (Intra-class correlation coefficient was 0.94) with the "gold standard" manual volumes by the radiologist in the evaluation with 27 cases from multiple medical centers. The running time was 8.4 min per case on average.

CONCLUSIONS

We developed a fully automated liver volumetry scheme in MR, which does not require any interaction by users. It was evaluated with cases from multiple medical centers. The liver volumetry performance of our developed system was comparable to that of the gold standard manual volumetry, and it saved radiologists' time for manual liver volumetry of 24.7 min per case.

Fast and accurate liver volumetry prior to hepatectomy

BACKGROUND

Volumetric assessment of the liver is essential in the prevention of postresectional liver failure after partial hepatectomy. Currently used methods are accurate but time-consuming. This study aimed to test a new automated method for preoperative volumetric liver assessment.

METHODS

Patients who underwent a contrast enhanced portovenous phase CT-scan prior to hepatectomy in 2012 were included. Total liver volume (TLV) and future remnant liver volume (FRLV) were measured using TeraRecon Aquarius iNtuition(®) (autosegmentation) and OsiriX(®) (manual segmentation) software by two observers for each software package. Remnant liver volume percentage (RLV%) was calculated. Time needed to determine TLV and FRLV was measured. Inter-observer variability was assessed using Bland-Altman plots.

RESULTS

Twenty-seven patients were included. There were no significant differences in measured volumes between OsiriX(®) and iNtuition(®). Moreover, there were significant correlations between the OsiriX(®) observers, the iNtuition(®) observers and between OsiriX(®) and iNtuition(®) post-processing systems (all R(2) > 0.97). The median time needed for complete liver volumetric analysis was 18.4 ± 4.9 min with OsiriX(®) and 5.8 ± 1.7 min using iNtuition(®) (p < 0.001).

CONCLUSION

Both OsiriX(®) and iNtuition(®) liver volumetry are accurate and easily applicable. However, volumetric assessment of the liver with iNtuition(®) auto-segmentation is three times faster compared to manual OsiriX(®) volumetry.

Minimum graft size calculated from preoperative recipient status in living donor liver transplantation

Small-for-size graft syndrome is an inevitable complication in living donor liver transplantation (LDLT). We hypothesized that graft weight (GW) measured after graft procurement is one of the variables predicting postoperative graft function. A total of 138 consecutive recipients of adult-to-adult LDLT between March 1999 and October 2014 were included in this study. We investigated the factors associated with small-for-size-associated graft loss (SAGL) to determine the GW required for each patient. Both preoperatively assessed and postoperatively obtained risk factors for SAGL were analyzed in univariate and multivariate logistic regression analysis. Twelve (8.8%) of the transplant recipients had SAGL. In multivariate logistic regression analyses using preoperatively assessed variables, the preoperative Model for End-Stage Liver Disease (MELD) score (P < 0.001) and actual GW/recipient standard liver volume (SLV) ratio (P = 0.008) were independent predictors of SAGL. The recommended graft volume by preoperative computed tomography volumetry was calculated as SLV × (1.616 × MELD + 0.344)/100/0.85 (mL) [MELD ≥ 18.2], or SLV × 0.35 (mL) [MELD < 18.2]. The required allograft volume in LDLT can be determined by the preoperative MELD score of the recipient, and patients with higher MELD scores require larger grafts or deceased donor whole liver transplant to avoid SAGL. Liver Transplantation 22 599-606 2016 AASLD.

[Importance of preoperative and intraoperative imaging for operative strategies]

Recent advances in preoperative and postoperative imaging have an increasing influence on surgical decision-making and make more complex surgical interventions possible. This improves the possibilities for frequently occurring challenges and promoting improved functional and oncological outcome. This manuscript reviews the role of preoperative and intraoperative imaging in surgery. Various techniques are explained based on examples from hepatobiliary surgery and neurosurgery, in particular real-time procedures, such as the online use of augmented reality and in vivo fluorescence, as well as new and promising optical techniques including imaging of intrinsic signals and vibrational spectroscopy.

Computerized segmentation of liver in hepatic CT and MRI by means of level-set geodesic active contouring

Computerized liver volumetry has been studied, because the current "gold-standard" manual volumetry is subjective and very time-consuming. Liver volumetry is done in either CT or MRI. A number of researchers have developed computerized liver segmentation in CT, but there are fewer studies on ones for MRI. Our purpose in this study was to develop a general framework for liver segmentation in both CT and MRI. Our scheme consisted of 1) an anisotropic diffusion filter to reduce noise while preserving liver structures, 2) a scale-specific gradient magnitude filter to enhance liver boundaries, 3) a fast-marching algorithm to roughly determine liver boundaries, and 4) a geodesic-active-contour model coupled with a level-set algorithm to refine the initial boundaries. Our CT database contained hepatic CT scans of 18 liver donors obtained under a liver transplant protocol. Our MRI database contains 23 patients with 1.5T MRI scanners. To establish "gold-standard" liver volumes, radiologists manually traced the contour of the liver on each CT or MR slice. We compared our computer volumetry with "gold-standard" manual volumetry. Computer volumetry in CT and MRI reached excellent agreement with manual volumetry (intra-class correlation coefficient = 0.94 and 0.98, respectively). Average user time for computer volumetry in CT and MRI was 0.57 ± 0.06 and 1.0 ± 0.13 min. per case, respectively, whereas those for manual volumetry were 39.4 ± 5.5 and 24.0 ± 4.4 min. per case, respectively, with statistically significant difference (p < .05). Our computerized liver segmentation framework provides an efficient and accurate way of measuring liver volumes in both CT and MRI.

CT volumetry of the liver: where does it stand in clinical practice?

Imaging-based volumetry has been increasingly utilised in current clinical practice to obtain accurate measurements of the liver volume. This is particularly useful prior to major hepatic resection and living donor liver transplantation where the size of the remnant liver and liver graft, respectively, affects procedural success and postoperative mortality and morbidity. The use of imaging-based volumetry, with emphasis on computed tomography, will be reviewed. We will explore the various technical factors that contribute to accurate volumetric measurements, and demonstrate how the accuracies of these techniques are influenced by their methodologies. The strengths and limitations of using anatomical imaging to estimate liver volume will be discussed, in relation to laboratory and functional imaging methods of assessment.

Computerized liver volumetry on MRI by using 3D geodesic active contour segmentation

OBJECTIVE

Our purpose was to develop an accurate automated 3D liver segmentation scheme for measuring liver volumes on MRI.

SUBJECTS AND METHODS

Our scheme for MRI liver volumetry consisted of three main stages. First, the preprocessing stage was applied to T1-weighted MRI of the liver in the portal venous phase to reduce noise and produce the boundary-enhanced image. This boundary-enhanced image was used as a speed function for a 3D fast-marching algorithm to generate an initial surface that roughly approximated the shape of the liver. A 3D geodesic-active-contour segmentation algorithm refined the initial surface to precisely determine the liver boundaries. The liver volumes determined by our scheme were compared with those manually traced by a radiologist, used as the reference standard.

RESULTS

The two volumetric methods reached excellent agreement (intraclass correlation coefficient, 0.98) without statistical significance (p = 0.42). The average (± SD) accuracy was 99.4% ± 0.14%, and the average Dice overlap coefficient was 93.6% ± 1.7%. The mean processing time for our automated scheme was 1.03 ± 0.13 minutes, whereas that for manual volumetry was 24.0 ± 4.4 minutes (p < 0.001).

CONCLUSION

The MRI liver volumetry based on our automated scheme agreed excellently with reference-standard volumetry, and it required substantially less completion time.

ALPPS in right trisectionectomy: a safe procedure to avoid postoperative liver failure?

INTRODUCTION

To induce rapid hepatic hypertrophy and to reduce post-hepatectomy liver failure (PHLF), associating liver partition and portal vein ligation for staged hepatectomy (ALPPS) has been recently developed for patients with a limited future liver remnant. The aim of this study was to further assess the perioperative risk of this procedure and its specific indications.

PATIENTS AND METHODS

The study was performed between November 2010 and April 2012 for patients undergoing right trisectionectomy by the ALPPS approach. Liver volume, intra- and postoperative complications, including PHLF, and residual tumour status were compared for patients with different diagnoses.

RESULTS

The interval between two operations in nine patients undergoing ALPPS was 13 days (median). Sufficient hepatic hypertrophy was achieved with a volume gain of 87.2 % (median). All patients underwent right trisectionectomy without residual tumours. In contrast to six patients with uneventful intra- and postoperative course, bile leak, vancomycin-resistant enterococcus infection, PHLF and sepsis developed in two of three patients with hilar cholangiocarcinoma as the preoperative diagnosis.

CONCLUSION

ALPPS leads to sufficient hepatic hypertrophy within 2 weeks, avoiding PHLF in most patients. In patients with hilar cholangiocarcinoma, ALPPS should be applied with extreme caution due to high morbidity and mortality.

Relationship between preoperative volume and weight of the right liver lobe graft, with and without the middle hepatic vein, in living-donor transplantation

BACKGROUND

The aim of this study was to assess the relationship between the preoperative volume of the right liver lobe (as determined by computed tomography) and the intraoperative graft weight with or without the middle hepatic vein.

METHODS

Sixty-three patients who underwent liver transplantation were included in this study. The preoperative volumes of both the left and the right liver lobe were measured in all patients using computed tomography. The intraoperative weight of the right liver lobe was also measured with (group 1, n = 29) and without (group 2, n = 34) the middle hepatic vein. The results were compared with respect to gender, age, body weight, height, body mass index (BMI), weights of the left and right liver lobes as measured by computed tomography, and intraoperative weight of the right liver lobe.

RESULTS

A 21.64 % difference was observed between the weight of the right liver lobe as measured by computed tomography and the weight of the right lobe without the hepatic vein as measured intraoperatively (group 2). Moreover, a 12.38 % difference was observed between the weight of the right liver lobe as measured by computed tomography and the weight of the right lobe plus the middle hepatic vein as measured intraoperatively (group 1).

CONCLUSIONS

The weight of the right liver lobe graft in a living-donor transplantation is less than that calculated by preoperative computed tomography, and the inclusion of the middle hepatic vein in the right liver lobe graft resulted in a statistically significant decrease in this difference.

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

The estimation of the standard liver volume (SLV) is an important component of the evaluation of potential living liver donors and the surgical planning for resection for tumors. At least 16 different formulas for estimating SLV have been published in the worldwide literature. More recently, several proprietary software-assisted image postprocessing (SAIP) programs have been developed to provide accurate volume measurements based on the actual anatomy of a specific patient. Using SAIP, we measured SLV in 375 healthy potential liver donors and compared the results to SLV values that were estimated with the previously published formulas and each donor's demographic and anthropomorphic data. The percentage errors of the 16 SLV formulas versus SAIP varied by more than 59% (from -21.6% to +37.7%). One formula was not statistically different from SAIP with respect to the percentage error (-1.2%), and another formula was not statistically different with respect to the absolute liver volume (18 mL). More than 75% of the estimated SLV values produced by these 2 formulas had percentage errors within ±15%, and the formulas provided good predictions within acceptable agreement (±15%) on scatter plots. Because of the wide variability, care must be taken when a formula is being chosen for estimating SLV, but the 2 aforementioned formulas provided the most accurate results with our patient demographics.

Function and volume recovery after partial hepatectomy: influence of preoperative liver function, residual liver volume, and obesity

BACKGROUND

The regenerative capacity of the liver is an essential pre-condition for the successful application of partial hepatectomy. However, the actual kinetics of functional recovery remains unspecified and no adequate tool for its clinical monitoring has yet been available.

METHODS

Eighty-five patients receiving major hepatectomy were investigated from the preoperative evaluation until 12 weeks after surgery. Liver function was determined by the LiMAx test for the enzymatic capacity of cytochrome P450 1A2. Liver volume was determined by volumetric analysis of repeated computer tomography scans. Functional and volume recovery were compared during follow-up.

RESULTS

Major hepatectomy decreased liver function capacity to 35.7 ± 13.8% of preoperative function. It was shown that functional recovery already reaches 77.2 ± 33.5% of preoperative values within 10 days. The actual kinetics were dependent from the type and extent of hepatectomy. Complete functional restoration was achieved within 12 weeks, while liver volume still remained at 73.2 ± 14.8% of preoperative. A constant but interindividually variable correlation between function and volume was observed at all points in time.

CONCLUSION

Partial hepatectomy leads to fast and complete functional recovery, while volume recovery is delayed and remains often incomplete. The functional recovery is mainly influenced by the preoperative liver function, the residual liver volume, and by obesity.

Accurate estimation of living donor right hemi-liver volume from portal vein diameter measurement and standard liver volume calculation

Lee et al. recently published a method for estimating right hemi-liver volume (RHLV) by using bedside ultrasound measurement of right (R) and left (L) portal vein (PV) diameters and Urata's standard liver volume (SLV) formula where RHLV = SLV×[R(2) /(R(2) +L(2) )]. We calculated RHLV by substituting SLV from 15 different published formulas in the worldwide literature. We also modified Lee's method using right anterior (RA) and posterior (RP) where RHLV = SLV×[(RA(2) +RP(2) )/(RA(2) +RP(2) +L(2) )] for donors with unusual PV branching. We compared the calculated RHLV with RHLV estimated with software-assisted CT (SACT) volumetry and actual graft weight after right-lobe donation in 200 right-lobe donors. This study confirmed that accurate estimates of RHLV can be achieved by SACT volumetry or by the simple method of Lee but using the SLV of only 3 of the 15 published formulas (Lin or Vauthey using body weight or body surface area) rather than Urata's. Our modification of the Lee's formula using RA and RP, PV diameters was also accurate and not different from Lee's formula. These simplified formulas may be used for donor screening for graft size adequacy before expensive evaluation proceeds.

Quantitative radiology: automated CT liver volumetry compared with interactive volumetry and manual volumetry

OBJECTIVE

The purpose of this study was to evaluate automated CT volumetry in the assessment of living-donor livers for transplant and to compare this technique with software-aided interactive volumetry and manual volumetry.

MATERIALS AND METHODS

Hepatic CT scans of 18 consecutively registered prospective liver donors were obtained under a liver transplant protocol. Automated liver volumetry was developed on the basis of 3D active-contour segmentation. To establish reference standard liver volumes, a radiologist manually traced the contour of the liver on each CT slice. We compared the results obtained with automated and interactive volumetry with those obtained with the reference standard for this study, manual volumetry.

RESULTS

The average interactive liver volume was 1553 ± 343 cm(3), and the average automated liver volume was 1520 ± 378 cm(3). The average manual volume was 1486 ± 343 cm(3). Both interactive and automated volumetric results had excellent agreement with manual volumetric results (intraclass correlation coefficients, 0.96 and 0.94). The average user time for automated volumetry was 0.57 ± 0.06 min/case, whereas those for interactive and manual volumetry were 27.3 ± 4.6 and 39.4 ± 5.5 min/case, the difference being statistically significant (p < 0.05).

CONCLUSION

Both interactive and automated volumetry are accurate for measuring liver volume with CT, but automated volumetry is substantially more efficient.

Preoperative estimation of the liver graft weight in adult right lobe living donor liver transplantation using maximal portal vein diameters

An accurate preoperative estimate of the graft weight is vital to avoid small-for-size syndrome in the recipient and ensure donor safety after adult living donor liver transplantation (LDLT). Here we describe a simple method for estimating the graft volume (GV) that uses the maximal right portal vein diameter (RPVD) and the maximal left portal vein diameter (LPVD). Between June 2004 and December 2009, 175 consecutive donors undergoing right hepatectomy for LDLT were retrospectively reviewed. The GV was determined with 3 estimation methods: (1) the radiological graft volume (RGV) estimated by computed tomography (CT) volumetry; (2) the computed tomography-calculated graft volume (CGV-CT), which was obtained by the multiplication of the standard liver volume (SLV) by the RGV percentage with respect to the total liver volume derived from CT; and (3) the portal vein diameter ratio-calculated graft volume (CGV-PVDR), which was obtained by the multiplication of the SLV by the portal vein diameter ratio [PVDR; ie, PVDR = RPVD(2) /(RPVD(2) + LPVD(2) )]. These values were compared to the actual graft weight (AGW), which was measured intraoperatively. The mean AGW was 633.63 ± 107.51 g, whereas the mean RGV, CGV-CT, and CGV-PVDR values were 747.83 ± 138.59, 698.21 ± 94.81, and 685.20 ± 90.88 cm(3) , respectively. All 3 estimation methods tended to overestimate the AGW (P < 0.001). The actual graft-to-recipient body weight ratio (GRWR) was 1.00% ± 0.19%, and the GRWRs calculated on the basis of the RGV, CGV-CT, and CGV-PVDR values were 1.19% ± 0.25%, 1.11% ± 0.22%, and 1.09% ± 0.21%, respectively. Overall, the CGV-PVDR values better correlated with the AGW and GRWR values according to Lin's concordance correlation coefficient and the Landis and Kock benchmark. In conclusion, the PVDR method is a simple estimation method that accurately predicts GVs and GRWRs in adult LDLT.

Liver tissue sparing resection using a novel planning tool

PURPOSE

Accurate preoperative prediction of liver function, volume, and vessel anatomy is essential in preventing postoperative liver failure, optimizing safety, and ensuring optimal outcome in patients undergoing hepatic surgery. We propose that preoperative resection planning provides useful anatomical and volumetric data, allowing for sparing of liver tissue in surgical resections. The purpose of the present study was to evaluate the use of a novel resection planning tool.

METHODS

Thirteen patients undergoing hemihepatectomy were included. Preoperative resection planning was performed using the commercially available software Mint Liver. During resection planning, virtual resections were calculated based on Couinaud classification, Cantlie's line (standard), and individually by the operating surgeon (individual). Intraoperatively, volume and weight of the resected specimen were measured. A 14-day follow-up was conducted, and laboratory parameters were collected. Statistical analysis was performed, comparing virtual resection volumes (i.e., standard vs. individual) and secondarily virtual vs. actual resection volume.

RESULTS

We found a significant difference (p = 0.001) in the comparison of standard vs. individual in all 13 cases, with an average 92.8 mL smaller resected volume, sparing 11.3% of liver parenchyma with virtual resection. No patients suffered from acute liver failure. Perioperative mortality was 0%.

CONCLUSION

Mint Liver is capable of acquiring exact anatomical and volumetric knowledge prior to hepatic resections. Liver parenchyma can be spared by preoperative assessment of the resection plan. We propose that this tool could be an important addition to preoperative patient evaluation, especially in complex liver surgery and living donor liver transplantation where precise volumetry is the decisive factor.

Computer-aided measurement of liver volumes in CT by means of geodesic active contour segmentation coupled with level-set algorithms

PURPOSE

Computerized liver extraction from hepatic CT images is challenging because the liver often abuts other organs of a similar density. The purpose of this study was to develop a computer-aided measurement of liver volumes in hepatic CT.

METHODS

The authors developed a computerized liver extraction scheme based on geodesic active contour segmentation coupled with level-set contour evolution. First, an anisotropic diffusion filter was applied to portal-venous-phase CT images for noise reduction while preserving the liver structure, followed by a scale-specific gradient magnitude filter to enhance the liver boundaries. Then, a nonlinear grayscale converter enhanced the contrast of the liver parenchyma. By using the liver-parenchyma-enhanced image as a speed function, a fast-marching level-set algorithm generated an initial contour that roughly estimated the liver shape. A geodesic active contour segmentation algorithm coupled with level-set contour evolution refined the initial contour to define the liver boundaries more precisely. The liver volume was then calculated using these refined boundaries. Hepatic CT scans of 15 prospective liver donors were obtained under a liver transplant protocol with a multidetector CT system. The liver volumes extracted by the computerized scheme were compared to those traced manually by a radiologist, used as "gold standard."

RESULTS

The mean liver volume obtained with our scheme was 1504 cc, whereas the mean gold standard manual volume was 1457 cc, resulting in a mean absolute difference of 105 cc (7.2%). The computer-estimated liver volumetrics agreed excellently with the gold-standard manual volumetrics (intraclass correlation coefficient was 0.95) with no statistically significant difference (F = 0.77; p(F < or = f) = 0.32). The average accuracy, sensitivity, specificity, and percent volume error were 98.4%, 91.1%, 99.1%, and 7.2%, respectively. Computerized CT liver volumetry would require substantially less completion time (compared to an average of 39 min per case by manual segmentation).

CONCLUSIONS

The computerized liver extraction scheme provides an efficient and accurate way of measuring liver volumes in CT.