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BACKGROUND: Postoperative hepatic insufficiency (PHI) is the most feared complication after hepatectomy. Volume of the future liver remnant (FLR) is one objectively measurable indicator to identify patients at risk of PHI. In this review, we summarized the development and rationale for the use of liver volumetry and liver-regenerative interventions and highlighted emerging tools that could yield new advancements in liver volumetry. METHODS: A review of MEDLINE/PubMed, Embase, and Cochrane Library databases was conducted to identify literature related to liver volumetry. The references of relevant articles were reviewed to identify additional publications. RESULTS: Liver volumetry based on radiologic imaging was developed in the 1980s to identify patients at risk of PHI and later used in the 1990s to evaluate grafts for living donor living transplantation. The field evolved in the 2000s by the introduction of standardized FLR based on the hepatic metabolic demands and in the 2010s by the introduction of the degree of hypertrophy and kinetic growth rate as measures of the FLR regenerative and functional capacity. Several liver-regenerative interventions, most notably portal vein embolization, are used to increase resectability and reduce the risk of PHI. In parallel with the increase in automation and machine assistance to physicians, many semi- and fully automated tools are being developed to facilitate liver volumetry. CONCLUSION: Liver volumetry is the most reliable tool to detect patients at risk of PHI. Advances in imaging analysis technologies, newly developed functional measures, and liver-regenerative interventions have been improving our ability to perform safe hepatectomy.

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Background Right hepatic venous anatomy, right lobe volume, and percentage of remnant liver are issues to be considered in preoperative planning especially transplantation. Objectives The aim of this study was to investigate the relationship of the presence of the inferior right hepatic vein (IRHV) with the right hepatic vein (RHV) diameter, right lobe volume, and percentage of remnant liver. Materials and Methods In t his cross-sectional study, the computed tomography (CT) images of 90 patients who underwent triphasic CT for being living liver donation were evaluated retrospectively. The number and diameter of IRHVs and the diameter of main RHV were recorded. For the liver volume analysis, a deep learning-based automatic liver segmentation (Hepatic VCAR) program was used. A virtual hepatectomy plane was drawn, where the right and left liver volumes were found and the percentage of the left lobe to the total liver volume was calculated. Pearson's correlation analysis was used for correlation analysis and Student's t -test was used to compare parameters. Results A total of 74 IRHVs were detected in 53 (58.88%) of 90 patients. There were no differences in the percentage of remnant left lobe volume, right lobe volume, and RHV diameter between the IRHV (+) and (-) groups. The RHV diameter had a weak negative correlation with the IRHV diameter, and a weak positive correlation with the right lobe volume. Conclusions The percentage of remnant left lobe volume, right lobe volume, and RHV diameter did not differ in liver donors with and without an IRHV. The RHV diameter had a weak negative correlation with the IRHV diameter and a weak positive correlation with the right lobe volume.

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Introduction: Future liver remnant volume (FLRV), a risk factor for liver failure (PHLF) after major hepatectomy (MH), is not routinely measured. This study aimed to evaluate the association between FLRV and PHLF. Patients and methods: All patients undergoing MH (4 + segments) between 2011 and 2018 were identified from a prospectively maintained single-centre database. Perioperative data were collected for patients with PHLF, who were matched (1:2) with non-PHLF controls. FLRV and FLRV% (i.e., % of total liver volume) were calculated retrospectively from preoperative CT scans using Synapse-3D software, and compared between the PHLF and matched control groups. Results: Of 711 patients undergoing MH, PHLF occurred in 27 (3.8%), of whom 24 had preoperative CT scans available. These patients were matched to 48 non-PHLF controls, 98% of whom were classified as being at high risk of PHLF on preoperative risk scoring. FLRV% was significantly lower in the PHLF group, compared to matched controls (median: 28.7 vs. 35.2%, p = 0.010), with FLRV% < 30% in 58% and 29% of patients, respectively. Assessment of the ability of FLRV% to differentiate between PHLF and matched controls returned an area under the ROC curve of 0.69, and an optimal cut-off value of FLRV% < 31.5%, which yielded 79% sensitivity and 67% specificity. Conclusions: FLRV% is significantly predictive of PHLF after MH, with over half of patients with PHLF having FLRV% < 30%. In light of this, we propose that all patients should undergo risk stratification prior to MH, with the high risk patients additionally being assessed with CT volumetry.

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OBJECTIVE: To validate the newly developed artificial intelligence (AI)-assisted simulation by evaluating the speed of three-dimensional (3D) reconstruction and accuracy of segmental volumetry among patients with liver tumors. BACKGROUND: AI with a deep learning algorithm based on healthy liver computer tomography images has been developed to assist three-dimensional liver reconstruction in virtual hepatectomy. METHODS: 3D reconstruction using hepatic computed tomography scans of 144 patients with liver tumors was performed using two different versions of Synapse 3D (Fujifilm, Tokyo, Japan): the manual method based on the tracking algorithm and the AI-assisted method. Processing time to 3D reconstruction and volumetry of whole liver, tumor-containing and tumor-free segments were compared. RESULTS: The median total liver volume and the volume ratio of a tumor-containing and a tumor-free segment were calculated as 1035 mL, 9.4%, and 9.8% by the AI-assisted reconstruction, whereas 1120 mL, 9.9%, and 9.3% by the manual reconstruction method. The mean absolute deviations were 16.7 mL and 1.0% in the tumor-containing segment and 15.5 mL and 1.0% in the tumor-free segment. The processing time was shorter in the AI-assisted (2.1 vs. 35.0 min; p < 0.001). CONCLUSIONS: The virtual hepatectomy, including functional liver volumetric analysis, using the 3D liver models reconstructed by the AI-assisted methods, was reliable for the practical planning of liver tumor resections.

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SUMMARY: The application of stereology in hepatobiliary conditions is essential in liver volume estimation. Computerized topographic scan with contrast is a reliable method in liver scanning for precise boundaries demarcation. Liver volumetry varies in relation to different factors. Reports showed a correlation of liver volume with sex and body mass index. Steady relation between age and ethnicity is not established. This study aimed to design a protocol for liver volume measurement and apply it in the estimation of volume among the Sudanese population use stereology. Recruitment of the study population was obtained in the royal scan clinic in Khartoum by making an announcement for participation in the study. Patients with a history of hepatobiliary diseases were excluded. CT abdomen with contrast was obtained in DICOM format and transferred to computer-based software for image analysis. A protocol was designed and validated and then applied in volume estimation using software MRIcro for image display, ImageJ for volume estimation, and Onis 2.6 as image viewer. 300 apparently healthy volunteers were recruited. The protocol reliability result was 0.805. Absolute mean liver volume was 3261.32 ± 1365.313 cm3. High liver volume among females was detected than among males. A positive correlation was detected between volume and body mass index (p-value 0.001) regardless of sex. Relation with age showed a rough steady rise till the age of 50 years then it started to decline steadily. The relationship was detected in liver volume with sex and body mass index. More studies are needed to investigate the relationship between ethnicity and age groups.

RESUMEN: La aplicación de la estereología en condiciones hepatobiliares es fundamental en la estimación del volumen hepático. El escaneo topográfico computarizado con contraste es un método confiable en el escaneo del hígado para la demarcación precisa de sus límites. La volumetría hepática varía en función de diferentes factores. Los informes mostraron una correlación del volumen del hígado con el sexo y el índice de masa corporal. No se establece una relación estable entre la edad y la etnia. Este estudio tuvo como objetivo diseñar un protocolo para la medición del volumen hepático de la población sudanesa usando la estereología. El reclutamiento de la población de estudio fue realizado en la clínica de exploración real en Jartum mediante un anuncio de participación. Se excluyeron los pacientes con antecedentes de enfermedades hepatobiliares. Se obtuvo TC de abdomen con contraste en formato DICOM y se transfirió a un software informático para el análisis de imágenes. Se diseñó y validó un protocolo y luego se aplicó en la estimación de volumen utilizando el software MRIcro para la visualización de imágenes, ImageJ para la estimación de volumen y Onis 2.6 como visor de imágenes. Se reclutaron 300 voluntarios sanos. El resultado de la fiabilidad del protocolo fue 0,805. El volumen hepático medio absoluto fue 3261,32 ± 1365,313 cm3. Se detectó un volumen más elevado de hígado en las mujeres que en los hombres. Se detectó una correlación positiva entre el volumen y el índice de masa corporal (valor de p 0,001) independientemente del sexo. La relación con la edad mostró un aumento continuo y brusco hasta los 50 años, luego comenzó a disminuir de manera constante. Se detectó la relación del volumen hepático con el sexo y el índice de masa corporal. Se necesitan más estudios para investigar la relación entre la etnia y los grupos etarios.

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Liver volumetry is an important tool in clinical practice. The calculation of liver volume is primarily based on Computed Tomography. Unfortunately, automatic segmentation algorithms based on handcrafted features tend to leak segmented objects into surrounding tissues like the heart or the spleen. Currently, convolutional neural networks are widely used in various applications of computer vision including image segmentation, while providing very promising results. In our work, we utilize robustly segmentable structures like the spine, body surface, and sagittal plane. They are used as key points for position estimation inside the body. The signed distance fields derived from these structures are calculated and used as an additional channel on the input of our convolutional neural network, to be more specific U-Net, which is widely used in medical image segmentation tasks. Our work shows that this additional position information improves the results of the segmentation. We test our approach in two experiments on two public datasets of Computed Tomography images. To evaluate the results, we use the Accuracy, the Hausdorff distance, and the Dice coefficient. Code is publicly available at: https://gitlab.com/hachaf/liver-segmentation.git.

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OBJECTIVE: To compare radioembolization treatment zone volumes from mapping cone beam CT (CBCT) versus planning CT/MRI and to model their impact on dosimetry. METHODS: Y90 cases were retrospectively identified in which intra-procedural CBCT angiograms were performed. Segmental and lobar treatment zone volumes were calculated with semi-automated contouring using Couinaud venous anatomy (planning CT/MRI) or tumor angiosome enhancement (CBCT). Differences were compared with a Wilcoxon signed-rank test. Treatment zone-specific differences in segmental volumes by volumetric method were also calculated and used to model differences in delivered dose using medical internal radiation dosimetry (MIRD) at 200 and 120 Gy targets. Anatomic, pathologic, and technical factors likely affecting segmental volumes by volumetric method were evaluated. RESULTS: Forty segmental and 48 lobar CBCT angiograms and corresponding planning CT/MRI scans were included. Median Couinaud- and CBCT-derived segmental volumes were 281 and 243 mL, respectively (p = 0.005). Differences between Couinaud and CBCT lobar volumes (right, left) were not significant (p = 0.24, p = 0.07). Couinaud overestimated segmental volumes in 28 cases by a median of 98 mL (83%) and underestimated in 12 cases by median 69 mL (20%). At a 200 Gy dose target, Couinaud estimates produced median delivered doses of 367 and 160 Gy in these 28 and 12 cases. At a 120 Gy target, Couinaud produced doses of 220 and 96 Gy. Proximal vs. distal microcatheter positioning, variant arterial anatomy, and tumor location on or near segmental watersheds were leading factors linked to volumetric differences. CONCLUSION: Use of CBCT-based volumetry may allow more accurate, personalized dosimetry for segmental Y90 radioembolization.

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OBJECTIVES: To correlate total and lobar liver and spleen volume with disease severity in primary sclerosing cholangitis (PSC) as determined by Mayo risk score. METHODS: This HIPAA-compliant single center retrospective study included 147 PSC patients with available imaging studies (MRCP/CT) and laboratory data between January 2003 and January 2018. Total and lobar (right, left and caudate) liver volume and spleen volume were measured. ANOVA test was performed to assess the differences in volumes between low, intermediate and high-risk groups (Mayo risk score <0, >0 and <2, >2, respectively). Correlations between volumes and Mayo risk score were calculated. ROC analysis was performed to assess the accuracy of the variable with the strongest correlation to PSC severity to predict Mayo risk score. P value <0.05 was considered statistically significant. RESULTS: The mean age of this cohort was 45 ± 17 years; 58% were men. Absolute volumes of left lobe, caudate and spleen and volume ratios of left lobe and caudate to total liver volume of the high-risk group were significantly higher compared to those of low and intermediate risk groups (p < 0.05). Left lobe to total liver volume ratio had the highest correlation to Mayo risk score (Pearson correlation coefficient 0.61, p < 0.05) and on ROC analysis it had 84.4% accuracy in detecting high-risk PSC. CONCLUSIONS: In this single institution large cohort study, the left lobe to total liver volume ratio was the best quantifiable volumetric biomarker to correlate with severity of PSC as identified by Mayo risk score.

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PURPOSE: The purpose of this study was to assess the accuracy of liver tumor volumetry by manual contouring on computed tomography (CT) compared to pathological tumor volume determined from surgical specimen that served as a reference method. PATIENTS AND METHOD: Thirty-eight patients with planned liver surgery and a total of 41 liver tumors were included. There were 24 men and 14 women (mean age: 57 years; range: 32-85 years). Two readers calculated tumor volume by manual contouring on axial CT images. The reference tumor volume was calculated by manual contouring with dedicated software applied to the liver specimen slice. CT and pathology volumes were compared and the percentage of error (PE%) was calculated. Intraobserver and interobserver variabilities were calculated using Bland and Altman plots, and intraclass correlation coefficients (ICC). RESULTS: A strong correlation was found between CT tumor volumes and pathology tumor volumes (r=0.994; P<0.001 for both readers). The mean (±SD) and median (range) PE% were 19%±12% and 16% (1%, +42%) and 19%±15% and 17% (0%, +55%) for readers 1 and 2, respectively. Readers 1 and 2 significantly overestimated tumor volume (i.e., PE%>40%) in 3 (7%) and 2 (5%) tumors on CT, respectively. Tumor volume was not significantly underestimated in any of the patients (i.e. PE%>33%). Tumor size, CT attenuation, time between imaging and surgery, contours and margin definition did not influence the results of PE% values (all P values>0.05 for both readers). The bias and limits of agreement between the two readers were +4.6% and (-24%, +33%) with an ICC of 0.997. CONCLUSION: There was a strong correlation between tumor volume measured on CT and that assessed with surgical specimen. Tumor size, visibility of contours and tumor margins and the time between CT and surgery did not influence the results.

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OBJECTIVES: This study aimed to evaluate the progress of future liver remnant volume (FLRV) in patients with liver metastases after portal vein embolization (PVE) with the application of hematopoietic stem cells (HSCs) and compare it with a patients control group after PVE only. METHODS: Twenty patients (group 1) underwent PVE with contralateral HSC application. Subsequently, CT volumetry with the determination of FLRV was performed at weekly intervals, in total three weeks. A sample of twenty patients (group 2) who underwent PVE without HSC application was used as a control group. RESULTS: The mean of FLRV increased by 173.2 mL during three weeks after the PVE/HSC procedure, whereas by 98.9 mL after PVE only (p = 0.015). Furthermore, the mean daily growth of FLRV by 7.6 mL in group 1 was significantly higher in comparison with 4.1 mL in group 2 (p = 0.007). CONCLUSIONS: PVE with the application of HSC significantly facilitates growth of FLRV in comparison with PVE only. This method could be one of the new suitable approaches to increase the resectability of liver tumours.

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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.

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Portal vein embolization (PVE) is a safe, percutaneous procedure that has been proven to lower the complication rates of curative intent large-volume hepatic resection by inducing hypertrophy of the future liver remnant. While the safety and efficacy of PVE has been well substantiated, there remains controversy with regards to the technical details, periprocedural management, and whether alternative methods of achieving future liver remnant hypertrophy are preferable to PVE. This paper will address those controversies and offer recommendations based on available data.

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Liver volume can reflect the change of parenchyma volume and functional reserve of liver.Liver volumetry is commonly achieved by imaging methods such as ultrasound,CT and MRI,while CT volumetry is most commonly used in clinical practice.This article discussed the decision making among different liver volumetry methods and associated applications in hepatectomy.

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In this paper, a fully automatic scheme for measuring liver volume in 3D MR images was developed. The proposed MRI liver volumetry scheme consisted of four main stages. First, the preprocessing stage was applied to T1-weighted MR images of the liver in the portal-venous phase to reduce noise. The histogram of the 3D image was determined, and the second-to-last peak of the histogram was calculated using a neural network. Thresholds, which are determined based upon the second-to-last peak, were used to generate a thresholding image. This thresholding image was refined using a gradient magnitude image. The morphological and connected component operations were applied to the refined image to generate the rough shape of the liver. A 3D geodesic-active-contour segmentation algorithm refined the rough shape in order to more precisely determine the liver boundaries. The liver volumes determined by the proposed automatic volumetry were compared to those manually traced by radiologists; these manual volumes were used as a "gold standard." The two volumetric methods reached an excellent agreement. The Dice overlap coefficient and the average accuracy were 91.0 ±2.8% and 99.0 ±0.4%, respectively. The mean processing time for the proposed automatic scheme was 1.02 ±0.08 min (CPU: Intel, core i7, 2.8GHz), whereas that of the manual volumetry was 24.3 ±3.7 min (p < 0.001).

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RATIONALE AND OBJECTIVES: To compare the repeatability and agreement of a semiautomated liver segmentation method with manual segmentation for assessment of total liver volume on CT (computed tomography). MATERIALS AND METHODS: This retrospective, institutional review board-approved study was conducted in 41 subjects who underwent liver CT for preoperative planning. The major pathologies encountered were colorectal cancer metastases, benign liver lesions and hepatocellular carcinoma. This semiautomated segmentation method is based on variational interpolation and 3D minimal path-surface segmentation. Total and subsegmental liver volumes were segmented from contrast-enhanced CT images in venous phase. Two image analysts independently performed semiautomated segmentations and two other image analysts performed manual segmentations. Repeatability and agreement of both methods were evaluated with intraclass correlation coefficients (ICC) and Bland-Altman analysis. Interaction time was recorded for both methods. RESULTS: Bland-Altman analysis revealed an intrareader agreement of -1 ± 27 mL (mean ± 1.96 standard deviation) with ICC of 0.999 (P < .001) for manual segmentation and 12 ± 97 mL with ICC of 0.991 (P < .001) for semiautomated segmentation. Bland-Altman analysis revealed an interreader agreement of -4 ± 22 mL with ICC of 0.999 (P < .001) for manual segmentation and 5 ± 98 mL with ICC of 0.991 (P < .001) for semiautomated segmentation. Intermethod agreement was found to be 3 ± 120 mL with ICC of 0.988 (P < .001). Mean interaction time was 34.3 ± 16.7 minutes for the manual method and 8.0 ± 1.2 minutes for the semiautomated method (P < .001). CONCLUSIONS: A semiautomated segmentation method can substantially shorten interaction time while preserving a high repeatability and agreement with manual segmentation.

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BACKGROUND: Metastatic spread is the most common cause of cancer-related death in colorectal cancer (CRC) patients, with the liver being the mostly affected organ. Circulating tumor cells (CTCs) are a prognostic marker in stage IV CRC. We hypothesized that tumor burden in the liver correlates with CTC quantity. METHODS: Blood (7.5 ml) was prospectively collected from 24 patients with novel stage IV CRC diagnosis. Baseline EpCAM+ CTCs were analyzed with the FDA-approved CellSearch® system. Clinicopathological data were collected, and hepatic tumor burden was determined by radiographic liver volumetry with contrast-enhanced CT scans. CRC primary tumors were immunohistochemically stained for EpCAM expression with BerEP4 monoclonal antibody. Statistical analyses were performed using 2-sample T-test, non-parametric Wilcoxon Rank-Sum test, and Fisher's exact test. RESULTS: CTCs were detected n 17 (71%) of 24 patients. The overall mean CTC number as determined by EpCAM-based CellSearch® detection was 6.3 (SEM 2.9). High baseline CTC numbers (≥3) correlated significantly with a high tumor/liver ratio (≥30%), and with high serum CEA levels, as determined by two-sample T-test on log-transformed data and by Fisher's Exact test on categorical data analysis (P < 0.05). The CRC primary tumors were consistently expressing EpCAM by immunostaining. CONCLUSIONS: High tumor burden in the liver and high baseline serum CEA levels are associated with high number of baseline CTCs in stage IV CRC patients. Future studies should further investigate the biological role and expression patterns of single CTCs in cancer patients to further improve personalized treatment strategies.

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Living donor liver transplantation is an effective, life sustaining surgical treatment in patients with end-stage liver disease and a successful liver transplant requires a close working relationship between the radiologist and the transplant surgeon. There is extreme variability in hepatic vascular anatomy; therefore, preoperative imaging of potential liver donors is crucial not only in donor selection but also helps the surgeons in planning their surgical approach. In this article, we elaborate important aspects in evaluation of potential liver donors on multi-detector computed tomography (MDCT) and the utility of MDCT in presurgical assessment of the hepatic parenchyma, relevant hepatic vascular anatomy and segmental liver volumes.

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PURPOSE: To assess the feasibility of semiautomated MR volumetry using gadoxetic acid-enhanced MRI at the hepatobiliary phase compared with manual CT volumetry. METHODS: Forty potential live liver donor candidates who underwent MR and CT on the same day, were included in our study. Semiautomated MR volumetry was performed using gadoxetic acid-enhanced MRI at the hepatobiliary phase. We performed the quadratic MR image division for correction of the bias field inhomogeneity. With manual CT volumetry as the reference standard, we calculated the average volume measurement error of the semiautomated MR volumetry. We also calculated the mean of the number and time of the manual editing, edited volume, and total processing time. RESULTS: The average volume measurement errors of the semiautomated MR volumetry were 2.35% ± 1.22%. The average values of the numbers of editing, operation times of manual editing, edited volumes, and total processing time for the semiautomated MR volumetry were 1.9 ± 0.6, 8.1 ± 2.7 s, 12.4 ± 8.8 mL, and 11.7 ± 2.9 s, respectively. CONCLUSION: Semiautomated liver MR volumetry using hepatobiliary phase gadoxetic acid-enhanced MRI with the quadratic MR image division is a reliable, easy, and fast tool to measure liver volume in potential living liver donors.

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BACKGROUND: In liver surgery, appropriate preoperative evaluation and preparation of the patient is of cardinal importance. The up-to-date, preoperative prediction of residual liver function has thus far been limited. As post-hepatectomy liver failure is a major cause of mortality, a new and simple bedside test (LiMAx) has been developed to predict postoperative liver function in conjunction with preoperative volumetric analysis of the liver. CASE PRESENTATION: A 45-year-old patient presented with a cecal carcinoma and a large synchronous liver metastasis for major liver surgery. Liver function was determined by the LiMAx-test for the enzymatic capacity of cytochrome P450 1A2, which is ubiquitously and solely active in the liver. A solution of 2 mg/kg body weight (13)C-labeled methacetin was injected as a bolus into an intravenous catheter and, thereafter, was metabolized into acetaminophen and (13)CO2 and pulmonarily exhaled. The analysis of the (13)CO2/(12)CO2 ratio was performed using online breath sampling over a period of maximally 60 minutes. Based on this test, a value of more than 315 µg/kg/h represents normal liver function. A laparoscopic right hemihepatectomy was planned during virtual resection with a residual liver volume of 48% and a preoperative anticipated residual LiMAx of 301 µg/kg/h. After successful resection, the initial postoperative LiMAx value was 316 µg/kg/h, indicating good liver function and a correct prediction of the outcome. CONCLUSION: In the presented patient, residual liver function could be accurately predicted preoperatively using a combination of the new LiMax test with CT-volumetry. This test might significantly improve preoperative evaluation and postoperative outcomes in liver surgery.

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BACKGROUNDS/AIMS: The future liver remnant (FLR) is usually calculated as a ratio of the remnant liver volume (RLV) to the total functional liver volume (RLV/TFLV). In liver transplantation, it is generally accepted that the ratio of the graft volume to standard liver volume (SLV) needs to be at least 30% to 40% to fit the hepatic metabolic demands of the recipient. The aim of this study was to compare RLV/TFLV versus RLV/SLV as a predictor of postoperative liver function and liver failure. METHODS: CT volumetric measurements of RLV were obtained retrospectively in 74 patients who underwent right hemihepatectomy for a malignant tumor from January 2010 to May 2013. RLV and TFLV were obtained using CT volumetry, and SLV was calculated using Yu's formula: SLV (ml)=21.585×body weight (kg)(0.732)×height (cm)(0.225). The RLV/SLV ratio was compared with the RLV/TFLV as a predictor of postoperative hepatic function. RESULTS: Postheptectomy liver failure (PHLF), morbidity, and serum total bilirubin level at postoperative day 5 (POD 5) were increased significantly in the group with the RLV/SLV ≤30% compared with the group with the RLV/SLV >30% (p=0.002, p=0.004, and p<0.001, respectively). But RLV/TFLV was not correlated with PHLF and morbidity (p=1.000 and 0.798, respectively). RLV/SLV showed a stronger correlation with serum total bilirubin level than RLV/TFLV (RLV/SLV vs. RLV/TFLV, R=0.706 vs. 0.499, R(2)=0.499 vs. 0.239). CONCLUSIONS: RLV/SLV was more specific than RLV/TFLV in predicting the postoperative course after right hemihepatectomy. To determine the safe limit of hepatic resection, a larger-scaled prospective study is needed.