Interobserver variability in the preoperative assessment of future liver remnant function using hepatobiliary scintigraphy

Interobserver variability in the preoperative assessment of future liver remnant function using hepatobiliary scintigraphy | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Interobserver variability in the preoperative assessment of future liver remnant function using hepatobiliary scintigraphy Kirsten de Vries, Jelmer E. Oor, Suomi M.G. Fouraschen, Marieke T. de Boer, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5865429/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 12 Jun, 2025 Read the published version in EJNMMI Research → Version 1 posted 5 You are reading this latest preprint version Abstract Background Post-hepatectomy liver failure (PHLF) is a serious complication following hepatic resection and associated with a high mortality rate. The risk of PHLF can be estimated pre-resection by assessing the function of the future liver remnant (FLR) using hepatobiliary scintigraphy (HBS). Inaccurate estimation can have profound consequences, including an incorrect decision whether or not to proceed with hepatic resection. Therefore, it is essential to determine the reproducibility of preoperative assessment of the FLR function using HBS. The interobserver variability in the assessments of FLR function between two independent observers, blinded for each other’s results, was evaluated. Results In 24 out of 50 patients, the FLR function was predicted to be sufficient (> 2.69%/min/m 2 ) to proceed with hepatic resection without preoperative FLR hypertrophy-inducing measures. In contrast, six patients were first subjected to portal vein embolization based on a predicted insufficient FLR function, which subsequently resulted in resection in four patients. Comparing the FLR function analyses of both observers, Bland-Altman plots demonstrated that most assessments lie within the 95% confidence interval and no pattern suggesting bias was observed. The interobserver level of agreement therefore appeared high for the FLR function (ICC = 0.996, Spearman’s ρ = 0.995 and Cohen’s κ = 0.948). Conclusions This study shows a high interobserver agreement and a negligible interobserver variability in the assessment of FLR function using HBS, regardless of the extent of observer experience. Therefore, the preoperative assessment of the FLR function is reproducible in the workup for patients planned to undergo (major) hepatic resections. Future Liver Remnant function hepatobiliary scintigraphy interobserver variability post-hepatectomy liver failure Figures Figure 1 Figure 2 Figure 3 Figure 4 Background Post-hepatectomy liver failure (PHLF) is a serious complication following major hepatic resection and an important cause of postoperative mortality. The definition and incidence of PHLF after major hepatic resection vary between study series. Incidences were reported up to 20% and mortality rates up to 10% for patients with primary hepatobiliary tumors, including hepatocellular carcinoma (HCC) and cholangiocarcinoma. Even higher mortality rates have been documented for patients subjected to resection of four or more liver segments, with mortality rates up to 30%. Furthermore, in 45% of cases, non-lethal but life-threatening complications potentially related to insufficient liver function are observed, including sepsis and cardiopulmonary events [ 1 , 2 ]. Prevention of PHLF is therefore of vital essence. The risk of developing PHLF after hepatic resection can be estimated by preoperative assessment of the future liver remnant (FLR) function. Until recent, techniques for qualitative assessment of liver function were unavailable, and FLR volume was determined as a quantitative surrogate marker for FLR function. In this setting, a minimum FLR volume of 30% of the standardized total liver volume is deemed sufficient to undergo hepatic resection. However, in patients diagnosed with underlying parenchymal hepatic disorders (i.e. profound steatosis, fibrosis, cirrhosis or drug-induced liver damage), FLR volume alone is an inadequate technique to determine the risk of PHLF [ 2 ]. Furthermore, the need for as well as the effect of FLR hypertrophy-inducing techniques, including portal vein embolization (PVE) with or without hepatic vein embolization (HVE) and ALPPS (Associating Liver Partition and Portal vein Ligation for Staged hepatectomy), should be objectively determined [ 3 – 5 ]. With hepatobiliary scintigraphy (HBS) in addition to the abovementioned FLR volume, FLR function can be determined in a more qualitative way and is based on the 99m Technetium (Tc)-mebrofenin uptake in the FLR as a percentage of the uptake in the whole liver. Nowadays, an FLR function (corrected for BSA) of 2.69%/min/m 2 is increasingly used as a cutoff value to aid preoperative decision-making whether or not to proceed with hepatic resection, and was first described by De Graaf et al. [ 6 ]. In general, an FLR function above this cutoff value is considered sufficient to proceed with hepatic resection without the need for preoperative FLR hypertrophy-inducing techniques, although there is no guarantee of an absent risk of PHLF development. Contrary, an FLR function below this cutoff value is considered to indicate a significantly increased risk of PHLF development [ 2 , 6 ]. In these patients, PVE is advised as a first step to increase FLR function, as this is the least invasive technique to induce FLR hypertrophy. Following PVE, FLR volume and function may conceivably increase after which hepatic resection can be reconsidered [ 7 ]. Upon the introduction of HBS and (if indicated) subsequent PVE, a decrease in the incidence of PHLF and postoperative mortality has been reported [ 8 ]. However, inaccurate estimation of the FLR function can have profound consequences, including the decision whether or not a patient can undergo hepatic resection. Currently, research on determinants influencing the analysis of preoperative HBS is still lacking. Therefore, the aim of the present study is to assess the reproducibility of the preoperative subjective assessment of FLR function using HBS in predicting the risk of PHLF. Methods In this reproducibility study, the interobserver variability in the preoperative assessment of the FLR function using HBS was evaluated. Two independent observers assessed the FLR function: an experienced Nuclear Medicine (NM) physician (observer A) and a Technical Medicine (TM) trainee (observer B). Observer B was trained by observer A only on how to retrieve FLR function using the data analysis program as described below. Separately, observer B was trained by an experienced liver surgeon on segmental anatomy of the liver and how to define distinct segments on CT imaging. FLR function was assessed by observer A at the time of the clinical workflow for each specific patient. Observer B reassessed the FLR function, blinded to the results of observer A. Subjects and materials Fifty patients who were referred for assessment of their FLR function prior to major hepatic resection and consequently underwent HBS at the University Medical Center Groningen (UMCG) between May 2020 and November 2022 were included in this study. All included subjects were diagnosed with either primary or secondary hepatobiliary malignancies or were potential candidates for living liver donation. An overview of the inclusion criteria is shown in Table 1 . Table 1 Overview of inclusion criteria Inclusion criteria Primary or secondary hepatobiliary malignancies or Potential donor for living liver donation Age 18 years or older Patients with normal anatomy of future liver remnant segments Availability of a low dose computed tomography (LDCT) as well as dynamic submodality and attenuation corrected (AC) HBS To keep analysis straightforward, patients requiring FLR assessment of atypical or difficult to define liver segments were excluded. Furthermore, patients in whom technical problems during HBS occurred, were also excluded from analysis, for instance in case of missing (dynamic) submodalities or a mismatch between Single Photon Emission Computed Tomography (SPECT) and Computed Tomography (CT) imaging. Also, HBS assessed by NM physicians other than observer A were excluded. Ethical approval was obtained by the Institutional Review Board of the University Medical Center Groningen. The HBS was acquired with a SPECT system: Symbia Intevo Bold SPECT system, (low-energy-high-resolution 180° collimator, 128 × 128, zoom 1.00) (Siemens Healthineers, Inc., Germany), using a previously published scanning protocol [ 8 ]. In short, patients were asked to fast for 4 hours prior to HBS to avoid undesirable gallbladder contractions at time of scanning. During acquisition, patients were placed in supine position on the imaging table. HBS was performed using intravenous infusion of approximately 200 MBq 99m Tc-mebrofenin. Directly after infusion, the first of two dynamic series was obtained to assess the hepatic uptake rate (38 frames, 10 seconds per frame). Secondly, a SPECT was acquired to determine the regional uptake (30 projections, 8 seconds per projection with a max. of 4 seconds to adjust the gamma-camera position) and a low-dose CT (LDCT) was performed for anatomical mapping and attenuation correction. Finally, the second dynamic series was obtained to assess the biliary excretion (20 frames, one minute per frame) [ 9 ]. Data collection and processing To process the acquired imaging data and analyze FLR function, the Hermes Hybrid Viewer PDR 6.1.3 software application was used (Hermes Medical Solutions, Inc, Sweden). For all included patients, screenshots of the Hermes tab were saved for future reference. Required clinical and biometric patient data were extracted from the UMCG electronic health record (EHR; Epic Systems Software, Verona, Wisconsin, USA). In the Hermes software application, the FLR function was assessed following the practical guidelines formulated by Arntz et al. [ 10 ]and Rassam et al.[ 11 ]. Briefly, regions-of-interest (ROI) were drawn and volumes-of-interests (VOI) were created using thresholding. The threshold represents the counts of gamma photons detected by the camera, generating isocontours that outline the entire liver volume and the FLR volume (i.e. the VOIs) based on this threshold. As a first step, the regions-of-interest (ROI) for the blood pool and liver were separately drawn on the planar images of the dynamic (2D) series. The ROI for the blood pool was manually drawn comprising the homogeneous uptake in the left ventricle of the heart. The ROI for the liver comprised the uptake of 99m Tc-mebrofenin in the entire liver. This ROI was semi-automatically determined by Hermes using thresholding, allowing the observer to adjust the amount of thresholding to comprise the entire liver. In case the observer was not satisfied with the automatically positioned ROI by Hermes, the ROI was edited manually. The ROIs for the liver and blood pool should not overlap. Drawing the ROI for the remnant liver on the planar images was skipped, because the FLR volume was determined subsequently through a VOI on the SPECT images. In the next step, the liver segments to be assessed were delineated by manually drawing image constraints in the axial and coronal plane of the SPECT-CT based on the information of the LDCT using the Couinaud classification [ 12 ]. A recent contrast-enhanced CT scan in the venous phase, if available, was consulted as a reference for identifying liver segments. Subsequently, the delineation of the liver volume by an isocontour was semi-automatically performed using an optimal threshold (determined through a trial-and-error process) and visual interpretation. For the delineation of the FLR volume, the same threshold was used. When stasis of uptake in the biliary ducts was visible, a masking VOI was applied. A step-by-step guide can be found in appendix A. Eventually, the FLR function (%/min/m 2 ) was computed after correction for body surface area (BSA) using the Mosteller formula (see Eq. 1) [ 9 , 11 ]. $$\:BSA\left({m}^{2}\right)=\sqrt{\frac{height\left(cm\right)\times\:weight\left(kg\right)}{3600}}$$ ( 1 ) Comparative data analysis between FLR functions obtained by observer A and observer B was performed using Microsoft Excel (Microsoft Corporation, Washington, USA, version 2023). Patient characteristics and treatment-related data were collected in the study database. Clinical complications were registered according to the Clavien-Dindo classification [ 13 ]. Major complications were defined as grade ≥ III. Statistical analysis All statistical analyses were performed using IBM SPSS Statistics 28.0 (IBM Corporation, New York, USA). The Shapiro-Wilk test was used to assess whether the data followed a normal distribution. Based on the outcome of the Shapiro-Wilk test, either a parametric or non-parametric test was performed for the paired data to evaluate whether there were significant differences between the assessment of observer A and observer B. The interobserver variability was first assessed by a visualization of the agreement using a Bland-Altman plot. With the one-sample t-test it was evaluated if there was a significant bias between the measurements of observer A and observer B. The one-sample t-test additionally provided the mean difference between the assessments of observer A and observer B and the standard deviation (SD) of the mean difference. With these values, the 95% confidence intervals (CI) were calculated, which were incorporated in the Bland-Altman plot. After conducting the Bland-Altman analysis, linear regression was applied to examine whether there was proportional bias. The interobserver agreement in the FLR function was quantified by three parameters: the Intraclass Correlation Coefficient (ICC), the Spearman Correlation coefficient (Spearman’s ρ) and the Cohen’s kappa (κ). For the computed parameters, p -values were also obtained. For all statistical tests and the computed parameters, a 2-tailed p -value < 0.05 was considered statistically significant. Results Subjects Between May 2020 and November 2022, in total 60 patients underwent HBS in the UMCG. Ten patients were excluded from the study population because they did not meet the inclusion criteria and/or had inadequate imaging (Fig. 1 ). For the included subjects, indications for hepatic resection were: Primary hepatobiliary malignancies (n = 40), including: HCC (n = 14), cholangiocarcinoma (n = 23), neuroendocrine tumors (NET) (n = 2) and gallbladder carcinoma (n = 1) Secondary hepatobiliary malignancies (n = 8), including: colorectal liver metastases (CRLM) (n = 7) and non-colorectal liver metastases (n = 1) Living liver donation (n = 2) A total of 41 patients were screened for (extended) right hemihepatectomy, six patients for (extended) left hemihepatectomy and one patient for posterior resection (segment 6 and 7). Two subjects were potential candidates for living liver donation. A recent contrast-enhanced CT scan in the venous phase was available for 92% of the patients (n = 46). Patient characteristics are presented in table 2. [INSERT Table 2 HERE] Table 2: Overview of patient characteristics ; Unless otherwise specified, data are shown as number and percentages. Number of patients Males Females Total n = 50 a 32 (64%) 18 (36%) Age (in years) b 63 (13) [25 – 82] Weight (kg) b 75 (14.5) Height (cm) b 174.5 (9.6) Body Surface Area (m 2 ) b 1.91 (0.2) Indications Hepatocellular carcinoma Cholangiocarcinoma Neuro-endocrine tumor Gallbladder carcinoma Colorectal liver metastases Non-colorectal liver metastases Living liver donation Total n = 50 14 (28) 23 (46) 2 (4) 1 (2) 7 (14) 1 (2) 2 (4) Proposed hepatic resection (extended) right hemihepatectomy (extended) left hemihepatectomy Posterior resection Segment resection Total n = 50 41 (82) 6 (12) 1 (2) 2 (4) Future liver remnant assessment questions Segments 2-3 (s2-3) Segments 2-4 (s2-4) Segments 1-3 (s1-3) Segments 1-4 (s1-4) Segments 4-8 (s4-8) Segments 5-8 (s5-8) Segments 1, 4-8 (s1,4-8) Segments 1, 5-8 (s1, 5-8) Segments 6-7 (s6-7) Total n = 77 c 24 (31) 28 (36) 2 (3) 14 (18) 1 (1) 4 (5) 2 (3) 1 (1) 1 (1) a Of 23 patients, weight and/or height was not known in Hermes. Weight and/or height is for these patients manually retrieved from notes in the electronic health record. b Data are shown as mean with standard deviation in parentheses. c Because a maximum of two assessments per patient is included, this resulted in a total of 77 assessments in the current study After FLR function assessment, 24 patients underwent hepatic resection without preoperative FLR-hypertrophy inducing measures. Eight patients first underwent PVE, of which four patients subsequently underwent hepatic resection. In four patients no adequate increase in FLR function was achieved, despite PVE. After hepatic resection, six patients (21.4%) developed major complications, including bile leakage (n = 5) and sepsis (n = 1, caused by infected fluid collections, in the presence of pancreatic leakage). None of the patients that underwent resection developed PHLF and 90-day mortality was 3.6% (n = 1 patient died from septic shock caused by infected fluid collections, in the presence of pancreatic leakage). Six patients received selective internal radiation therapy (SIRT) instead of hepatic resection due to insufficient FLR function (n = 4) or because they were considered unfit for surgery (n = 2; n = 1 poor underlying parenchyma quality and n = 1 poor physical condition with extensive history), of whom one patient developed liver failure after SIRT. Sixteen patients did not undergo hepatic resection or SIRT due to insufficient FLR function (n = 3), insufficient growth of FLR after PVE (n = 4), disease progression (n = 5), irresectable liver tumors (n = 2) or a diagnosis of benign disease (n = 2). An overview of the actions taken and corresponding number of patients based on the result of the HBS analysis is provided in Fig. 2 . Data and statistical analysis The FLR function (corrected for BSA) assessed by observer A and observer B for all included patients is demonstrated in Fig. 3 . Overall, there was no significant difference in the assessment of FLR function between both observers (Z = -0.692, p = 0.489; data was not normally distributed: W = 0.945, p = 0.002 for observer A and W = 0.949, p = 0.004 for observer B). Overall, observer A reported a mean FLR function of 3.01 ± 1.39 and observer B of 3.00 ± 1.38. Among patients with an adequate FLR function, observer A reported a mean FLR function of 4.07 ± 1.13, while observer B reported 4.06 ± 1.10. For the patients with an insufficient FLR function, the mean FLR function assessed by observer A was 1.92 ± 0.50 and by observer B was 1.91 ± 0.51. Additional statistics per FLR segment assessment can be found in appendix B. No significant bias was found between the observers (M = 0.0123, SD = 0.11829; t(76) = 0.915 and p = 0.363). Furthermore, linear regression analysis confirmed the absence of proportional bias (B = 0.010, p = 0.306). The Bland-Altman plot is presented in Fig. 4 , demonstrating that the majority of the assessments lie within the 95% CI with no clear pattern. The two outliers indicate that only these two assessments of the FLR function differ significantly between the observers. The interobserver agreement in the FLR function is reported in Table 3 . Table 3 The interobserver agreement in the FLR function. Quantification by three parameters: Intraclass Correlation Coefficient (ICC), Spearman's ρ and Cohen's κ and their corresponding p-value. CI = Confidence Interval Parameter Interobserver agreement p -value ICC 0.996 (95% CI: 0.994–0.998) < 0.001 Spearman’s ρ 0.995 < 0.001 Cohen’s κ 0.948 < 0.001 All three parameters were high (close to 1) and the corresponding p -values were statistically significant. For Cohen’s κ, the assessments of the FLR functions were divided into two categories: assessments with a value > 2.69%/min/m 2 resulting in approval for hepatic resection and assessments with a value ≤ 2.69%/min/m 2 resulting in disapproval for hepatic resection. When the cutoff value of 2.69%/min/m 2 was applied, two assessments did not correspond between both observers, where observer B assessed a FLR function higher than 2.69%/min/m 2 and observer A lower than 2.69%/min/m 2 . Discussion The aim of the current study was to assess the reproducibility of the preoperative assessment of the FLR function using HBS. The interobserver variability and agreement was therefore evaluated. The interobserver agreement in the FLR function assessed by observer A and observer B was high and the interobserver variability was negligible. Therefore, the preoperative assessment of the FLR function appears to be reproducible. The accuracy of risk assessment for postoperative morbidity, liver failure and mortality was previously assessed by Dinant et al. [ 14 ], who also reported an acceptable level of agreement (93% of values within the 95% CI) between two observers in the uptake measurement of the FLR considering planar analysis (dynamic 2D imaging analysis of the 99m Tc-mebrofenin uptake). However, to date, no studies have been published that analyze to what extent the FLR function may differ between observers when SPECT-CT imaging is included. Only a small number of outliers were observed for the FLR function (n = 2), indicating that these assessments differed significantly between the observers. Nevertheless, the differences between the assessments by observer A and observer B for these outliers have no clinical impact, since both assessments are above the cutoff value of 2.69%/min/m 2 (5.92 vs 5.08 and 3.37 vs 3.67). Based on both assessments, the conclusion for these patients is consistent: the FLR function is sufficient to proceed with major hepatic resection. Variations in the FLR function can be introduced by differences in height and weight and hence BSA. Since the normalized FLR function is quite sensitive to differences in BSA, accurate BSA estimation at the time of HBS is essential. Even small deviations in height and weight, for example 2 cm and 2 kg, can cause the FLR function to vary by 0.12%/min/m 2 for the same patient. This effect is particularly relevant when the FLR function approaches the cutoff value of 2.69%/min/m 2 , which may result in misinterpretation of the FLR function. Another factor possibly influencing the FLR function is the way the ROI for the blood pool and liver is drawn. The ROI for the liver should comprise the uptake of 99m Tc-mebrofenin in the entire liver, while the left ventricular blood pool serves as a reference region for the ROI for the blood pool. Both ROIs should not overlap. These two steps are, however, carried out manually and are therefore susceptible to subjectivity. In addition, it is relevant that the VOI of the liver is representative for the volume of the liver. However, the selection of the threshold is based on the interpretation of the observer and can vary between the subjects, since the rates of uptake and excretion of 99m Tc-mebrofenin may differ. There can be a notable variability in the selection of the absolute threshold, resulting in variation in the VOI of the liver and consequently affecting the FLR function. Furthermore, the decision to correct for the uptake in the bile ducts could also introduce variations in the FLR function. Nevertheless, the extent to which these steps affect the FLR function and whether it can result in significant differences have to be determined in future research. Moreover, the FLR is manually delineated on the LDCT. While segment 2–3 are generally identifiable on the LDCT, the remaining segments can be more difficult to identify. Therefore, it is essential that the observer has good knowledge of the liver anatomy and has access to anatomical imaging, preferably in the venous phase. The liver can be divided into segments based on the course of the left, middle and right hepatic vein, as well as the left and right portal vein. If a contrast-enhanced CT prior to the HBS is available, it can aid in identifying the liver segments. However, the delineation of the segments on the LDCT remains an estimation. Additionally, it is not possible to establish the boundaries of the remnant liver with millimeter precision. When the liver is imaged at 140 keV and at 10 cm (typical organ depth [ 15 ]) relative to the detector, the resolution of the image is specified to be 7.5 mm (Full Width at Half Maximum) [ 16 ]. This implies that the boundaries of the remnant liver can be delineated with an accuracy of 7.5 mm. In summary, the assessment of the FLR function remains partly subjective. What level of variation in the assessment of FLR function between observers can be regarded acceptable, remains the question. However, differences in FLR function assessed by various observers are of no major concern when the assessments are not approaching the cutoff value of 2.69%/min/m 2 . Discrepancies between observers are clinically irrelevant when both assessments are either above or below the cutoff value, since the decision of insufficient FLR will be the same. In the current study, the assessments of two patients show conflicting outcomes between observers. Observer B assessed a FLR function above the cutoff value and thereby allowing hepatic resection, while observer A assessed a FLR function below the cutoff value. Both assessments are indeed very close to the cutoff value (2.67 and 2.63 for observer A and 2.74 and 2.70 for observer B), however these differences were no outliers and thus not significantly different. The decision to proceed with hepatic resection in these cases should be carefully considered, perhaps consulting multiple observers and/or a multidisciplinary team to aid in the decision-making process. Furthermore, FLR volume may provide additional guidance in such cases, as FLR volumes above 30% are considered sufficient to proceed with hepatic resection in healthy liver tissue [ 6 ]. When the assessments are inconclusive, PVE needs to be considered. It should be noted that observer A, an expert in the field of HBS analyses, trained observer B on how to use Hermes for retrieval of FLR function. Observer A was trained exactly the same way in the use of Hermes for the retrieval of FLR function by the group of Bennink et al. [ 6 ] from the Amsterdam University Medical Center. As stated before, the delineation of the liver segments is an observer depending part of FLR function assessment. Considering the results of observer B are comparable to the results of observer A, a potential bias caused by the training component cannot be excluded. To keep this risk of potential bias as low as possible, observer B was separately trained by an experienced liver surgeon on segmental anatomy of the liver and how to delineate the distinct segments on the imaging. Furthermore, observer B individually assessed the FLR function while being blinded to the results of observer A. Considering the postoperative course and outcome of the patients who underwent hepatic resection, the widely used cutoff value of 2.69%/min/m 2 appears effective in preventing PHLF. Perhaps a more lenient cutoff value could be used, thereby allowing more patients to be eligible for hepatic resection. Dinant et al. [ 14 ] revealed that when applying a cutoff value of 2.5%/min/m 2 approximately 3% of patients have a risk of developing PHLF, based on receiver operating characteristic (ROC) analysis. Chapelle et al. [ 3 ] suggested an even lower cutoff value of 2.3%/min/m 2 , which would prevent almost all PHLF incidences and all mortalities due to PHLF. On the contrary, Olthof et al. [ 17 ] suggested to use a cutoff value of 8.5%/min for the absolute FLR function (not corrected for BSA) in patients with (suspected) perihilar cholangiocarcinoma. It could very well be that different indications for major liver resection also require different cutoff values. In the current study, of the 28 patients who actually underwent hepatic resection, six patients (21.4%) developed complications after hepatic resection but none developed PHLF. Of these eight patients, three were diagnosed with HCC and five with cholangiocarcinoma. Two patients with cholangiocarcinoma died, one due to septic shock (caused by infected fluid collections, in the presence of pancreatic leakage) after hepatic resection. Based on this outcome, one could indeed argue for a stricter cutoff value for livers affected by cholangiocarcinoma compared to HCC. However, this is based on a very small sample size and one has to take into account that the outcome of surgical treatment of cholangiocarcinoma is influenced by far more variables than FLR function alone. Further investigation to determine the most optimal cutoff value involving ROC analysis is therefore necessary. A limitation of the current study is that the observers did not re-assess their own FLR function analyses, allowing a more complete assessment of the reproducibility by also quantifying the intra-observer agreement. A future recommendation is to conduct a study involving multiple NM physicians and trainees across the country to assess and re-assess the FLR function, providing a more comprehensive and diverse perspective on the subjective assessment of the FLR function. Additionally, the effects of various factors potentially influencing FLR function assessment, including thresholding and biliary duct corrections, and whether these effects result in significant differences in the assessments, should be investigated. Finally, to reach a higher statistical power, future studies should include a larger number of patients. More observers as well as more patients will provide a more reliable representation of the subjective FLR function assessment and thereby enhance the generalizability of the findings. Conclusions In conclusion, the FLR function assessment using HBS appears to be a reproducible tool in the decision-making whether or not to proceed with hepatic resection, showing low interobserver variability. The preoperative assessment of FLR function can be easily learned by a trainee, though thorough knowledge of segmental anatomy of the liver is required. Variations in FLR function assessments can occur due to different interpretations of the observers. Nevertheless, the assessment of the FLR function is safe to employ and justified based on this single center evaluation. Abbreviations ALPPS Associating Liver Partition and Portal vein ligation for Staged hepatectomy BSA Body Surface Area CI Confidence Interval CRLM Colorectal Liver Metastases CT Computed Tomography EHR Electronic Health Record FLR Future Liver Remnant HBS Hepatobiliary Scintigraphy HCC Hepatocellular Carcinoma HVE Hepatic Vein Embolization ICC Intraclass Correlation Coefficient LDCT Low-Dose Computed Tomography NET Neuroendocrine Tumor NM Nuclear Medicine PHLF Post-hepatectomy Liver Failure PVE Portal Vein Embolization ROC Receiver Operating Characteristic ROI Region-of-Interest SD Standard Deviation SPECT Single Photon Emission Computed Tomography Tc Technetium TM Technical Medicine UMCG University Medical Center Groningen VOI Volume-of-Interest Declarations Ethics approval and consent to participate Ethical approval was obtained by the Institutional Review Board of the University Medical Center Groningen (reference number: 20842). Consent for publication Not applicable Availability of data and material The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding None Authors' contributions KdV: Conceptualization; Data curation; Formal analysis; Methodology; Writing - original draft; JO: Conceptualization; Methodology; Validation; Supervision; Writing – review & editing. SF: Conceptualization; Methodology; Writing – review & editing. MdB: Conceptualization; Methodology; Writing – review & editing. MN: Conceptualization; Methodology; Writing – review & editing. EGJ: Conceptualization; Methodology; Supervision; Writing – review & editing. GS: Data curation; Formal analysis; Methodology; Writing – review & editing. SR: Conceptualization; Data curation; Formal analysis; Methodology; Validation; Supervision; Writing – review & editing. All authors read and approved the final manuscript. Acknowledgements None Authors' information 1 Technical Medicine, University of Twente, Drienerlolaan 5, 7522 NB Enschede, The Netherlands 2 Department of Hepato-pancreato-biliary Surgery and Liver Transplantation, University Medical Center Groningen, Hanzeplein 1, 9713 GZ Groningen, The Netherlands 3 Department of Surgical Oncology, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands 4 Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, Hanzeplein 1, 9713 GZ Groningen, The Netherlands 5 Multi-Modality Medical Imaging (M3I) Group, TechMed Centre , University of Twente, Drienerlolaan 5, 7522 NB Enschede, The Netherlands References Søreide JA, Deshpande R. Post hepatectomy liver failure (PHLF) – Recent advances in prevention and clinical management. Eur J Surg Oncol 2021;47:216–24. https://doi.org/10.1016/J.EJSO.2020.09.001. 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Effect of structured use of preoperative portal vein embolization on outcomes after liver resection of perihilar cholangiocarcinoma. Br J Surg Open 2020;4:449–55. https://doi.org/10.1002/BJS5.50273. de Graaf W, van Lienden KP, Dinant S, Roelofs JJTH, Busch ORC, Gouma DJ, et al. Assessment of future remnant liver function using hepatobiliary scintigraphy in patients undergoing major liver resection. J Gastrointest Surg 2010;14:369–78. https://doi.org/10.1007/s11605-009-1085-2. Van Lienden KP, Van Den Esschert JW, De Graaf W, Bipat S, Lameris JS, Van Gulik TM, et al. Portal vein embolization before liver resection: A systematic review. Cardiovasc Intervent Radiol 2013;36:25–34. https://doi.org/10.1007/s00270-012-0440-y. Cieslak KP, Bennink RJ, de Graaf W, van Lienden KP, Besselink MG, Busch ORC, et al. Measurement of liver function using hepatobiliary scintigraphy improves risk assessment in patients undergoing major liver resection. HPB 2016;18:773–80. https://doi.org/10.1016/j.hpb.2016.06.006. Gupta M, Choudhury PS, Singh S, Hazarika D. Liver Functional Volumetry by Tc-99m Mebrofenin Hepatobiliary Scintigraphy before Major Liver Resection: A Game Changer. Indian J Nucl Med 2018;33:283. https://doi.org/10.4103/IJNM.IJNM_72_18. Arntz PJW, Deroose CM, Marcus C, Sturesson C, Panaro F, Erdmann J, et al. Joint EANM/SNMMI/IHPBA procedure guideline for [99mTc]Tc-mebrofenin hepatobiliary scintigraphy SPECT/CT in the quantitative assessment of the future liver remnant function. HPB 2023;25:1131–44. https://doi.org/10.1016/J.HPB.2023.06.001. Rassam F, Olthof PB, Richardson H, Van Gulik TM, Bennink RJ. Practical guidelines for the use of technetium-99m mebrofenin hepatobiliary scintigraphy in the quantitative assessment of liver function. Nucl Med Commun 2019;40:297–307. https://doi.org/10.1097/MNM.0000000000000973. Abdel-Misih SRZ, Bloomston M. Liver Anatomy. Surg Clin North Am 2010;90:653. https://doi.org/10.1016/J.SUC.2010.04.017. Dindo D, Demartines N, Clavien PA. Classification of surgical complications: A new proposal with evaluation in a cohort of 6336 patients and results of a survey. Ann Surg 2004;240:205–13. https://doi.org/10.1097/01.SLA.0000133083.54934.AE. Dinant S, De Graaf W, Verwer BJ, Bennink RJ, Van Lienden KP, Gouma DJ, et al. Risk Assessment of Posthepatectomy Liver Failure Using Hepatobiliary Scintigraphy and CT Volumetry. J Nucl Med 2007;48:685–92. https://doi.org/10.2967/JNUMED.106.038430. Sorenson JA, Phelps ME. The Anger Camera: Performance Characteristics. Phys. Nucl. Med. 2nd ed., W.B. Saunders Company; 1987, p. 331–45. Bui MHH, Robert A, Badel J-N, Kvassheim M, Stokke C, Rit S, et al. Validation of a model of the Symbia Intevo Bold SPECT scanner for Monte Carlo simulations. Nucl. Sci. Symp. Med. Imaging Conf. (IEEE NSS MIC), Vancouver, Canada: 2023. Olthof PB, Coelen RJS, Bennink RJ, Heger M, Lam MF, Besselink MG, et al. 99mTc-mebrofenin hepatobiliary scintigraphy predicts liver failure following major liver resection for perihilar cholangiocarcinoma. HPB 2017;19:850–8. https://doi.org/10.1016/j.hpb.2017.05.007. Supplementary Files AppendixAJan202025.docx AppendixBIOVHBSrevision20250317.docx Cite Share Download PDF Status: Published Journal Publication published 12 Jun, 2025 Read the published version in EJNMMI Research → Version 1 posted Editorial decision: Accept 14 May, 2025 Reviewers agreed at journal 04 Apr, 2025 Reviewers invited by journal 31 Mar, 2025 Editor assigned by journal 31 Mar, 2025 First submitted to journal 28 Mar, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5865429","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":436437545,"identity":"20c8cbb8-81c9-4021-9fbe-c2b38d252907","order_by":0,"name":"Kirsten de Vries","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABKElEQVRIie2RMUvEMBSAcwTSpYfrK2cP/AcHgXLgn7HLuaR7h0MKB3XRO8frv+h0qynBnEPBtYOLFG4QhEJBHMpxiQ46NKKbSL4heeHlI+/lIWSx/EEAf+yDRC1cncdHzoLrxPG3Cv9UptS7kmc64RoV9EVRxGFesYmOjIp3OazbJn70VxA98aYDrbTP1XzqIkfc5T3KCDsB8HJHs/X5pMhSoFn5sjllUhXmzmZVjzLGhKAiFWFeSiSGCfjLbbShjCgF3MCg4KbYi/BWK10Hg4SzHWV7szLCBEGRqFecFAlE4OTmnuE6Ss2KtyAESinoepui4lr1oj45wNESXGLoBR4kbuK58FcLVeFbd6FHWbfsVQdC9im9kPdpkZ9e1+DmN7ctFovl33MAdbxrDSBoBXMAAAAASUVORK5CYII=","orcid":"https://orcid.org/0009-0001-1815-648X","institution":"University of Twente Technical Medical Centre: Universiteit Twente Technical Medical Centre","correspondingAuthor":true,"prefix":"","firstName":"Kirsten","middleName":"","lastName":"de Vries","suffix":""},{"id":436437546,"identity":"f52671e3-1575-4ae5-aa46-66486bbb9811","order_by":1,"name":"Jelmer E. Oor","email":"","orcid":"","institution":"University Medical Centre Utrecht: Universitair Medisch Centrum Utrecht","correspondingAuthor":false,"prefix":"","firstName":"Jelmer","middleName":"E.","lastName":"Oor","suffix":""},{"id":436437547,"identity":"c78eb52b-cba7-490c-af81-5b6ec6ddef96","order_by":2,"name":"Suomi M.G. Fouraschen","email":"","orcid":"","institution":"University Medical Centre Groningen: Universitair Medisch Centrum Groningen","correspondingAuthor":false,"prefix":"","firstName":"Suomi","middleName":"M.G.","lastName":"Fouraschen","suffix":""},{"id":436437548,"identity":"999630e7-fa25-4e2b-a96f-c13268ce4f85","order_by":3,"name":"Marieke T. de Boer","email":"","orcid":"","institution":"University Medical Centre Groningen: Universitair Medisch Centrum Groningen","correspondingAuthor":false,"prefix":"","firstName":"Marieke","middleName":"T.","lastName":"de Boer","suffix":""},{"id":436437549,"identity":"005e845d-29c6-4837-89b1-0a8de0583097","order_by":4,"name":"Maarten W. Nijkamp","email":"","orcid":"","institution":"University Medical Centre Groningen: Universitair Medisch Centrum Groningen","correspondingAuthor":false,"prefix":"","firstName":"Maarten","middleName":"W.","lastName":"Nijkamp","suffix":""},{"id":436437550,"identity":"5bab0547-245d-48f3-af29-f6ba0558054f","order_by":5,"name":"Erik Groot Jebbink","email":"","orcid":"","institution":"University of Twente: Universiteit Twente","correspondingAuthor":false,"prefix":"","firstName":"Erik","middleName":"Groot","lastName":"Jebbink","suffix":""},{"id":436437551,"identity":"0833574b-ccc0-4f48-83a7-6d0a4d386d62","order_by":6,"name":"Gilles N. Stormezand","email":"","orcid":"","institution":"University Medical Centre Groningen: Universitair Medisch Centrum Groningen","correspondingAuthor":false,"prefix":"","firstName":"Gilles","middleName":"N.","lastName":"Stormezand","suffix":""},{"id":436437552,"identity":"c820d1ec-695a-49b0-9893-51fac5a09b00","order_by":7,"name":"Simeon J.S. Ruiter","email":"","orcid":"https://orcid.org/0000-0002-2298-689X","institution":"University Medical Centre Groningen: Universitair Medisch Centrum Groningen","correspondingAuthor":false,"prefix":"","firstName":"Simeon","middleName":"J.S.","lastName":"Ruiter","suffix":""}],"badges":[],"createdAt":"2025-01-20 11:23:37","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5865429/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5865429/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13550-025-01261-3","type":"published","date":"2025-06-12T15:57:39+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":79661734,"identity":"81b1a61a-4346-4d0b-9ce1-3ad0434fcc1d","added_by":"auto","created_at":"2025-04-01 09:46:05","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":689723,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of patient inclusion\u003c/p\u003e","description":"","filename":"Figure1Flowchart.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5865429/v1/fb53f496045122d275c31401.jpg"},{"id":79660706,"identity":"797ab05a-5e96-4edc-b6a5-3f414bcd1c52","added_by":"auto","created_at":"2025-04-01 09:38:05","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":594515,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of actions and corresponding number of patients based on HBS analysis\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5865429/v1/6b008df471457c8c957a6c9a.jpg"},{"id":79660707,"identity":"dfee7130-5c46-4b86-93a7-8c9934a2ae2c","added_by":"auto","created_at":"2025-04-01 09:38:05","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":324160,"visible":true,"origin":"","legend":"\u003cp\u003eOverview of the assessed FLR functions by observer A vs observer B\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5865429/v1/ae615ccd55ed8ae6e5ce5373.jpg"},{"id":79660704,"identity":"e7485f42-4f0c-45da-9676-3acaf18e8f43","added_by":"auto","created_at":"2025-04-01 09:38:05","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":418536,"visible":true,"origin":"","legend":"\u003cp\u003eBland-Altman plot of the FLR function\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5865429/v1/9b41bab3aebf27120727c536.jpg"},{"id":84726514,"identity":"d85c4910-6dd7-4bdc-be98-8355746ae669","added_by":"auto","created_at":"2025-06-16 16:06:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2681327,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5865429/v1/53ef15b3-2442-467f-ad6f-b9191e10a17b.pdf"},{"id":79660125,"identity":"9ad21e81-dc66-4ef0-ad84-af2f79cf7cf5","added_by":"auto","created_at":"2025-04-01 09:30:05","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":404937,"visible":true,"origin":"","legend":"","description":"","filename":"AppendixAJan202025.docx","url":"https://assets-eu.researchsquare.com/files/rs-5865429/v1/b02495d0ab6c0f26d40e7fa2.docx"},{"id":79660705,"identity":"d1679c64-ea8e-43ca-b615-f8b62eabec3d","added_by":"auto","created_at":"2025-04-01 09:38:05","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":27730,"visible":true,"origin":"","legend":"","description":"","filename":"AppendixBIOVHBSrevision20250317.docx","url":"https://assets-eu.researchsquare.com/files/rs-5865429/v1/2ec4ec61f48516910961a2bb.docx"}],"financialInterests":"","formattedTitle":"Interobserver variability in the preoperative assessment of future liver remnant function using hepatobiliary scintigraphy","fulltext":[{"header":"Background","content":"\u003cp\u003ePost-hepatectomy liver failure (PHLF) is a serious complication following major hepatic resection and an important cause of postoperative mortality. The definition and incidence of PHLF after major hepatic resection vary between study series. Incidences were reported up to 20% and mortality rates up to 10% for patients with primary hepatobiliary tumors, including hepatocellular carcinoma (HCC) and cholangiocarcinoma. Even higher mortality rates have been documented for patients subjected to resection of four or more liver segments, with mortality rates up to 30%. Furthermore, in 45% of cases, non-lethal but life-threatening complications potentially related to insufficient liver function are observed, including sepsis and cardiopulmonary events [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Prevention of PHLF is therefore of vital essence.\u003c/p\u003e \u003cp\u003eThe risk of developing PHLF after hepatic resection can be estimated by preoperative assessment of the future liver remnant (FLR) function. Until recent, techniques for qualitative assessment of liver function were unavailable, and FLR volume was determined as a quantitative surrogate marker for FLR function. In this setting, a minimum FLR volume of 30% of the standardized total liver volume is deemed sufficient to undergo hepatic resection. However, in patients diagnosed with underlying parenchymal hepatic disorders (i.e. profound steatosis, fibrosis, cirrhosis or drug-induced liver damage), FLR volume alone is an inadequate technique to determine the risk of PHLF [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Furthermore, the need for as well as the effect of FLR hypertrophy-inducing techniques, including portal vein embolization (PVE) with or without hepatic vein embolization (HVE) and ALPPS (Associating Liver Partition and Portal vein Ligation for Staged hepatectomy), should be objectively determined [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWith hepatobiliary scintigraphy (HBS) in addition to the abovementioned FLR volume, FLR function can be determined in a more qualitative way and is based on the \u003csup\u003e99m\u003c/sup\u003eTechnetium (Tc)-mebrofenin uptake in the FLR as a percentage of the uptake in the whole liver. Nowadays, an FLR function (corrected for BSA) of 2.69%/min/m\u003csup\u003e2\u003c/sup\u003e is increasingly used as a cutoff value to aid preoperative decision-making whether or not to proceed with hepatic resection, and was first described by De Graaf et al. [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In general, an FLR function above this cutoff value is considered sufficient to proceed with hepatic resection without the need for preoperative FLR hypertrophy-inducing techniques, although there is no guarantee of an absent risk of PHLF development. Contrary, an FLR function below this cutoff value is considered to indicate a significantly increased risk of PHLF development [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In these patients, PVE is advised as a first step to increase FLR function, as this is the least invasive technique to induce FLR hypertrophy. Following PVE, FLR volume and function may conceivably increase after which hepatic resection can be reconsidered [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eUpon the introduction of HBS and (if indicated) subsequent PVE, a decrease in the incidence of PHLF and postoperative mortality has been reported [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. However, inaccurate estimation of the FLR function can have profound consequences, including the decision whether or not a patient can undergo hepatic resection. Currently, research on determinants influencing the analysis of preoperative HBS is still lacking. Therefore, the aim of the present study is to assess the reproducibility of the preoperative subjective assessment of FLR function using HBS in predicting the risk of PHLF.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eIn this reproducibility study, the interobserver variability in the preoperative assessment of the FLR function using HBS was evaluated. Two independent observers assessed the FLR function: an experienced Nuclear Medicine (NM) physician (observer A) and a Technical Medicine (TM) trainee (observer B). Observer B was trained by observer A only on how to retrieve FLR function using the data analysis program as described below. Separately, observer B was trained by an experienced liver surgeon on segmental anatomy of the liver and how to define distinct segments on CT imaging. FLR function was assessed by observer A at the time of the clinical workflow for each specific patient. Observer B reassessed the FLR function, blinded to the results of observer A.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSubjects and materials\u003c/h2\u003e \u003cp\u003eFifty patients who were referred for assessment of their FLR function prior to major hepatic resection and consequently underwent HBS at the University Medical Center Groningen (UMCG) between May 2020 and November 2022 were included in this study. All included subjects were diagnosed with either primary or secondary hepatobiliary malignancies or were potential candidates for living liver donation. An overview of the inclusion criteria is shown in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOverview of inclusion criteria\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"1\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInclusion criteria\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary or secondary hepatobiliary malignancies or\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePotential donor for living liver donation\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge 18 years or older\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatients with normal anatomy of future liver remnant segments\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAvailability of a low dose computed tomography (LDCT) as well as dynamic submodality and attenuation corrected (AC) HBS\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTo keep analysis straightforward, patients requiring FLR assessment of atypical or difficult to define liver segments were excluded. Furthermore, patients in whom technical problems during HBS occurred, were also excluded from analysis, for instance in case of missing (dynamic) submodalities or a mismatch between Single Photon Emission Computed Tomography (SPECT) and Computed Tomography (CT) imaging. Also, HBS assessed by NM physicians other than observer A were excluded.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eEthical approval\u003c/strong\u003e \u003cp\u003e was obtained by the Institutional Review Board of the University Medical Center Groningen.\u003c/p\u003e \u003c/p\u003e \u003cp\u003eThe HBS was acquired with a SPECT system: Symbia Intevo Bold SPECT system, (low-energy-high-resolution 180\u0026deg; collimator, 128 \u0026times; 128, zoom 1.00) (Siemens Healthineers, Inc., Germany), using a previously published scanning protocol [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In short, patients were asked to fast for 4 hours prior to HBS to avoid undesirable gallbladder contractions at time of scanning. During acquisition, patients were placed in supine position on the imaging table. HBS was performed using intravenous infusion of approximately 200 MBq \u003csup\u003e99m\u003c/sup\u003eTc-mebrofenin. Directly after infusion, the first of two dynamic series was obtained to assess the hepatic uptake rate (38 frames, 10 seconds per frame). Secondly, a SPECT was acquired to determine the regional uptake (30 projections, 8 seconds per projection with a max. of 4 seconds to adjust the gamma-camera position) and a low-dose CT (LDCT) was performed for anatomical mapping and attenuation correction. Finally, the second dynamic series was obtained to assess the biliary excretion (20 frames, one minute per frame) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData collection and processing\u003c/h3\u003e\n\u003cp\u003eTo process the acquired imaging data and analyze FLR function, the Hermes Hybrid Viewer PDR 6.1.3 software application was used (Hermes Medical Solutions, Inc, Sweden). For all included patients, screenshots of the Hermes tab were saved for future reference. Required clinical and biometric patient data were extracted from the UMCG electronic health record (EHR; Epic Systems Software, Verona, Wisconsin, USA). In the Hermes software application, the FLR function was assessed following the practical guidelines formulated by Arntz et al. [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]and Rassam et al.[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Briefly, regions-of-interest (ROI) were drawn and volumes-of-interests (VOI) were created using thresholding. The threshold represents the counts of gamma photons detected by the camera, generating isocontours that outline the entire liver volume and the FLR volume (i.e. the VOIs) based on this threshold. As a first step, the regions-of-interest (ROI) for the blood pool and liver were separately drawn on the planar images of the dynamic (2D) series. The ROI for the blood pool was manually drawn comprising the homogeneous uptake in the left ventricle of the heart. The ROI for the liver comprised the uptake of \u003csup\u003e99m\u003c/sup\u003eTc-mebrofenin in the entire liver. This ROI was semi-automatically determined by Hermes using thresholding, allowing the observer to adjust the amount of thresholding to comprise the entire liver. In case the observer was not satisfied with the automatically positioned ROI by Hermes, the ROI was edited manually. The ROIs for the liver and blood pool should not overlap. Drawing the ROI for the remnant liver on the planar images was skipped, because the FLR volume was determined subsequently through a VOI on the SPECT images. In the next step, the liver segments to be assessed were delineated by manually drawing image constraints in the axial and coronal plane of the SPECT-CT based on the information of the LDCT using the Couinaud classification [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. A recent contrast-enhanced CT scan in the venous phase, if available, was consulted as a reference for identifying liver segments. Subsequently, the delineation of the liver volume by an isocontour was semi-automatically performed using an optimal threshold (determined through a trial-and-error process) and visual interpretation. For the delineation of the FLR volume, the same threshold was used. When stasis of uptake in the biliary ducts was visible, a masking VOI was applied. A step-by-step guide can be found in appendix A.\u003c/p\u003e \u003cp\u003eEventually, the FLR function (%/min/m\u003csup\u003e2\u003c/sup\u003e) was computed after correction for body surface area (BSA) using the Mosteller formula (see Eq.\u0026nbsp;1) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:BSA\\left({m}^{2}\\right)=\\sqrt{\\frac{height\\left(cm\\right)\\times\\:weight\\left(kg\\right)}{3600}}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\n\u003ch3\u003e( 1 )\u003c/h3\u003e\n\u003cp\u003eComparative data analysis between FLR functions obtained by observer A and observer B was performed using Microsoft Excel (Microsoft Corporation, Washington, USA, version 2023). Patient characteristics and treatment-related data were collected in the study database. Clinical complications were registered according to the Clavien-Dindo classification [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Major complications were defined as grade\u0026thinsp;\u0026ge;\u0026thinsp;III.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eAll statistical analyses were performed using IBM SPSS Statistics 28.0 (IBM Corporation, New York, USA). The Shapiro-Wilk test was used to assess whether the data followed a normal distribution. Based on the outcome of the Shapiro-Wilk test, either a parametric or non-parametric test was performed for the paired data to evaluate whether there were significant differences between the assessment of observer A and observer B. The interobserver variability was first assessed by a visualization of the agreement using a Bland-Altman plot. With the one-sample t-test it was evaluated if there was a significant bias between the measurements of observer A and observer B. The one-sample t-test additionally provided the mean difference between the assessments of observer A and observer B and the standard deviation (SD) of the mean difference. With these values, the 95% confidence intervals (CI) were calculated, which were incorporated in the Bland-Altman plot.\u003c/p\u003e \u003cp\u003eAfter conducting the Bland-Altman analysis, linear regression was applied to examine whether there was proportional bias. The interobserver agreement in the FLR function was quantified by three parameters: the Intraclass Correlation Coefficient (ICC), the Spearman Correlation coefficient (Spearman\u0026rsquo;s ρ) and the Cohen\u0026rsquo;s kappa (κ).\u003c/p\u003e \u003cp\u003eFor the computed parameters, \u003cem\u003ep\u003c/em\u003e-values were also obtained. For all statistical tests and the computed parameters, a 2-tailed \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSubjects\u003c/h2\u003e \u003cp\u003eBetween May 2020 and November 2022, in total 60 patients underwent HBS in the UMCG. Ten patients were excluded from the study population because they did not meet the inclusion criteria and/or had inadequate imaging (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFor the included subjects, indications for hepatic resection were:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003ePrimary hepatobiliary malignancies (n\u0026thinsp;=\u0026thinsp;40), including: HCC (n\u0026thinsp;=\u0026thinsp;14), cholangiocarcinoma (n\u0026thinsp;=\u0026thinsp;23), neuroendocrine tumors (NET) (n\u0026thinsp;=\u0026thinsp;2) and gallbladder carcinoma (n\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eSecondary hepatobiliary malignancies (n\u0026thinsp;=\u0026thinsp;8), including: colorectal liver metastases (CRLM) (n\u0026thinsp;=\u0026thinsp;7) and non-colorectal liver metastases (n\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eLiving liver donation (n\u0026thinsp;=\u0026thinsp;2)\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eA total of 41 patients were screened for (extended) right hemihepatectomy, six patients for (extended) left hemihepatectomy and one patient for posterior resection (segment 6 and 7). Two subjects were potential candidates for living liver donation. A recent contrast-enhanced CT scan in the venous phase was available for 92% of the patients (n\u0026thinsp;=\u0026thinsp;46). Patient characteristics are presented in table 2.\u003c/p\u003e \u003cp\u003e[INSERT Table\u0026nbsp;2 HERE]\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTable 2: Overview\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;of patient characteristics\u003c/strong\u003e; Unless otherwise specified, data are shown as number and percentages.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eNumber of patients\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eMales\u003c/p\u003e\n \u003cp\u003eFemales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eTotal n = 50\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e32 (64%)\u003c/p\u003e\n \u003cp\u003e18 (36%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eAge (in years)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003e63\u0026nbsp;(13) [25 \u0026ndash; 82]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eWeight (kg)\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003e75\u0026nbsp;(14.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eHeight (cm)\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003e174.5\u0026nbsp;(9.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eBody Surface Area (m\u003csup\u003e2\u003c/sup\u003e)\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003e1.91\u0026nbsp;(0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eIndications\u003c/p\u003e\n \u003cp\u003eHepatocellular carcinoma\u003c/p\u003e\n \u003cp\u003eCholangiocarcinoma\u003c/p\u003e\n \u003cp\u003eNeuro-endocrine tumor\u003c/p\u003e\n \u003cp\u003eGallbladder carcinoma\u003c/p\u003e\n \u003cp\u003eColorectal liver metastases\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eNon-colorectal liver metastases\u003c/p\u003e\n \u003cp\u003eLiving liver donation\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eTotal n = 50\u003c/p\u003e\n \u003cp\u003e14 (28)\u003c/p\u003e\n \u003cp\u003e23 (46)\u003c/p\u003e\n \u003cp\u003e2 (4)\u003c/p\u003e\n \u003cp\u003e1 (2)\u003c/p\u003e\n \u003cp\u003e7 (14)\u003c/p\u003e\n \u003cp\u003e1 (2)\u003c/p\u003e\n \u003cp\u003e2 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eProposed hepatic resection\u003c/p\u003e\n \u003cp\u003e(extended) right hemihepatectomy\u0026nbsp;\u003cbr\u003e\u0026nbsp;(extended) left hemihepatectomy\u003c/p\u003e\n \u003cp\u003ePosterior resection\u003c/p\u003e\n \u003cp\u003eSegment resection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eTotal n = 50\u003c/p\u003e\n \u003cp\u003e41 (82)\u003c/p\u003e\n \u003cp\u003e6 (12)\u003c/p\u003e\n \u003cp\u003e1 (2)\u003c/p\u003e\n \u003cp\u003e2 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eFuture liver remnant assessment questions\u003c/p\u003e\n \u003cp\u003eSegments 2-3 (s2-3)\u003c/p\u003e\n \u003cp\u003eSegments 2-4 (s2-4)\u003c/p\u003e\n \u003cp\u003eSegments 1-3 (s1-3)\u003c/p\u003e\n \u003cp\u003eSegments 1-4 (s1-4)\u003c/p\u003e\n \u003cp\u003eSegments 4-8 (s4-8)\u003c/p\u003e\n \u003cp\u003eSegments 5-8 (s5-8)\u003c/p\u003e\n \u003cp\u003eSegments 1, 4-8 (s1,4-8)\u003c/p\u003e\n \u003cp\u003eSegments 1, 5-8 (s1, 5-8)\u003c/p\u003e\n \u003cp\u003eSegments 6-7 (s6-7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eTotal n = 77\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e24 (31)\u003c/p\u003e\n \u003cp\u003e28 (36)\u003c/p\u003e\n \u003cp\u003e2 (3)\u003c/p\u003e\n \u003cp\u003e14 (18)\u003c/p\u003e\n \u003cp\u003e1 (1)\u003c/p\u003e\n \u003cp\u003e4 (5)\u003c/p\u003e\n \u003cp\u003e2 (3)\u003c/p\u003e\n \u003cp\u003e1 (1)\u003c/p\u003e\n \u003cp\u003e1 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003e Of 23 patients, weight and/or height was not known in Hermes. Weight and/or height is for these patients manually\u003c/p\u003e\n\u003cp\u003eretrieved from notes in the electronic health record.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eb\u003c/sup\u003e Data are shown as mean with standard deviation \u0026nbsp;in parentheses.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ec\u003c/sup\u003e Because a maximum of two assessments per patient is included, this resulted in a total of 77 assessments in the current study\u003c/p\u003e \u003cp\u003eAfter FLR function assessment, 24 patients underwent hepatic resection without preoperative FLR-hypertrophy inducing measures. Eight patients first underwent PVE, of which four patients subsequently underwent hepatic resection. In four patients no adequate increase in FLR function was achieved, despite PVE.\u003c/p\u003e \u003cp\u003eAfter hepatic resection, six patients (21.4%) developed major complications, including bile leakage (n\u0026thinsp;=\u0026thinsp;5) and sepsis (n\u0026thinsp;=\u0026thinsp;1, caused by infected fluid collections, in the presence of pancreatic leakage). None of the patients that underwent resection developed PHLF and 90-day mortality was 3.6% (n\u0026thinsp;=\u0026thinsp;1 patient died from septic shock caused by infected fluid collections, in the presence of pancreatic leakage). Six patients received selective internal radiation therapy (SIRT) instead of hepatic resection due to insufficient FLR function (n\u0026thinsp;=\u0026thinsp;4) or because they were considered unfit for surgery (n\u0026thinsp;=\u0026thinsp;2; n\u0026thinsp;=\u0026thinsp;1 poor underlying parenchyma quality and n\u0026thinsp;=\u0026thinsp;1 poor physical condition with extensive history), of whom one patient developed liver failure after SIRT. Sixteen patients did not undergo hepatic resection or SIRT due to insufficient FLR function (n\u0026thinsp;=\u0026thinsp;3), insufficient growth of FLR after PVE (n\u0026thinsp;=\u0026thinsp;4), disease progression (n\u0026thinsp;=\u0026thinsp;5), irresectable liver tumors (n\u0026thinsp;=\u0026thinsp;2) or a diagnosis of benign disease (n\u0026thinsp;=\u0026thinsp;2). An overview of the actions taken and corresponding number of patients based on the result of the HBS analysis is provided in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData and statistical analysis\u003c/h3\u003e\n\u003cp\u003eThe FLR function (corrected for BSA) assessed by observer A and observer B for all included patients is demonstrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eOverall, there was no significant difference in the assessment of FLR function between both observers (Z = -0.692, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.489; data was not normally distributed: W\u0026thinsp;=\u0026thinsp;0.945, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002 for observer A and W\u0026thinsp;=\u0026thinsp;0.949, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004 for observer B). Overall, observer A reported a mean FLR function of 3.01\u0026thinsp;\u0026plusmn;\u0026thinsp;1.39 and observer B of 3.00\u0026thinsp;\u0026plusmn;\u0026thinsp;1.38. Among patients with an adequate FLR function, observer A reported a mean FLR function of 4.07\u0026thinsp;\u0026plusmn;\u0026thinsp;1.13, while observer B reported 4.06\u0026thinsp;\u0026plusmn;\u0026thinsp;1.10. For the patients with an insufficient FLR function, the mean FLR function assessed by observer A was 1.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.50 and by observer B was 1.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51. Additional statistics per FLR segment assessment can be found in appendix B.\u003c/p\u003e \u003cp\u003eNo significant bias was found between the observers (M\u0026thinsp;=\u0026thinsp;0.0123, SD\u0026thinsp;=\u0026thinsp;0.11829; t(76)\u0026thinsp;=\u0026thinsp;0.915 and \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.363). Furthermore, linear regression analysis confirmed the absence of proportional bias (B\u0026thinsp;=\u0026thinsp;0.010, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.306). The Bland-Altman plot is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e4\u003c/span\u003e, demonstrating that the majority of the assessments lie within the 95% CI with no clear pattern. The two outliers indicate that only these two assessments of the FLR function differ significantly between the observers.\u003c/p\u003e \u003cp\u003eThe interobserver agreement in the FLR function is reported in Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eThe interobserver agreement in the FLR function.\u003c/b\u003e Quantification by three parameters: Intraclass Correlation Coefficient (ICC), Spearman's ρ and Cohen's κ and their corresponding p-value. CI\u0026thinsp;=\u0026thinsp;Confidence Interval\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInterobserver agreement\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eICC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.996 (95% CI: 0.994\u0026ndash;0.998)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSpearman\u0026rsquo;s ρ\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.995\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCohen\u0026rsquo;s κ\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.948\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAll three parameters were high (close to 1) and the corresponding \u003cem\u003ep\u003c/em\u003e-values were statistically significant. For Cohen\u0026rsquo;s κ, the assessments of the FLR functions were divided into two categories: assessments with a value\u0026thinsp;\u0026gt;\u0026thinsp;2.69%/min/m\u003csup\u003e2\u003c/sup\u003e resulting in approval for hepatic resection and assessments with a value\u0026thinsp;\u0026le;\u0026thinsp;2.69%/min/m\u003csup\u003e2\u003c/sup\u003e resulting in disapproval for hepatic resection.\u003c/p\u003e \u003cp\u003eWhen the cutoff value of 2.69%/min/m\u003csup\u003e2\u003c/sup\u003e was applied, two assessments did not correspond between both observers, where observer B assessed a FLR function higher than 2.69%/min/m\u003csup\u003e2\u003c/sup\u003e and observer A lower than 2.69%/min/m\u003csup\u003e2\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe aim of the current study was to assess the reproducibility of the preoperative assessment of the FLR function using HBS. The interobserver\u003c/p\u003e \u003cp\u003evariability and agreement was therefore evaluated. The interobserver agreement in the FLR function assessed by observer A and observer B was high and the interobserver variability was negligible. Therefore, the preoperative assessment of the FLR function appears to be reproducible.\u003c/p\u003e \u003cp\u003eThe accuracy of risk assessment for postoperative morbidity, liver failure and mortality was previously assessed by Dinant et al. [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], who also reported an acceptable level of agreement (93% of values within the 95% CI) between two observers in the uptake measurement of the FLR considering planar analysis (dynamic 2D imaging analysis of the \u003csup\u003e99m\u003c/sup\u003eTc-mebrofenin uptake). However, to date, no studies have been published that analyze to what extent the FLR function may differ between observers when SPECT-CT imaging is included.\u003c/p\u003e \u003cp\u003eOnly a small number of outliers were observed for the FLR function (n\u0026thinsp;=\u0026thinsp;2), indicating that these assessments differed significantly between the observers. Nevertheless, the differences between the assessments by observer A and observer B for these outliers have no clinical impact, since both assessments are above the cutoff value of 2.69%/min/m\u003csup\u003e2\u003c/sup\u003e (5.92 vs 5.08 and 3.37 vs 3.67). Based on both assessments, the conclusion for these patients is consistent: the FLR function is sufficient to proceed with major hepatic resection.\u003c/p\u003e \u003cp\u003eVariations in the FLR function can be introduced by differences in height and weight and hence BSA. Since the normalized FLR function is quite sensitive to differences in BSA, accurate BSA estimation at the time of HBS is essential. Even small deviations in height and weight, for example 2 cm and 2 kg, can cause the FLR function to vary by 0.12%/min/m\u003csup\u003e2\u003c/sup\u003e for the same patient. This effect is particularly relevant when the FLR function approaches the cutoff value of 2.69%/min/m\u003csup\u003e2\u003c/sup\u003e, which may result in misinterpretation of the FLR function.\u003c/p\u003e \u003cp\u003eAnother factor possibly influencing the FLR function is the way the ROI for the blood pool and liver is drawn. The ROI for the liver should comprise the uptake of \u003csup\u003e99m\u003c/sup\u003eTc-mebrofenin in the entire liver, while the left ventricular blood pool serves as a reference region for the ROI for the blood pool. Both ROIs should not overlap. These two steps are, however, carried out manually and are therefore susceptible to subjectivity. In addition, it is relevant that the VOI of the liver is representative for the volume of the liver. However, the selection of the threshold is based on the interpretation of the observer and can vary between the subjects, since the rates of uptake and excretion of \u003csup\u003e99m\u003c/sup\u003eTc-mebrofenin may differ. There can be a notable variability in the selection of the absolute threshold, resulting in variation in the VOI of the liver and consequently affecting the FLR function. Furthermore, the decision to correct for the uptake in the bile ducts could also introduce variations in the FLR function. Nevertheless, the extent to which these steps affect the FLR function and whether it can result in significant differences have to be determined in future research.\u003c/p\u003e \u003cp\u003eMoreover, the FLR is manually delineated on the LDCT. While segment 2\u0026ndash;3 are generally identifiable on the LDCT, the remaining segments can be more difficult to identify. Therefore, it is essential that the observer has good knowledge of the liver anatomy and has access to anatomical imaging, preferably in the venous phase. The liver can be divided into segments based on the course of the left, middle and right hepatic vein, as well as the left and right portal vein. If a contrast-enhanced CT prior to the HBS is available, it can aid in identifying the liver segments. However, the delineation of the segments on the LDCT remains an estimation. Additionally, it is not possible to establish the boundaries of the remnant liver with millimeter precision. When the liver is imaged at 140 keV and at 10 cm (typical organ depth [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]) relative to the detector, the resolution of the image is specified to be 7.5 mm (Full Width at Half Maximum) [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. This implies that the boundaries of the remnant liver can be delineated with an accuracy of 7.5 mm.\u003c/p\u003e \u003cp\u003eIn summary, the assessment of the FLR function remains partly subjective. What level of variation in the assessment of FLR function between observers can be regarded acceptable, remains the question. However, differences in FLR function assessed by various observers are of no major concern when the assessments are not approaching the cutoff value of 2.69%/min/m\u003csup\u003e2\u003c/sup\u003e. Discrepancies between observers are clinically irrelevant when both assessments are either above or below the cutoff value, since the decision of insufficient FLR will be the same. In the current study, the assessments of two patients show conflicting outcomes between observers. Observer B assessed a FLR function above the cutoff value and thereby allowing hepatic resection, while observer A assessed a FLR function below the cutoff value. Both assessments are indeed very close to the cutoff value (2.67 and 2.63 for observer A and 2.74 and 2.70 for observer B), however these differences were no outliers and thus not significantly different. The decision to proceed with hepatic resection in these cases should be carefully considered, perhaps consulting multiple observers and/or a multidisciplinary team to aid in the decision-making process. Furthermore, FLR volume may provide additional guidance in such cases, as FLR volumes above 30% are considered sufficient to proceed with hepatic resection in healthy liver tissue [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. When the assessments are inconclusive, PVE needs to be considered.\u003c/p\u003e \u003cp\u003eIt should be noted that observer A, an expert in the field of HBS analyses, trained observer B on how to use Hermes for retrieval of FLR function. Observer A was trained exactly the same way in the use of Hermes for the retrieval of FLR function by the group of Bennink et al. [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] from the Amsterdam University Medical Center. As stated before, the delineation of the liver segments is an observer depending part of FLR function assessment. Considering the results of observer B are comparable to the results of observer A, a potential bias caused by the training component cannot be excluded. To keep this risk of potential bias as low as possible, observer B was separately trained by an experienced liver surgeon on segmental anatomy of the liver and how to delineate the distinct segments on the imaging. Furthermore, observer B individually assessed the FLR function while being blinded to the results of observer A.\u003c/p\u003e \u003cp\u003eConsidering the postoperative course and outcome of the patients who underwent hepatic resection, the widely used cutoff value of 2.69%/min/m\u003csup\u003e2\u003c/sup\u003e appears effective in preventing PHLF. Perhaps a more lenient cutoff value could be used, thereby allowing more patients to be eligible for hepatic resection. Dinant et al. [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] revealed that when applying a cutoff value of 2.5%/min/m\u003csup\u003e2\u003c/sup\u003e approximately 3% of patients have a risk of developing PHLF, based on receiver operating characteristic (ROC) analysis. Chapelle et al. [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] suggested an even lower cutoff value of 2.3%/min/m\u003csup\u003e2\u003c/sup\u003e, which would prevent almost all PHLF incidences and all mortalities due to PHLF. On the contrary, Olthof et al. [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] suggested to use a cutoff value of 8.5%/min for the absolute FLR function (not corrected for BSA) in patients with (suspected) perihilar cholangiocarcinoma. It could very well be that different indications for major liver resection also require different cutoff values. In the current study, of the 28 patients who actually underwent hepatic resection, six patients (21.4%) developed complications after hepatic resection but none developed PHLF. Of these eight patients, three were diagnosed with HCC and five with cholangiocarcinoma. Two patients with cholangiocarcinoma died, one due to septic shock (caused by infected fluid collections, in the presence of pancreatic leakage) after hepatic resection. Based on this outcome, one could indeed argue for a stricter cutoff value for livers affected by cholangiocarcinoma compared to HCC. However, this is based on a very small sample size and one has to take into account that the outcome of surgical treatment of cholangiocarcinoma is influenced by far more variables than FLR function alone. Further investigation to determine the most optimal cutoff value involving ROC analysis is therefore necessary.\u003c/p\u003e \u003cp\u003eA limitation of the current study is that the observers did not re-assess their own FLR function analyses, allowing a more complete assessment of the reproducibility by also quantifying the intra-observer agreement. A future recommendation is to conduct a study involving multiple NM physicians and trainees across the country to assess and re-assess the FLR function, providing a more comprehensive and diverse perspective on the subjective assessment of the FLR function. Additionally, the effects of various factors potentially influencing FLR function assessment, including thresholding and biliary duct corrections, and whether these effects result in significant differences in the assessments, should be investigated. Finally, to reach a higher statistical power, future studies should include a larger number of patients. More observers as well as more patients will provide a more reliable representation of the subjective FLR function assessment and thereby enhance the generalizability of the findings.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, the FLR function assessment using HBS appears to be a reproducible tool in the decision-making whether or not to proceed with hepatic resection, showing low interobserver variability. The preoperative assessment of FLR function can be easily learned by a trainee, though thorough knowledge of segmental anatomy of the liver is required. Variations in FLR function assessments can occur due to different interpretations of the observers. Nevertheless, the assessment of the FLR function is safe to employ and justified based on this single center evaluation.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eALPPS\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Associating Liver Partition and Portal vein ligation for Staged hepatectomy\u003c/p\u003e\n\u003cp\u003eBSA\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Body Surface Area\u003c/p\u003e\n\u003cp\u003eCI\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Confidence Interval\u003c/p\u003e\n\u003cp\u003eCRLM\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Colorectal Liver Metastases\u003c/p\u003e\n\u003cp\u003eCT\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Computed Tomography\u003c/p\u003e\n\u003cp\u003eEHR\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Electronic Health Record\u003c/p\u003e\n\u003cp\u003eFLR\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Future Liver Remnant\u003c/p\u003e\n\u003cp\u003eHBS\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Hepatobiliary Scintigraphy\u003c/p\u003e\n\u003cp\u003eHCC\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Hepatocellular Carcinoma\u003c/p\u003e\n\u003cp\u003eHVE\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Hepatic Vein Embolization\u003c/p\u003e\n\u003cp\u003eICC\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Intraclass Correlation Coefficient\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLDCT\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Low-Dose Computed Tomography\u003c/p\u003e\n\u003cp\u003eNET\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Neuroendocrine Tumor\u003c/p\u003e\n\u003cp\u003eNM\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Nuclear Medicine\u003c/p\u003e\n\u003cp\u003ePHLF\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Post-hepatectomy Liver Failure\u003c/p\u003e\n\u003cp\u003ePVE\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Portal Vein Embolization\u003c/p\u003e\n\u003cp\u003eROC\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Receiver Operating Characteristic\u003c/p\u003e\n\u003cp\u003eROI\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Region-of-Interest\u003c/p\u003e\n\u003cp\u003eSD\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Standard Deviation\u003c/p\u003e\n\u003cp\u003eSPECT\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Single Photon Emission Computed Tomography\u003c/p\u003e\n\u003cp\u003eTc\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Technetium\u003c/p\u003e\n\u003cp\u003eTM\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Technical Medicine\u003c/p\u003e\n\u003cp\u003eUMCG\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;University Medical Center Groningen\u003c/p\u003e\n\u003cp\u003eVOI \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Volume-of-Interest\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate\u003cbr\u003e\u0026nbsp;Ethical approval was obtained by the Institutional Review Board of the University Medical Center Groningen (reference number: 20842).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003cbr\u003e\u0026nbsp;Not applicable\u003c/p\u003e\n\u003cp\u003eAvailability of data and material\u003cbr\u003e\u0026nbsp;The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003cbr\u003e\u0026nbsp;The authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003eFunding\u003cbr\u003e\u0026nbsp;None\u003c/p\u003e\n\u003cp\u003eAuthors\u0026apos; contributions\u003c/p\u003e\n\u003cp\u003eKdV: Conceptualization; Data curation; Formal analysis; Methodology; Writing - original draft; JO: Conceptualization; Methodology; Validation; Supervision; Writing \u0026ndash; review \u0026amp; editing. SF: Conceptualization; Methodology; Writing \u0026ndash; review \u0026amp; editing. MdB: Conceptualization; Methodology; Writing \u0026ndash; review \u0026amp; editing. MN: Conceptualization; Methodology; Writing \u0026ndash; review \u0026amp; editing. EGJ: Conceptualization; Methodology; Supervision; Writing \u0026ndash; review \u0026amp; editing. GS: Data curation; Formal analysis; Methodology; Writing \u0026ndash; review \u0026amp; editing. SR: Conceptualization; Data curation; Formal analysis; Methodology; Validation; Supervision; Writing \u0026ndash; review \u0026amp; editing. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003cbr\u003e\u0026nbsp;None\u003c/p\u003e\n\u003cp\u003eAuthors\u0026apos; information\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003e Technical Medicine, University of Twente, Drienerlolaan 5, 7522 NB Enschede, The Netherlands\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u0026nbsp;\u003c/sup\u003eDepartment of Hepato-pancreato-biliary Surgery and Liver Transplantation, University Medical Center Groningen, Hanzeplein 1, 9713 GZ Groningen, The Netherlands\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u003c/sup\u003e Department of Surgical Oncology, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e4\u003c/sup\u003e Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, Hanzeplein 1, 9713 GZ Groningen, The Netherlands\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e5\u003c/sup\u003e Multi-Modality Medical Imaging (M3I) Group, TechMed Centre , University of Twente, Drienerlolaan 5, 7522 NB Enschede, The Netherlands\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eS\u0026oslash;reide JA, Deshpande R. Post hepatectomy liver failure (PHLF) \u0026ndash; Recent advances in prevention and clinical management. Eur J Surg Oncol 2021;47:216\u0026ndash;24. https://doi.org/10.1016/J.EJSO.2020.09.001.\u003c/li\u003e\n\u003cli\u003eOlthof PB, Arntz P, Truant S, El Amrani M, Dasari BVM, Tomassini F, et al. Hepatobiliary scintigraphy to predict postoperative liver failure after major liver resection; a multicenter cohort study in 547 patients. HPB 2023;25:417\u0026ndash;24. https://doi.org/10.1016/J.HPB.2022.12.005.\u003c/li\u003e\n\u003cli\u003eChapelle T, Op De Beeck B, Huyghe I, Francque S, Driessen A, Roeyen G, et al. Future remnant liver function estimated by combining liver volumetry on magnetic resonance imaging with total liver function on 99mTc-mebrofenin hepatobiliary scintigraphy: Can this tool predict post-hepatectomy liver failure? HPB 2015;18:494\u0026ndash;503. https://doi.org/10.1016/j.hpb.2015.08.002.\u003c/li\u003e\n\u003cli\u003eKhan AS, Garcia-Aroz S, Ansari MA, Atiq SM, Senter-Zapata M, Fowler K, et al. Assessment and optimization of liver volume before major hepatic resection: Current guidelines and a narrative review. Int J Surg 2018;52:74\u0026ndash;81. https://doi.org/10.1016/J.IJSU.2018.01.042.\u003c/li\u003e\n\u003cli\u003eFranken LC, Rassam F, van Lienden KP, Bennink RJ, Besselink MG, Busch OR, et al. Effect of structured use of preoperative portal vein embolization on outcomes after liver resection of perihilar cholangiocarcinoma. Br J Surg Open 2020;4:449\u0026ndash;55. https://doi.org/10.1002/BJS5.50273.\u003c/li\u003e\n\u003cli\u003ede Graaf W, van Lienden KP, Dinant S, Roelofs JJTH, Busch ORC, Gouma DJ, et al. Assessment of future remnant liver function using hepatobiliary scintigraphy in patients undergoing major liver resection. J Gastrointest Surg 2010;14:369\u0026ndash;78. https://doi.org/10.1007/s11605-009-1085-2.\u003c/li\u003e\n\u003cli\u003eVan Lienden KP, Van Den Esschert JW, De Graaf W, Bipat S, Lameris JS, Van Gulik TM, et al. Portal vein embolization before liver resection: A systematic review. Cardiovasc Intervent Radiol 2013;36:25\u0026ndash;34. https://doi.org/10.1007/s00270-012-0440-y.\u003c/li\u003e\n\u003cli\u003eCieslak KP, Bennink RJ, de Graaf W, van Lienden KP, Besselink MG, Busch ORC, et al. Measurement of liver function using hepatobiliary scintigraphy improves risk assessment in patients undergoing major liver resection. HPB 2016;18:773\u0026ndash;80. https://doi.org/10.1016/j.hpb.2016.06.006.\u003c/li\u003e\n\u003cli\u003eGupta M, Choudhury PS, Singh S, Hazarika D. Liver Functional Volumetry by Tc-99m Mebrofenin Hepatobiliary Scintigraphy before Major Liver Resection: A Game Changer. Indian J Nucl Med 2018;33:283. https://doi.org/10.4103/IJNM.IJNM_72_18.\u003c/li\u003e\n\u003cli\u003eArntz PJW, Deroose CM, Marcus C, Sturesson C, Panaro F, Erdmann J, et al. Joint EANM/SNMMI/IHPBA procedure guideline for [99mTc]Tc-mebrofenin hepatobiliary scintigraphy SPECT/CT in the quantitative assessment of the future liver remnant function. HPB 2023;25:1131\u0026ndash;44. https://doi.org/10.1016/J.HPB.2023.06.001.\u003c/li\u003e\n\u003cli\u003eRassam F, Olthof PB, Richardson H, Van Gulik TM, Bennink RJ. Practical guidelines for the use of technetium-99m mebrofenin hepatobiliary scintigraphy in the quantitative assessment of liver function. Nucl Med Commun 2019;40:297\u0026ndash;307. https://doi.org/10.1097/MNM.0000000000000973.\u003c/li\u003e\n\u003cli\u003eAbdel-Misih SRZ, Bloomston M. Liver Anatomy. Surg Clin North Am 2010;90:653. https://doi.org/10.1016/J.SUC.2010.04.017.\u003c/li\u003e\n\u003cli\u003eDindo D, Demartines N, Clavien PA. Classification of surgical complications: A new proposal with evaluation in a cohort of 6336 patients and results of a survey. Ann Surg 2004;240:205\u0026ndash;13. https://doi.org/10.1097/01.SLA.0000133083.54934.AE.\u003c/li\u003e\n\u003cli\u003eDinant S, De Graaf W, Verwer BJ, Bennink RJ, Van Lienden KP, Gouma DJ, et al. Risk Assessment of Posthepatectomy Liver Failure Using Hepatobiliary Scintigraphy and CT Volumetry. J Nucl Med 2007;48:685\u0026ndash;92. https://doi.org/10.2967/JNUMED.106.038430.\u003c/li\u003e\n\u003cli\u003eSorenson JA, Phelps ME. The Anger Camera: Performance Characteristics. Phys. Nucl. Med. 2nd ed., W.B. Saunders Company; 1987, p. 331\u0026ndash;45.\u003c/li\u003e\n\u003cli\u003eBui MHH, Robert A, Badel J-N, Kvassheim M, Stokke C, Rit S, et al. Validation of a model of the Symbia Intevo Bold SPECT scanner for Monte Carlo simulations. Nucl. Sci. Symp. Med. Imaging Conf. (IEEE NSS MIC), Vancouver, Canada: 2023.\u003c/li\u003e\n\u003cli\u003eOlthof PB, Coelen RJS, Bennink RJ, Heger M, Lam MF, Besselink MG, et al. 99mTc-mebrofenin hepatobiliary scintigraphy predicts liver failure following major liver resection for perihilar cholangiocarcinoma. HPB 2017;19:850\u0026ndash;8. https://doi.org/10.1016/j.hpb.2017.05.007.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"ejnmmi-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejre","sideBox":"Learn more about [EJNMMI Research](http://ejnmmires.springeropen.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ejre/default.aspx","title":"EJNMMI Research","twitterHandle":"@officialEANM","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Future Liver Remnant function, hepatobiliary scintigraphy, interobserver variability, post-hepatectomy liver failure","lastPublishedDoi":"10.21203/rs.3.rs-5865429/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5865429/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003ePost-hepatectomy liver failure (PHLF) is a serious complication following hepatic resection and associated with a high mortality rate. The risk of PHLF can be estimated pre-resection by assessing the function of the future liver remnant (FLR) using hepatobiliary scintigraphy (HBS). Inaccurate estimation can have profound consequences, including an incorrect decision whether or not to proceed with hepatic resection. Therefore, it is essential to determine the reproducibility of preoperative assessment of the FLR function using HBS. The interobserver variability in the assessments of FLR function between two independent observers, blinded for each other\u0026rsquo;s results, was evaluated.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eIn 24 out of 50 patients, the FLR function was predicted to be sufficient (\u0026gt;\u0026thinsp;2.69%/min/m\u003csup\u003e2\u003c/sup\u003e) to proceed with hepatic resection without preoperative FLR hypertrophy-inducing measures. In contrast, six patients were first subjected to portal vein embolization based on a predicted insufficient FLR function, which subsequently resulted in resection in four patients. Comparing the FLR function analyses of both observers, Bland-Altman plots demonstrated that most assessments lie within the 95% confidence interval and no pattern suggesting bias was observed. The interobserver level of agreement therefore appeared high for the FLR function (ICC\u0026thinsp;=\u0026thinsp;0.996, Spearman\u0026rsquo;s ρ\u0026thinsp;=\u0026thinsp;0.995 and Cohen\u0026rsquo;s κ\u0026thinsp;=\u0026thinsp;0.948).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThis study shows a high interobserver agreement and a negligible interobserver variability in the assessment of FLR function using HBS, regardless of the extent of observer experience. Therefore, the preoperative assessment of the FLR function is reproducible in the workup for patients planned to undergo (major) hepatic resections.\u003c/p\u003e","manuscriptTitle":"Interobserver variability in the preoperative assessment of future liver remnant function using hepatobiliary scintigraphy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-01 09:30:00","doi":"10.21203/rs.3.rs-5865429/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Accept","date":"2025-05-14T08:16:02+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2025-04-04T08:04:05+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-31T15:47:14+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-31T05:24:55+00:00","index":"","fulltext":""},{"type":"submitted","content":"EJNMMI Research","date":"2025-03-28T04:13:29+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"ejnmmi-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejre","sideBox":"Learn more about [EJNMMI Research](http://ejnmmires.springeropen.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ejre/default.aspx","title":"EJNMMI Research","twitterHandle":"@officialEANM","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e7569c3e-ba5a-4e70-9432-a36a4f1d37d5","owner":[],"postedDate":"April 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-06-16T16:01:31+00:00","versionOfRecord":{"articleIdentity":"rs-5865429","link":"https://doi.org/10.1186/s13550-025-01261-3","journal":{"identity":"ejnmmi-research","isVorOnly":false,"title":"EJNMMI Research"},"publishedOn":"2025-06-12 15:57:39","publishedOnDateReadable":"June 12th, 2025"},"versionCreatedAt":"2025-04-01 09:30:00","video":"","vorDoi":"10.1186/s13550-025-01261-3","vorDoiUrl":"https://doi.org/10.1186/s13550-025-01261-3","workflowStages":[]},"version":"v1","identity":"rs-5865429","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5865429","identity":"rs-5865429","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}