Hepatic angiomyolipoma is a rare benign tumor that often mimics hepatocellular carcinoma on imaging. Here, we report a rare case of hepatic angiomyolipoma with extensive hemorrhagic degeneration, resulting in a large hemorrhagic component that mimicked a complicated cystic neoplasm. A 43-year-old woman presented with mild abdominal distension, and imaging revealed a 16-cm multiloculated cystic mass in the left hepatic lobe. Computed tomography revealed a thick, enhancing wall and septa with hyperattenuating internal fluid. On gadoxetic acid-enhanced magnetic resonance imaging, arterial enhancement was observed along the thick wall, and a subtle opposedphase signal drop indicated a small fat component that was initially missed. Laparoscopic left lobectomy was performed under suspicion of a malignant cystic neoplasm. Histopathological examination revealed an angiomyolipoma composed of thick-walled vessels, spindle-shaped muscle bundles, and scant adipocytes, with human melanoma black 45 positivity and absence of an epithelial lining, consistent with hemorrhagic degeneration. This case highlights how hemorrhagic degeneration can pose a significant diagnostic challenge by masking the typical features of hepatic angiomyolipoma, leading to diagnostic confusion with complicated cystic tumors.

Purpose: Given the widening of the donor pool to include patients with steatosis, small-for-size grafts, and older patients, this study examined the effect of age on liver volumetric regeneration after a donor right hepatectomy. Methods: We enrolled 33 older (≥55 years) and 277 younger (<30 years) donors who underwent donor right hepatectomy between March 2012 and December 2022. After propensity score-matched analysis, the perioperative surgical outcomes and growth rates of the remnant liver in 63 younger and 32 older donors were compared. Liver regeneration was assessed using CT volumetry for up to 6 months after surgery. Poor liver regeneration was defined as restoration of less than 80% of the original liver volume. The risk factors for poor liver regeneration were analyzed using a binary logistic regression model. Results: The mean age of older and younger donors was 58.0 and 24.3 years, respectively. Despite comparable preoperative factors, older donors showed significantly lower regeneration rates at all observed time points (1 month:75.5% vs. 82.3%, P = 0.001; 3 months: 80.4% vs. 90.5%, P < 0.001; and 6 months: 87.9% vs. 95.8, P = 0.006, compared to total liver volume). A large total liver volume and older age were identified as risk factors for poor liver regeneration. Conclusion Older donors showed a reduced capacity for liver regeneration. This finding suggests the need for the development of more conservative criteria for residual liver volume in older donors than for younger donors to ensure donor safety.

Background: s/Aims: Artificial intelligence (AI) technology has been used to assess surgery quality, educate, and evaluate surgical performance using video recordings in the minimally invasive surgery era. Much attention has been paid to automating surgical workflow analysis from surgical videos for an effective evaluation to achieve the assessment and evaluation. This study aimed to design a deep learning model to automatically identify surgical phases using laparoscopic cholecystectomy videos and automatically assess the accuracy of recognizing surgical phases. Methods: One hundred and twenty cholecystectomy videos from a public dataset (Cholec80) and 40 laparoscopic cholecystectomy videos recorded between July 2022 and December 2022 at a single institution were collected. These datasets were split into training and testing datasets for the AI model at a 2:1 ratio. Test scenarios were constructed according to structural characteristics of the trained model. No pre- or post-processing of input data or inference output was performed to accurately analyze the effect of the label on model training. Results: A total of 98,234 frames were extracted from 40 cases as test data. The overall accuracy of the model was 91.2%. The most accurate phase was Calot’s triangle dissection (F1 score: 0.9421), whereas the least accurate phase was clipping and cutting (F1 score:0.7761). Conclusions Our AI model identified phases of laparoscopic cholecystectomy with a high accuracy.

Background: s/Aims: Artificial intelligence (AI) technology has been used to assess surgery quality, educate, and evaluate surgical performance using video recordings in the minimally invasive surgery era. Much attention has been paid to automating surgical workflow analysis from surgical videos for an effective evaluation to achieve the assessment and evaluation. This study aimed to design a deep learning model to automatically identify surgical phases using laparoscopic cholecystectomy videos and automatically assess the accuracy of recognizing surgical phases. Methods: One hundred and twenty cholecystectomy videos from a public dataset (Cholec80) and 40 laparoscopic cholecystectomy videos recorded between July 2022 and December 2022 at a single institution were collected. These datasets were split into training and testing datasets for the AI model at a 2:1 ratio. Test scenarios were constructed according to structural characteristics of the trained model. No pre- or post-processing of input data or inference output was performed to accurately analyze the effect of the label on model training. Results: A total of 98,234 frames were extracted from 40 cases as test data. The overall accuracy of the model was 91.2%. The most accurate phase was Calot’s triangle dissection (F1 score: 0.9421), whereas the least accurate phase was clipping and cutting (F1 score:0.7761). Conclusions Our AI model identified phases of laparoscopic cholecystectomy with a high accuracy.

Background: /Aim: Gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid-enhanced magnetic resonance imaging (EOBMRI) further enhances the identification of additional hepatic nodules compared with computed tomography (CT) alone; however, the optimal treatment for such additional nodules remains unclear. We investigated the long-term oncological effect of aggressive treatment strategies for additional lesions identified using EOB-MRI in patients with hepatocellular carcinoma (HCC). Methods: Data from 522 patients diagnosed with solitary HCC using CT between January 2008 and December 2012 were retrospectively reviewed. Propensity score-matched (PSM) analysis was used to compare the oncologic outcomes between patients with solitary HCC and those with additional nodules on EOB-MRI after aggressive treatment (resection or radiofrequency ablation [RFA]). Results: Among the 383 patients included, 59 had additional nodules identified using EOB-MRI. Compared with patients with solitary HCC, those with additional nodules on EOB-MRI had elevated total bilirubin, aspartate transaminase, and alanine transaminase; had a lower platelet count, higher MELD score, and highly associated with liver cirrhosis (P<0.05). Regarding long-term outcomes, 59 patients with solitary HCC and those with additional nodules after PSM were compared. Disease-free survival (DFS) and overall survival (OS) were comparable between the two groups (DFS, 60.4 vs. 44.3 months, P=0.071; OS, 82.8 vs. 84.8 months, P=0.986). Conclusion The aggressive treatment approach, either resection or RFA, for patients with additional nodules identified on EOBMRI was associated with long-term survival comparable with that for solitary HCC. However, further studies are required to confirm these findings.

Background: s/Aims: Artificial intelligence (AI) technology has been used to assess surgery quality, educate, and evaluate surgical performance using video recordings in the minimally invasive surgery era. Much attention has been paid to automating surgical workflow analysis from surgical videos for an effective evaluation to achieve the assessment and evaluation. This study aimed to design a deep learning model to automatically identify surgical phases using laparoscopic cholecystectomy videos and automatically assess the accuracy of recognizing surgical phases. Methods: One hundred and twenty cholecystectomy videos from a public dataset (Cholec80) and 40 laparoscopic cholecystectomy videos recorded between July 2022 and December 2022 at a single institution were collected. These datasets were split into training and testing datasets for the AI model at a 2:1 ratio. Test scenarios were constructed according to structural characteristics of the trained model. No pre- or post-processing of input data or inference output was performed to accurately analyze the effect of the label on model training. Results: A total of 98,234 frames were extracted from 40 cases as test data. The overall accuracy of the model was 91.2%. The most accurate phase was Calot’s triangle dissection (F1 score: 0.9421), whereas the least accurate phase was clipping and cutting (F1 score:0.7761). Conclusions Our AI model identified phases of laparoscopic cholecystectomy with a high accuracy.

Purpose: The aim of the present study was to evaluate the per-lesion sensitivity and specificity of the Korean Liver Cancer Association–National Cancer Center (KLCA-NCC) 2022 criteria for the noninvasive diagnosis of hepatocellular carcinoma (HCC), with intraindividual comparison of the diagnostic performance of magnetic resonance imaging with extracellular agents (ECA-MRI) and hepatobiliary agents (HBA-MRI). Materials and Methods: Patients at high risk for HCC who were referred to a tertiary academic institution for hepatic lesions with size ≥ 10 mm between July 2019 and June 2022 were enrolled. A total of 91 patients (mean age, 58.1 years; 76 men and 15 women) with 118 lesions who underwent both ECA-MRI and HBA-MRI were eligible for final analysis. The per-lesion sensitivities and specificities of the KLCA-NCC 2022 criteria using ECA-MRI and HBA-MRI were compared using McNemar’s test. Results: The 118 lesions were 93 HCCs, 4 non-HCC malignancies, and 21 benign lesions. On HBA-MRI, the “definite” HCC category showed significantly higher sensitivity than ECA-MRI (78.5% vs. 58.1%, p < 0.001), with identical specificity (92.0% vs. 92.0%, p > 0.999). For “probable” or “definite” HCC categories, there were no differences in the sensitivity (84.9% vs. 84.9%, p > 0.999) and specificity (84.0% vs. 84.0%, p > 0.999) between ECA-MRI and HBA-MRI. Conclusion The “definite” HCC category of the KLCA-NCC 2022 criteria showed higher sensitivity in diagnosing HCC on HBA-MRI compared with ECA-MRI, without compromising specificity. There were no significant differences in the sensitivity and specificity of “probable” or “definite” HCC categories according to ECA-MRI and HBA-MRI.

Gastrointestinal stromal tumors (GISTs) are rare mesenchymal tumors derived from precursors of the interstitial cells of Cajal that commonly arise from the stomach or small intestine. These tumors usually contain KIT and/or PDGFRA mutations, which encode type III receptor tyrosine kinases. Approximately 10% of GISTs originate from sites other than the gastrointestinal tract, such as the mesentery, urinary bladder, retroperitoneum, pancreas, gallbladder, and liver. These tumors are hypothesized to originate from interstitial Cajal-like cells or undifferentiated pluripotent mesenchymal cells outside the gastrointestinal tract. Primary hepatic GISTs are rare, with most hepatic GISTs being secondary.Here, we report the case of a 69-year-old woman with a rare primary hepatic GIST. The hepatic GIST, measuring 13.5 cm, was incidentally discovered in the right liver lobe and exhibited heterogeneous arterial phase hyperenhancement, washout, diffusion restriction, low signal intensity in the hepatobiliary phase, intratumoral hemorrhage, necrosis, and fluid-fluid levels. Imaging revealed no evidence of extrahepatic primary lesions. GIST was pathologically confirmed via percutaneous biopsy and subsequent surgical resection.Despite adjuvant imatinib therapy, the tumor recurred with peritoneal seeding 15 months postoperatively.

Background/aims: Circulating tumor cells (CTCs) with cancer stemness have been demonstrated to be a direct cause of tumor recurrence, and only few studies have reported the role of CTCs in liver transplantation (LT) for hepatocellular carcinoma (HCC). Methods: Epithelial cell adhesion molecule+ (EpCAM+), cluster of differentiation 90+ (CD90+) and EpCAM+/CD90+ CTCs were sorted via fluorescence-activated cell sorting, and transcripts level of EpCAM, K19 and CD90 in the peripheral blood were analyzed via real-time polymerase chain reaction preoperatively and on postoperative days 1 and 7 in 25 patients who underwent living donor liver transplantation (LDLT) for HCC. EpCAM protein was assessed in HCC tissue using immunohistochemical staining. The median follow-up duration was 40 months. Results: HCC after LDLT recurred in four out of 25 patients. Detection of EpCAM+ or CD90+ CTCs correlated well with their messenger RNA levels (p<0.05). EpCAM+ CTCs were readily detected in HCC tissue expressing EpCAM protein. The detection of EpCAM+ CTCs or EpCAM+/CD90+ CTCs before surgery and on postoperative day 1 was significantly associated with HCC recurrence after LT (all p<0.05). Pretransplant serum PIVKA-II >100 mAU/mL and postoperative day 1 EpCAM+/CD90+ CTCs were independent risk factors for HCC recurrence (hazard ratio, 14.64; 95% confidence interval, 1.08 to 198.20; p=0.043 and hazard ratio, 26.88; 95% confidence interval, 1.86 to 387.51; p=0.016, respectively). Conclusions EpCAM+/CD90+ CTCs can be used preoperatively and 1 day after LDLT as key biological markers in LT candidate selection and post-LDLT management.

Background/Aims: This study aimed to investigate whether everolimus (EVR) affects long-term survival after liver transplantation (LT) in patients with hepatocellular carcinoma (HCC). Methods: The data from 303 consecutive patients with HCC who had undergone LT from January 2012 to July 2018 were retrospectively reviewed. The patients were divided into two groups: 1) patients treated with EVR in combination with calcineurin inhibitors (CNIs) (EVR group; n=114) and 2) patients treated with CNI-based therapy without EVR (non-EVR group; n=189). Time to recurrence (TTR) and overall survival (OS) after propensity score (PS) matching were compared between the groups, and prognostic factors for TTR and OS were evaluated. Results: The EVR group exhibited more aggressive tumor biology than the non-EVR group, such as a higher number of tumors (P=0.003), a higher prevalence of microscopic vascular invasion (P=0.017) and exceeding Milan criteria (P=0.029). Compared with the PS-matched non-EVR group, the PS-matched EVR group had significantly better TTR (P<0.001) and OS (P<0.001). In multivariable analysis, EVR was identified as an independent prognostic factor for TTR (hazard ratio [HR], 0.248; P=0.001) and OS (HR, 0.145; P<0.001). Conclusions Combined with CNIs, EVR has the potential to prolong long-term survival in patients undergoing LT for HCC. These findings warrant further investigation in a well-designed prospective study.