Practice guidelines for managing extrahepatic biliary tract cancers.

Backgrounds/Aims: Reported incidence of extrahepatic bile duct cancer is higher in Asians than in Western populations. Korea, in particular, is one of the countries with the highest incidence rates of extrahepatic bile duct cancer in the world. Although research and innovative therapeutic modalities for extrahepatic bile duct cancer are emerging, clinical guidelines are currently unavailable in Korea. The Korean Society of Hepato-Biliary-Pancreatic Surgery in collaboration with related societies (Korean Pancreatic and Biliary Surgery Society, Korean Society of Abdominal Radiology, Korean Society of Medical Oncology, Korean Society of Radiation Oncology, Korean Society of Pathologists, and Korean Society of Nuclear Medicine) decided to establish clinical guideline for extrahepatic bile duct cancer in June 2021. Methods: Contents of the guidelines were developed through subgroup meetings for each key question and a preliminary draft was finalized through a Clinical Guidelines Committee workshop. Results: In November 2021, the finalized draft was presented for public scrutiny during a formal hearing. Conclusions: The extrahepatic guideline committee believed that this guideline could be helpful in the treatment of patients.

Comparison of four histological scoring systems for autoimmune hepatitis to improve diagnostic sensitivity.

BACKGROUND/AIMS: The histological criteria in the 1999 and 2008 scoring systems proposed by the International Autoimmune Hepatitis Group (IAIHG) have their inherent limitations in diagnosing autoimmune hepatitis (AIH). In this study, we evaluated the histology components of four scoring systems (1. revised original scoring system ["1999 IAIHG"], 2. simplified scoring system ["2008 IAIHG"], 3. modified histologic criteria ["2017 UCSF"], and 4. a new histologic criteria proposed by the International AIH Pathology Group ["2022 IAHPG"]) in AIH patients. METHODS: Medical records and liver biopsies were retrospectively reviewed for 68 patients from two independent medical institutions, diagnosed with AIH based on the 1999 IAIHG system between 2006 and 2016. The histological features were reviewed in detail, and the four histological scoring systems were compared. RESULTS: Out of the 68 patients, 56 (82.4%) patients met the "probable" or "definite" AIH criteria of the 2008 IAIHG system, and the proportion of histologic score 2 (maximum) was 40/68 (58.8%). By applying the 2017 UCSF criteria, the number of histology score 2 increased to 60/68 (88.2%), and "probable" or "definite" AIH cases increased to 61/68 (89.7%). Finally, applying the 2022 IAHPG histology score resulted in the highest number of cases with histologic score 2 (64/68; 94.1%) and with a diagnosis of "probable" or "definite" AIH (62/68; 91.2%). CONCLUSION: The recently proposed UCSF/IAHPG histological criteria increased the histology score of AIH. Substituting the histology component of the 2008 IAIHG system with the 2022 IAHPG criteria increased the sensitivity for diagnosing AIH (≥"Probable AIH") from 82.4% to 91.2%.

PAIP 2020: Microsatellite instability prediction in colorectal cancer.

Microsatellite instability (MSI) refers to alterations in the length of simple repetitive genomic sequences. MSI status serves as a prognostic and predictive factor in colorectal cancer. The MSI-high status is a good prognostic factor in stage II/III cancer, and predicts a lack of benefit to adjuvant fluorouracil chemotherapy in stage II cancer but a good response to immunotherapy in stage IV cancer. Therefore, determining MSI status in patients with colorectal cancer is important for identifying the appropriate treatment protocol. In the Pathology Artificial Intelligence Platform (PAIP) 2020 challenge, artificial intelligence researchers were invited to predict MSI status based on colorectal cancer slide images. Participants were required to perform two tasks. The primary task was to classify a given slide image as belonging to either the MSI-high or the microsatellite-stable group. The second task was tumor area segmentation to avoid ties with the main task. A total of 210 of the 495 participants enrolled in the challenge downloaded the images, and 23 teams submitted their final results. Seven teams from the top 10 participants agreed to disclose their algorithms, most of which were convolutional neural network-based deep learning models, such as EfficientNet and UNet. The top-ranked system achieved the highest F1 score (0.9231). This paper summarizes the various methods used in the PAIP 2020 challenge. This paper supports the effectiveness of digital pathology for identifying the relationship between colorectal cancer and the MSI characteristics.

Molecular Classification of Extrapulmonary Neuroendocrine Carcinomas With Emphasis on POU2F3-positive Tuft Cell Carcinoma.

Extrapulmonary neuroendocrine carcinomas (EP-NECs) are associated with a poor clinical outcome, and limited information is available on the biology and treatment of EP-NECs. We studied EP-NECs by applying the recent novel findings from studies of pulmonary neuroendocrine carcinomas, including POU2F3, the master regulator of tuft cell variant of small cell lung carcinomas. A cohort of 190 patients with surgically resected EP-NECs or poorly differentiated carcinomas (PDCs) were established. Immunohistochemistry (IHC) for POU2F3 along with ASCL1, NEUROD1, YAP1, and conventional neuroendocrine markers was performed on tissue microarrays. Selected cases with or without POU2F3 expression were subjected to targeted gene expression profiling using nCounter PanCancer Pathway panel. POU2F3-positive tuft cell carcinomas were present in 12.6% of EP-NEC/PDCs, with variable proportions according to organ systems. POU2F3 expression was negatively correlated with the expression levels of ASCL1, NEUROD1, and conventional neuroendocrine markers ( P <0.001), enabling IHC-based molecular classification into ASCL1-dominant, NEUROD1-dominant, POU2F3-dominant, YAP1-dominant, and not otherwise specified subtypes. Compared wih POU2F3-negative cases, POU2F3-positive tuft cell carcinomas showed markedly higher expression levels of PLCG2 and BCL2 , which was also validated in the entire cohort by IHC. In addition to POU2F3, YAP1-positive tumors were a distinct subtype among EP-NEC/PDCs, characterized by unique T-cell inflamed microenvironment. We found rare extrapulmonary POU2F3-positive tumors arising from previously unappreciated cells of origin. Our data show novel molecular pathologic features of EP-NEC/PDCs including potential therapeutic vulnerabilities, thereby emphasizing the need for focusing on unique features of EP-NEC/PDCs.

Usefulness of Liquid-Based Cytology in Diagnosing Biliary Tract Cancer Compared to Conventional Smear and Forceps Biopsy.

BACKGROUND/AIMS: Liquid-based cytology (LBC) has been shown to improve the diagnostic efficacy of brush cytology for thyroid, cervical and pancreatic cancer. To evaluate the diagnostic performance of LBC for biliary tract cancer, we compared it with conventional smears and forceps biopsies. METHODS: A retrospective study was conducted of all consecutive patients who underwent brush cytology under ERCP from January 2010 to April 2020. The primary outcome was the diagnostic efficacy of conventional smears and LBC. The difference between the two groups was corrected using inverse probability weighting (IPW). The secondary outcome was the sensitivity and specificity of brush cytology and forceps biopsy. The secondary outcome was evaluated in patients who underwent both methods. RESULTS: Among 162 patients, conventional smears were performed in 70 patients and LBC was performed in 92 patients. In the primary analysis using IPW, the sensitivity of conventional smears and LBC was 56.00% and 78.26% respectively (P = 0.009). The specificity was 100% for both methods. The accuracy was 66.15% for conventional smears and 83.33% for LBC (P = 0.012). In the secondary analysis, the sensitivity of conventional smears versus forceps biopsies was 62.16% versus 78.38% (P = 0.034) and 81.16% for both LBC and forceps biopsies. The specificity of both cytological examination and forceps biopsies was 100%. CONCLUSIONS: Liquid-based cytology demonstrated better sensitivity and accuracy than conventional smears. Moreover, its diagnostic performance was close to that of forceps biopsies.

A transcriptome-Based Deep Neural Network Classifier for Identifying the Site of Origin in Mucinous Cancer.

Purpose: There is a lack of tools for identifying the site of origin in mucinous cancer. This study aimed to evaluate the performance of a transcriptome-based classifier for identifying the site of origin in mucinous cancer. Materials And Methods: Transcriptomic data of 1878 non-mucinous and 82 mucinous cancer specimens, with 7 sites of origin, namely, the uterine cervix (CESC), colon (COAD), pancreas (PAAD), stomach (STAD), uterine endometrium (UCEC), uterine carcinosarcoma (UCS), and ovary (OV), obtained from The Cancer Genome Atlas, were used as the training and validation sets, respectively. Transcriptomic data of 14 mucinous cancer specimens from a tissue archive were used as the test set. For identifying the site of origin, a set of 100 differentially expressed genes for each site of origin was selected. After removing multiple iterations of the same gene, 427 genes were chosen, and their RNA expression profiles, at each site of origin, were used to train the deep neural network classifier. The performance of the classifier was estimated using the training, validation, and test sets. Results: The accuracy of the model in the training set was 0.998, while that in the validation set was 0.939 (77/82). In the test set which is newly sequenced from a tissue archive, the model showed an accuracy of 0.857 (12/14). t-SNE analysis revealed that samples in the test set were part of the clusters obtained for the training set. Conclusion: Although limited by small sample size, we showed that a transcriptome-based classifier could correctly identify the site of origin of mucinous cancer.

Comprehensive clinicopathologic, molecular, and immunologic characterization of colorectal carcinomas with loss of three intestinal markers, CDX2, SATB2, and KRT20.

Caudal-type homeobox 2 (CDX2), special AT-rich sequence-binding protein 2 (SATB2), and keratin 20 (KRT20) are frequently used as intestinal epithelium-specific markers in immunohistochemical studies. However, subsets of colorectal carcinomas (CRCs) show loss of these markers. We analyzed The Cancer Genome Atlas data to explore molecular correlates of CDX2, SATB2, and KRT20 genes in 390 CRCs. The decreased mRNA expression of each of the three genes commonly correlated with microsatellite instability-high (MSI-H), CpG island methylator phenotype-high (CIMP-H), BRAF/RNF43 mutations, consensus molecular subtype 1, and high tumor mutational burden. The downregulation of CDX2 or SATB2 was dependent on both MSI-H and CIMP-H, whereas that of KRT20 was more dependent on MSI-H than on CIMP-H. Next, we evaluated the immunohistochemical expression of CDX2, SATB2, and KRT20 in 436 primary CRCs. In contrast to RNA-level expression, decreased expression of CDX2 and SATB2 was more dependent on CIMP-H than on MSI-H. However, consistent with RNA-level expression, decreased expression of KRT20 was more dependent on MSI-H than on CIMP-H. CIMP-H and lymphatic invasion were consistently associated with both CDX2 loss and SATB2 loss in CRCs, regardless of MSI status. In microsatellite stable CRCs, CDX2 loss correlated with BRAF mutation, whereas SATB2 loss was associated with KRAS mutations and decreased T-cell infiltration. Cases with concurrent loss of all three markers were found exclusively in MLH1-methylated MSI-H/CIMP-H CRCs. In conclusion, MSI-H and/or CIMP-H are major common correlates of decreased CDX2/SATB2/KRT20 expression in CRCs, but the specific features associated with the loss of each marker are different in CRCs.

Quantitative analysis of tendon histopathology using digital pathology in rat models with Achilles tendon injury.

Although digital image analysis methods that quantify histopathologic features have emerged, no validated quantitative methods are available to evaluate tendon injury. This study aimed to propose and validate a quantitative analysis method to identify the histopathologic features of tendon injuries. The histopathologic features of two Achilles tendon injury models (a partial full-thickness defect model and a collagenase injection model) using Sprague-Dawley rats were evaluated by semiquantitative grading and a quantitative analysis method using a digital pathology software at weeks 1 and 4 after tendon injury (six tendons per group at each time point). The outcome variables between tendon injury models and between time points were compared, and the correlation between semiquantitative scores and the results of the quantitative analysis was investigated. The proposed analysis method quantified the severity of the histopathological features after tendon injury. Quantitative analysis differentiated the cell morphology between tendon injury models and time points better than semiquantitative scoring. The results from quantitative measurements correlated significantly with the semiquantitative scores. The proposed quantitative method can be effective in evaluating the histopathology of tendon injuries.

LI-RADS Tumor in Vein at CT and Hepatobiliary MRI.

Background Diagnostic performance of the Liver Imaging Reporting and Data System tumor in vein (LR-TIV) category at CT and/or MRI has not yet been evaluated, to the knowledge of the authors. Purpose To assess the diagnostic performance of the LR-TIV category in detecting macroscopic tumors in veins (TIVs) at CT and hepatobiliary contrast agent-enhanced (HBA) MRI, with pathologic results used as the reference standard. Materials and Methods Between January 2010 and December 2019, consecutive patients with or without macroscopic TIV who underwent both CT and HBA MRI before hepatic resection or liver transplant were retrospectively included. Three radiologists independently assessed the LR-TIV features of enhancing soft tissue in vein and features suggestive of TIV (FSTIV) and reached a consensus. Macroscopic TIV at pathologic examination was the reference standard. Sensitivities and specificities of the LR-TIV category without and with FSTIV were calculated, and the added value of FSTIV was evaluated by using the McNemar test. Results In the 1322 patients with (n = 101) or without (n = 1221) macroscopic TIV (median age, 64 years [interquartile range, 58-70 years]; 1053 men), without consideration of FSTIV, the sensitivity and specificity of enhancing soft tissue in vein for detecting macroscopic TIV at pathologic examination were 64.4% (65 of 101) and 99.8% (1218 of 1221) with CT and 62.4% (63 of 101) and 99.8% (1218 of 1221) with HBA MRI, respectively. With consideration of FSTIV, the sensitivity and specificity of the LR-TIV category became 67.3% (68 of 101 patients) and 99.7% (1217 of 1221 patients) at both CT and HBA MRI. No difference was found between measurements without and with FSTIV (sensitivity, 62% vs 67% for CT [P = .45] and 64% vs 67% for HBA MRI [P = .18]; specificity, 99% for both CT and HBA MRI [P > .99 for both]). Conclusion The Liver Imaging Reporting and Data System tumor in vein category showed moderate sensitivity and high specificity in the detection of macroscopic tumors in veins at both CT and hepatobiliary contrast agent-enhanced MRI, with pathologic examination used as the reference standard. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Morrell in this issue.

Simultaneous evaluation of perfusion and morphology using GRASP MRI in hepatic fibrosis.

OBJECTIVES: To determine if golden-angle radial sparse parallel (GRASP) dynamic contrast-enhanced (DCE)-MRI allows simultaneous evaluation of perfusion and morphology in liver fibrosis. METHODS: Participants who were scheduled for liver biopsy or resection were enrolled (NCT02480972). Images were reconstructed at 12-s temporal resolution for morphologic assessment and at 3.3-s temporal resolution for quantitative evaluation. The image quality of the morphologic images was assessed on a four-point scale, and the Liver Imaging Reporting and Data System score was recorded for hepatic observations. Comparisons were made between quantitative parameters of DCE-MRI for the different fibrosis stages, and for hepatocellular carcinoma (HCCs) with different LR features. RESULTS: DCE-MRI of 64 participants (male = 48) were analyzed. The overall image quality consistently stood at 3.5 ± 0.4 to 3.7 ± 0.4 throughout the exam. Portal blood flow significantly decreased in participants with F2-F3 (n = 18, 175 ± 110 mL/100 mL/min) and F4 (n = 12, 98 ± 47 mL/100 mL/min) compared with those in participants with F0-F1 (n = 34, 283 ± 178 mL/100 mL/min, p < 0.05 for all). In participants with F4, the arterial fraction and extracellular volume were significantly higher than those in participants with F0-F1 and F2-F3 (p < 0.05). Compared with HCCs showing non-LR-M features (n = 16), HCCs with LR-M (n = 5) had a significantly prolonged mean transit time and lower arterial blood flow (p < 0.05). CONCLUSIONS: Liver MRI using GRASP obtains both sufficient spatial resolution for confident diagnosis and high temporal resolution for pharmacokinetic modeling. Significant differences were found between the MRI-derived portal blood flow at different hepatic fibrosis stages. KEY POINTS: A single MRI examination is able to provide both images with sufficient spatial resolution for anatomic evaluation and those with high temporal resolution for pharmacokinetic modeling. Portal blood flow was significantly lower in clinically significant hepatic fibrosis and mean transit time and extracellular volume increased in cirrhosis, compared with those in no or mild hepatic fibrosis. HCCs with different LR features showed different quantitative parameters of DCE-MRI: longer mean transit time and lower arterial flow were observed in HCCs with LR-M features.

Prognostic significance of viable tumor size measurement in hepatocellular carcinomas after preoperative locoregional treatment.

BACKGROUND: Preoperative locoregional treatment (LRT) for hepatocellular carcinoma (HCC) often induces intratumoral necrosis without affecting the overall tumor size, and residual viable tumor size (VTS) on imaging is an important clinical parameter for assessing post-treatment response. However, for surgical specimens, it is unclear whether the VTS would be more relevant to prognosis compared to total tumor size (TTS). METHODS: A total of 142 surgically resected solitary HCC cases were retrospectively reviewed. The TTS and VTS were assessed by applying the modified Response Evaluation Criteria in Solid Tumors method to the resected specimens, and correlated with the clinicopathological features and survival. RESULTS: As applying VTS, 13/142 cases (9.2%) were down-staged to ypT1a. Although the survival analysis results for overall survival according to TTS or VTS were similar, VTS was superior to predict disease-free survival (DFS; p = .023) compared to TTS (p = .08). In addition, multivariate analysis demonstrated VTS > 2 cm to be an independent predictive factor for decreased DFS (p = .001). In the subpopulation of patients with LRT (n = 54), DFS in HCCs with TTS or VTS > 2 cm were significantly shorter than those with TTS or VTS ≤ 2 cm (p = .047 and p = .001, respectively). Interestingly, HCCs with TTS > 2 cm but down-staged to VTS ≤ 2 cm after preoperative LRT had similar survival to those with TTS ≤ 2 cm. CONCLUSIONS: Although the prognostic impact of tumor size was similar regardless of whether TTS or VTS was applied, reporting VTS may help to increase the number of candidates for surgery in HCC patients with preoperative LRT.

Development and operation of a digital platform for sharing pathology image data.

BACKGROUND: Artificial intelligence (AI) research is highly dependent on the nature of the data available. With the steady increase of AI applications in the medical field, the demand for quality medical data is increasing significantly. We here describe the development of a platform for providing and sharing digital pathology data to AI researchers, and highlight challenges to overcome in operating a sustainable platform in conjunction with pathologists. METHODS: Over 3000 pathological slides from five organs (liver, colon, prostate, pancreas and biliary tract, and kidney) in histologically confirmed tumor cases by pathology departments at three hospitals were selected for the dataset. After digitalizing the slides, tumor areas were annotated and overlaid onto the images by pathologists as the ground truth for AI training. To reduce the pathologists' workload, AI-assisted annotation was established in collaboration with university AI teams. RESULTS: A web-based data sharing platform was developed to share massive pathological image data in 2019. This platform includes 3100 images, and 5 pre-processing algorithms for AI researchers to easily load images into their learning models. DISCUSSION: Due to different regulations among countries for privacy protection, when releasing internationally shared learning platforms, it is considered to be most prudent to obtain consent from patients during data acquisition. CONCLUSIONS: Despite limitations encountered during platform development and model training, the present medical image sharing platform can steadily fulfill the high demand of AI developers for quality data. This study is expected to help other researchers intending to generate similar platforms that are more effective and accessible in the future.

Peritumoral lymph nodes in pancreatic cancer revisited; is it truly equivalent to lymph node metastasis?

BACKGROUND: Lymph node (LN) metastasis is a well-known poor prognostic factor of pancreatic cancer. LN metastasis, through direct invasion of tumor cell to peritumoral lymph nodes (PTLN), is treated as the same as those which spread through lymphatic channels. This study aimed to evaluate the impact of PTLN invasion on the oncologic outcome of pancreatic cancer. METHODS: Five hundred and six patients who underwent operation for pancreatic ductal adenocarcinoma from 2012 to 2018 were reviewed. PTLN invasion was defined as direct invasion of tumor cells in contact with main tumor. RESULTS: Among the 506 patients, 112 patients (22.1%) had PTLN invasion. PTLN invasion group (PTLNI) showed better disease-free survival than regional LN metastasis group (RLNM) and combined LN metastasis group (CLNM) (PTLNI 21 vs RLNM 11 vs CLNM 12 months, P = .003). There was no significant difference between N0 and PTLNI (PTLNI 21 vs N0 23 months, P = .999). In multivariate analysis, conventional LN metastasis was a significant factor compared to N0, but PTLN invasion was not (hazard ratio 0.786 [0.507-1.220], P = .283). CONCLUSION: Because PTLN invasion does not adversely affect survival in the same way as LN metastasis does, pancreatic cancer-may be overstaged if PTLN invasion were dealt in the same manner as a metastatic LN. Therefore, PTLN invasion should be disregarded from current nodal staging system.

Preoperative assessment of the resectability of pancreatic ductal adenocarcinoma on CT according to the NCCN Guidelines focusing on SMA/SMV branch invasion.

OBJECTIVES: For patients with pancreatic adenocarcinoma (PAC), adequate determination of disease extent is critical for optimal management. We aimed to evaluate diagnostic accuracy of CT in determining the resectability of PAC based on 2020 NCCN Guidelines. METHODS: We retrospectively enrolled 368 consecutive patients who underwent upfront surgery for PAC and preoperative pancreas protocol CT from January 2012 to December 2017. The resectability of PAC was assessed based on 2020 NCCN Guidelines and compared to 2017 NCCN Guidelines using chi-square tests. Overall survival (OS) was estimated using the Kaplan-Meier method and compared using log-rank test. R0 resection-associated factors were identified using logistic regression analysis. RESULTS: R0 rates were 80.8% (189/234), 67% (71/106), and 10.7% (3/28) for resectable, borderline resectable, and unresectable PAC according to 2020 NCCN Guidelines, respectively (p < 0.001). The estimated 3-year OS was 28.9% for borderline resectable PAC, which was significantly lower than for resectable PAC (43.6%) (p = 0.004) but significantly higher than for unresectable PAC (0.0%) (p < 0.001). R0 rate was significantly lower in patients with unresectable PAC according to 2020 NCCN Guidelines (10.7%, 3/28) than in those with unresectable PAC according to the previous version (31.7%, 20/63) (p = 0.038). In resectable PAC, tumor size ≥ 3 cm (p = 0.03) and abutment to portal vein (PV) (p = 0.04) were independently associated with margin-positive resection. CONCLUSIONS: The current NCCN Guidelines are useful for stratifying patients according to prognosis and perform better in R0 prediction in unresectable PAC than the previous version. Larger tumor size and abutment to PV were associated with margin-positive resection in patients with resectable PAC. KEY POINTS: • The updated 2020 NCCN Guidelines were useful for stratifying patients according to prognosis. • The updated 2020 NCCN Guidelines performed better in the prediction of margin-positive resection in unresectable cases than the previous version. • Tumor size ≥ 3 cm and abutment to the portal vein were associated with margin-positive resection in patients with resectable pancreatic adenocarcinoma.

Hepatic fibrosis grading with extracellular volume fraction from iodine mapping in spectral liver CT.

PURPOSE: To determine whether hepatic extracellular volume fraction (ECV) obtained from iodine density map (ECV-iodine) can be used to estimate hepatic fibrosis grade and to compare performance with ECV measured using Hounsfield units (ECV-HU). METHODS: From December 2016 to March 2019, patients who underwent liver resection or biopsy within four weeks after spectral liver CT were included. ECV-iodine and ECV-HU were calculated using the equilibrium phase. Within each of these, comparison of ECVs was made for different fibrosis grades (F0 - 1 vs. F2 - 3 vs. F4) and also for patients with compensated and decompensated cirrhosis. The diagnostic performance of ECVs in detecting clinically significant fibrosis (≥ F2) and cirrhosis (F4) was assessed using ROC analysis. RESULTS: A total of 144 patients (men = 98, mean age 58.1 ± 11.5 years) were included. The ECV-iodine value was significantly higher in cirrhosis (33.6 ± 6.8 %) than those with F0 - 1 (25.0 ± 3.7 %) or F2 - 3 (28.3 ± 3.4 %, P < 0.001 for all). It was significantly higher in decompensated cirrhosis than those with compensated cirrhosis (36.5 ± 7.2 % vs. 30.7 ± 5.0 %, respectively; P < 0.001). The AUC of ECV-iodine was 0.82 for detecting F2 or above (cut-off value, > 26.9 %) and 0.81 for detecting cirrhosis (cut-off value, > 29 %). ECV-iodine had a significantly higher AUC than ECV-HU for detecting F2 or above (AUC: 0.69, P < 0.001) and cirrhosis (AUC: 0.74, P = 0.04). CONCLUSIONS: ECV-iodine from spectral CT was able to detect clinically significant hepatic fibrosis and cirrhosis.

T2 gallbladder cancer shows substantial survival variation between continents and this is not due to histopathologic criteria or pathologic sampling differences.

Published data on survival of T2 gallbladder carcinoma (GBC) from different countries show a wide range of 5-year survival rates from 30-> 70%. Recently, studies have demonstrated substantial variation between countries in terms of their approach to sampling gallbladders, and furthermore, that pathologists from different continents apply highly variable criteria in determining stage of invasion in this organ. These findings raised the question of whether these variations in pathologic evaluation could account for the vastly different survival rates of T2 GBC reported in the literature. In this study, survival of 316 GBCs from three countries (Chile n = 137, South Korea n = 105, USA n = 74), all adequately sampled (with a minimum of five tumor sections examined) and histopathologically verified as pT2 (after consensus examination by expert pathologists from three continents), was analyzed. Chilean patients had a significantly worse prognosis based on 5-year all-cause mortality (HR: 1.89, 95% CI: 1.27-2.83, p = 0.002) and disease-specific mortality (HR: 2.41, 95% CI: 1.51-3.84, p < 0.001), compared to their South Korean counterparts, even when controlled for age and sex. Comparing the USA to South Korea, the survival differences in all-cause mortality (HR: 1.75, 95% CI: 1.12-2.75, p = 0.015) and disease-specific mortality (HR: 1.94, 95% CI: 1.14-3.31, p = 0.015) were also pronounced. The 3-year disease-specific survival rates in South Korea, the USA, and Chile were 75%, 65%, and 55%, respectively, the 5-year disease-specific survival rates were 60%, 50%, and 50%, respectively, and the overall 5-year survival rates were 55%, 45%, and 35%, respectively. In conclusion, the survival of true T2 GBC in properly classified cases is neither as good nor as bad as previously documented in the literature and shows notable geographic differences even in well-sampled cases with consensus histopathologic criteria. Future studies should focus on other potential reasons including biologic, etiopathogenetic, management-related, populational, or healthcare practice-related factors that may influence the survival differences of T2 GBC in different regions.

PAIP 2019: Liver cancer segmentation challenge.

Pathology Artificial Intelligence Platform (PAIP) is a free research platform in support of pathological artificial intelligence (AI). The main goal of the platform is to construct a high-quality pathology learning data set that will allow greater accessibility. The PAIP Liver Cancer Segmentation Challenge, organized in conjunction with the Medical Image Computing and Computer Assisted Intervention Society (MICCAI 2019), is the first image analysis challenge to apply PAIP datasets. The goal of the challenge was to evaluate new and existing algorithms for automated detection of liver cancer in whole-slide images (WSIs). Additionally, the PAIP of this year attempted to address potential future problems of AI applicability in clinical settings. In the challenge, participants were asked to use analytical data and statistical metrics to evaluate the performance of automated algorithms in two different tasks. The participants were given the two different tasks: Task 1 involved investigating Liver Cancer Segmentation and Task 2 involved investigating Viable Tumor Burden Estimation. There was a strong correlation between high performance of teams on both tasks, in which teams that performed well on Task 1 also performed well on Task 2. After evaluation, we summarized the top 11 team's algorithms. We then gave pathological implications on the easily predicted images for cancer segmentation and the challenging images for viable tumor burden estimation. Out of the 231 participants of the PAIP challenge datasets, a total of 64 were submitted from 28 team participants. The submitted algorithms predicted the automatic segmentation on the liver cancer with WSIs to an accuracy of a score estimation of 0.78. The PAIP challenge was created in an effort to combat the lack of research that has been done to address Liver cancer using digital pathology. It remains unclear of how the applicability of AI algorithms created during the challenge can affect clinical diagnoses. However, the results of this dataset and evaluation metric provided has the potential to aid the development and benchmarking of cancer diagnosis and segmentation.

Natural history and optimal treatment strategy of intraductal papillary mucinous neoplasm of the pancreas: Analysis using a nomogram and Markov decision model.

BACKGROUND/PURPOSE: With the increase in detection of intraductal papillary mucinous neoplasms (IPMN), a tailored approach is needed. This study was aimed at exploring the natural history of IPMN and suggest optimal treatment based on malignancy risk using a nomogram and Markov decision model. METHODS: Patients with IPMN who underwent surveillance or surgery were included. Changes in worrisome features/high-risk stigmata and malignancy conversion rate were assessed. Life expectancy and quality-adjusted life year (QALY) were compared using a nomogram predicting malignancy. RESULTS: Overall, 2006 patients with histologically confirmed or radiologically typical IPMN were enrolled. Of these, 1773 (88.4%), 81 (4.0%), and 152 (7.6%), respectively, had branch duct (BD)-, main duct-, and mixed-type IPMN at initial diagnosis. The cumulative risk of developing worrisome feature or high-risk stigmata was 19.0% and 35.0% at 5- and 10-year follow-up, respectively. The progression of malignancy rate at 10-year follow-up was 79.9% for main and mixed IPMNs and 5.9% for BD-IPMN. Nomogram-based malignancy risk prediction is well correlated with natural history based on pathologic biopsy and shows good stratification of survival. The decision model recommends surgery to maximize survival and QALY especially in those with >35% malignancy risk. CONCLUSIONS: Compared with main duct- and mixed-type IPMN, which have a high risk of malignancy (79.9%), BD-IPMN is very indolent (5.9%). The nomogram-based decision model suggests surgery rather than surveillance for patients with a high malignancy risk. The optimal treatment strategy between surgery and surveillance should consider patients' health status, malignancy risk, and centers' experience.