Tumor thickness as a novel risk factor for lymph node metastasis by superficial squamous cell carcinoma of head and neck.

Narrow-band imaging combined with magnified endoscopy has enabled the detection of superficial squamous cell carcinoma of the head and neck (SSCCHN) that has been resected with minimally invasive treatment, preserving vocalization and swallowing functions. However, risk factors of lymph node metastasis (LNM) must be identified, as some patients with LNM have a poor prognosis. From an initial 599 patients with 700 lesions who underwent trans-oral surgery in 27 Japanese hospitals (a nationwide registration survey), we enrolled 541 patients with 633 SSCCHNs, as indicated by central pathological diagnoses. All pathological specimens for each patient were examined using 20 pathological factors that are thought to affect the LNM of SSCCHN. In all, 24 (4.4%) of the 568 SSCCHNs exhibited LNM, and all 24 had at least one solitary nest of epithelial neoplastic cells present in the stroma, clearly separated from the intraepithelial carcinoma. Multivariate analysis also showed that tumor thickness (p = 0.0132, RR: 7.85, 95% confidence interval [CI]: 1.54-40.02), and an INFc pattern classified as infiltrating growth (INF) with unclear boundaries between tumor and non-tumor tissues (p = 0.0003, RR: 14.47, 3.46-60.46), and tumor budding (p = 0.0019, RR: 4.35, CI: 1.72-11.01) were significantly associated with LNM. Solitary nests may be indicative of LNM. In addition, tumor thickness was revealed to be a risk factor for LNM in SSCCHNs using pT factors that do not include an invasion depth element because of the anatomical absence of the muscularis mucosae.

Artificial Intelligence to Predict the Risk of Lymph Node Metastasis in T2 Colorectal Cancer.

OBJECTIVE: To develop and externally validate an updated artificial intelligence (AI) prediction system for stratifying the risk of lymph node metastasis (LNM) in T2 colorectal cancer (CRC). SUMMARY BACKGROUND DATA: Recent technical advances allow complete local excision of T2 CRC, traditionally treated with surgical resection. Yet, the widespread adoption of this approach is hampered by the inability to stratify the risk of LNM. METHODS: Data from pT2 CRC patients undergoing surgical resection between April 2000 and May 2022 at one Japanese and one Italian center were analyzed. Primary goal was AI system development for accurate LNM prediction. Predictors encompassed seven variables: age, sex, tumor size and location, lympho-vascular invasion, histological differentiation, and carcinoembryonic antigen level. The tool's discriminating power was assessed via Area Under the Curve (AUC), sensitivity, and specificity. RESULTS: Out of 735 initial patients, 692 were eligible. Training and validation cohorts comprised of 492 and 200 patients, respectively. The AI model displayed an AUC of 0.75 in the combined validation dataset. Sensitivity for LNM prediction was 97.8% and specificity was 15.6%. The Positive and the Negative Predictive Value were 25.7% and 96% respectively. The False Negative (FN) rate was 2.2%, the False Positive was 84.4%. CONCLUSIONS: Our AI model, based on easily accessible clinical and pathological variables, moderately predicts LNM in T2 CRC. However, the risk of FN needs to be considered. The training of the model including more patients across Western and Eastern centers -differentiating between colon and rectal cancers- may improve its performance and accuracy.

Automated Neutrophil Quantification and Histological Score Estimation in Ulcerative Colitis.

BACKGROUND: In the management of ulcerative colitis (UC), histological remission is increasingly recognized as the ultimate goal. The absence of neutrophil infiltration is crucial for assessing remission. This study aimed to develop an artificial intelligence (AI) system capable of accurately quantifying and localizing neutrophils in UC biopsy specimens to facilitate histological assessment. METHODS: Our AI system, which incorporates semantic segmentation and object detection models, was developed to identify neutrophils in hematoxylin and eosin-stained whole slide images. The system assessed the presence and location of neutrophils within either the epithelium or lamina propria and predicted components of the Nancy Histological Index and the PICaSSO Histologic Remission Index. We evaluated the system's performance against that of experienced pathologists and validated its ability to predict future clinical relapse risk in patients with clinically remitted UC. The primary outcome measure was the clinical relapse rate, defined as a partial Mayo score of ≥3. RESULTS: The model accurately identified neutrophils, achieving a performance of 0.77, 0.81, and 0.79 for precision, recall, and F-score, respectively. The system's histological score predictions showed a positive correlation with the pathologists' diagnoses (Spearman's ρ = 0.68-0.80; P < .05). Among patients who relapsed, the mean number of neutrophils in the rectum was higher than in those who did not relapse. Furthermore, the study highlighted that higher AI-based PICaSSO Histologic Remission Index and Nancy Histological Index scores were associated with hazard ratios increasing from 3.2 to 5.0 for evaluating the risk of UC relapse. CONCLUSIONS: The AI system's precise localization and quantification of neutrophils proved valuable for histological assessment and clinical prognosis stratification.

A novel artificial intelligence-assisted "vascular healing" diagnosis for prediction of future clinical relapse in patients with ulcerative colitis: a prospective cohort study (with video).

BACKGROUND AND AIMS: Image-enhanced endoscopy has attracted attention as a method for detecting inflammation and predicting outcomes in patients with ulcerative colitis (UC); however, the procedure requires specialist endoscopists. Artificial intelligence (AI)-assisted image-enhanced endoscopy may help nonexperts provide objective accurate predictions with the use of optical imaging. We aimed to develop a novel AI-based system using 8853 images from 167 patients with UC to diagnose "vascular-healing" and establish the role of AI-based vascular-healing for predicting the outcomes of patients with UC. METHODS: This open-label prospective cohort study analyzed data for 104 patients with UC in clinical remission. Endoscopists performed colonoscopy using the AI system, which identified the target mucosa as AI-based vascular-active or vascular-healing. Mayo endoscopic subscore (MES), AI outputs, and histologic assessment were recorded for 6 colorectal segments from each patient. Patients were followed up for 12 months. Clinical relapse was defined as a partial Mayo score >2 RESULTS: The clinical relapse rate was significantly higher in the AI-based vascular-active group (23.9% [16/67]) compared with the AI-based vascular-healing group (3.0% [1/33)]; P = .01). In a subanalysis predicting clinical relapse in patients with MES ≤1, the area under the receiver operating characteristic curve for the combination of complete endoscopic remission and vascular healing (0.70) was increased compared with that for complete endoscopic remission alone (0.65). CONCLUSIONS: AI-based vascular-healing diagnosis system may potentially be used to provide more confidence to physicians to accurately identify patients in remission of UC who would likely relapse rather than remain stable.

Efficacy of a whole slide image-based prediction model for lymph node metastasis in T1 colorectal cancer: A systematic review.

BACKGROUND AND AIM: Accurate stratification of the risk of lymph node metastasis (LNM) following endoscopic resection of submucosal invasive (T1) colorectal cancer (CRC) is imperative for determining the necessity for additional surgery. In this systematic review, we evaluated the efficacy of prediction of LNM by artificial intelligence (AI) models utilizing whole slide image (WSI) in patients with T1 CRC. METHODS: In accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, a systematic review was conducted through searches in PubMed (MEDLINE), Embase, and the Cochrane Library for relevant studies published up to December 2023. The inclusion criteria were studies assessing the accuracy of hematoxylin and eosin-stained WSI-based AI models for predicting LNM in patients with T1 CRC. RESULTS: Four studies met the criteria for inclusion in this systematic review. The area under the receiver operating characteristic curve for these AI models ranged from 0.57 to 0.76. In the three studies in which AI performance was compared directly with current treatment guidelines, AI consistently exhibited a higher area under the receiver operating characteristic curve. At a fixed sensitivity of 100%, specificities ranged from 18.4% to 45.0%. CONCLUSIONS: Artificial intelligence models based on WSI can potentially address the issue of diagnostic variability between pathologists and exceed the predictive accuracy of current guidelines. However, these findings require confirmation by larger studies that incorporate external validation.

Impact of computer-aided characterization for diagnosis of colorectal lesions, including sessile serrated lesions: Multireader, multicase study.

OBJECTIVES: Computer-aided characterization (CADx) may be used to implement optical biopsy strategies into colonoscopy practice; however, its impact on endoscopic diagnosis remains unknown. We aimed to evaluate the additional diagnostic value of CADx when used by endoscopists for assessing colorectal polyps. METHODS: This was a single-center, multicase, multireader, image-reading study using randomly extracted images of pathologically confirmed polyps resected between July 2021 and January 2022. Approved CADx that could predict two-tier classification (neoplastic or nonneoplastic) by analyzing narrow-band images of the polyps was used to obtain a CADx diagnosis. Participating endoscopists determined if the polyps were neoplastic or not and noted their confidence level using a computer-based, image-reading test. The test was conducted twice with a 4-week interval: the first test was conducted without CADx prediction and the second test with CADx prediction. Diagnostic performances for neoplasms were calculated using the pathological diagnosis as reference and performances with and without CADx prediction were compared. RESULTS: Five hundred polyps were randomly extracted from 385 patients and diagnosed by 14 endoscopists (including seven experts). The sensitivity for neoplasia was significantly improved by referring to CADx (89.4% vs. 95.6%). CADx also had incremental effects on the negative predictive value (69.3% vs. 84.3%), overall accuracy (87.2% vs. 91.8%), and high-confidence diagnosis rate (77.4% vs. 85.8%). However, there was no significant difference in specificity (80.1% vs. 78.9%). CONCLUSIONS: Computer-aided characterization has added diagnostic value for differentiating colorectal neoplasms and may improve the high-confidence diagnosis rate.

Whole slide image-based prediction of lymph node metastasis in T1 colorectal cancer using unsupervised artificial intelligence.

OBJECTIVES: Lymph node metastasis (LNM) prediction for T1 colorectal cancer (CRC) is critical for determining the need for surgery after endoscopic resection because LNM occurs in 10%. We aimed to develop a novel artificial intelligence (AI) system using whole slide images (WSIs) to predict LNM. METHODS: We conducted a retrospective single center study. To train and test the AI model, we included LNM status-confirmed T1 and T2 CRC between April 2001 and October 2021. These lesions were divided into two cohorts: training (T1 and T2) and testing (T1). WSIs were cropped into small patches and clustered by unsupervised K-means. The percentage of patches belonging to each cluster was calculated from each WSI. Each cluster's percentage, sex, and tumor location were extracted and learned using the random forest algorithm. We calculated the areas under the receiver operating characteristic curves (AUCs) to identify the LNM and the rate of over-surgery of the AI model and the guidelines. RESULTS: The training cohort contained 217 T1 and 268 T2 CRCs, while 100 T1 cases (LNM-positivity 15%) were the test cohort. The AUC of the AI system for the test cohort was 0.74 (95% confidence interval [CI] 0.58-0.86), and 0.52 (95% CI 0.50-0.55) using the guidelines criteria (P = 0.0028). This AI model could reduce the 21% of over-surgery compared to the guidelines. CONCLUSION: We developed a pathologist-independent predictive model for LNM in T1 CRC using WSI for determination of the need for surgery after endoscopic resection. TRIAL REGISTRATION: UMIN Clinical Trials Registry (UMIN000046992, https://center6.umin.ac.jp/cgi-open-bin/ctr/ctr_view.cgi?recptno=R000053590).

Evaluation in real-time use of artificial intelligence during colonoscopy to predict relapse of ulcerative colitis: a prospective study.

BACKGROUND AND AIMS: The use of artificial intelligence (AI) during colonoscopy is attracting attention as an endoscopist-independent tool to predict histologic disease activity of ulcerative colitis (UC). However, no study has evaluated the real-time use of AI to directly predict clinical relapse of UC. Hence, it is unclear whether the real-time use of AI during colonoscopy helps clinicians make real-time decisions regarding treatment interventions for patients with UC. This study aimed to establish the role of real-time AI in stratifying the relapse risk of patients with UC in clinical remission. METHODS: This open-label, prospective, cohort study was conducted in a referral center. The cohort comprised 145 consecutive patients with UC in clinical remission who underwent AI-assisted colonoscopy with a contact-microscopy function. We classified patients into either the Healing group or Active group based on the AI outputs during colonoscopy. The primary outcome measure was clinical relapse of UC (defined as a partial Mayo score >2) during 12 months of follow-up after colonoscopy. RESULTS: Overall, 135 patients completed the 12-month follow-up after AI-assisted colonoscopy. AI-assisted colonoscopy classified 61 patients as the Healing group and 74 as the Active group. The relapse rate was significantly higher in the AI-Active group (28.4% [21/74]; 95% confidence interval, 18.5%-40.1%) than in the AI-Healing group (4.9% [3/61]; 95% confidence interval, 1.0%-13.7%; P < .001). CONCLUSIONS: Real-time use of AI predicts the risk of clinical relapse in patients with UC in clinical remission, which helps clinicians make real-time decisions regarding treatment interventions. (Clinical trial registration number: UMIN000036650.).

Current problems and perspectives of pathological risk factors for lymph node metastasis in T1 colorectal cancer: Systematic review.

With the prevalence of endoscopic submucosal dissection and endoscopic full thickness resection, which enable complete resection of T1 colorectal cancer with a negative margin, the treatment strategy following endoscopic resection has become more important. The necessity of secondary surgical resection is determined on the basis of the risk of lymph node metastasis according to the histopathological findings of resected specimens because ~10% of T1 colorectal cancer cases have lymph node metastasis. The current Japanese treatment guidelines state four risk factors for lymph node metastasis: lymphovascular invasion, histological differentiation, depth of submucosal invasion, and tumor budding. These guidelines have succeeded in stratifying the low-risk group for lymph node metastasis, in which endoscopic resection alone is acceptable for cure. On the other hand, there are some problems: there is variation in diagnosis methods and low interobserver agreement for each pathological factor and 90% of surgical resections are unnecessary, with lymph node metastasis negativity. To ensure patients with T1 colorectal cancer receive more appropriate treatment, these problems should be addressed. In this systematic review, we gave some suggestions to these practical issues of four pathological factors as predictors.

Use of advanced endoscopic technology for optical characterization of neoplasia in patients with ulcerative colitis: Systematic review.

OBJECTIVES: Advances in endoscopic technology, including magnifying and image-enhanced techniques, have been attracting increasing attention for the optical characterization of colorectal lesions. These techniques are being implemented into clinical practice as cost-effective and real-time approaches. Additionally, with the recent progress in endoscopic interventions, endoscopic resection is gaining acceptance as a treatment option in patients with ulcerative colitis (UC). Therefore, accurate preoperative characterization of lesions is now required. However, lesion characterization in patients with UC may be difficult because UC is often affected by inflammation, and it may be characterized by a distinct "bottom-up" growth pattern, and even expert endoscopists have relatively little experience with such cases. In this systematic review, we assessed the current status and limitations of the use of optical characterization of lesions in patients with UC. METHODS: A literature search of online databases (MEDLINE via PubMed and CENTRAL via the Cochrane Library) was performed from 1 January 2000 to 30 November 2021. RESULTS: The database search initially identified 748 unique articles. Finally, 25 studies were included in the systematic review: 23 focused on differentiation of neoplasia from non-neoplasia, one focused on differentiation of UC-associated neoplasia from sporadic neoplasia, and one focused on differentiation of low-grade dysplasia from high-grade dysplasia and cancer. CONCLUSIONS: Optical characterization of neoplasia in patients with UC, even using advanced endoscopic technology, is still challenging and several issues remain to be addressed. We believe that the information revealed in this review will encourage researchers to commit to the improvement of optical diagnostics for UC-associated lesions.

Beyond complete endoscopic healing: Goblet appearance using an endocytoscope to predict future sustained clinical remission in ulcerative colitis.

OBJECTIVES: Complete endoscopic healing, defined as Mayo endoscopic score (MES) = 0, is an optimal target in the treatment of ulcerative colitis (UC). However, some patients with MES = 0 show clinical relapse within 12 months. Histologic goblet mucin depletion has emerged as a predictor of clinical relapse in patients with MES = 0. We observed goblet depletion in vivo using an endocytoscope, and analyzed the association between goblet appearance and future prognosis in UC patients. METHODS: In this retrospective cohort study, all enrolled UC patients had MES = 0 and confirmed clinical remission between October 2016 and March 2020. We classified the patients into two groups according to the goblet appearance status: preserved-goblet and depleted-goblet groups. We followed the patients until March 2021 and evaluated the difference in cumulative clinical relapse rates between the two groups. RESULTS: We identified 125 patients with MES = 0 as the study subjects. Five patients were subsequently excluded. Thus, we analyzed the data for 120 patients, of whom 39 were classified as the preserved-goblet group and 81 as the depleted-goblet group. The patients were followed-up for a median of 549 days. During follow-up, the depleted-goblet group had a significantly higher cumulative clinical relapse rate than the preserved-goblet group (19% [15/81] vs. 5% [2/39], respectively; P = 0.02). CONCLUSIONS: Observing goblet appearance in vivo allowed us to better predict the future prognosis of UC patients with MES = 0. This approach may assist clinicians with onsite decision-making regarding treatment interventions without a biopsy.

Combined endocytoscopy with pit pattern diagnosis in ulcerative colitis-associated neoplasia: Pilot study.

OBJECTIVES: Ulcerative colitis-associated neoplasias (UCAN) are often flat with an indistinct boundary from surrounding tissues, which makes differentiating UCAN from non-neoplasias difficult. Pit pattern (PIT) has been reported as one of the most effective indicators to identify UCAN. However, regenerated mucosa is also often diagnosed as a neoplastic PIT. Endocytoscopy (EC) allows visualization of cell nuclei. The aim of this retrospective study was to demonstrate the diagnostic ability of combined EC irregularly-formed nuclei with PIT (EC-IN-PIT) diagnosis to identify UCAN. METHODS: This study involved patients with ulcerative colitis whose lesions were observed by EC. Each lesion was diagnosed by two independent expert endoscopists, using two types of diagnostic strategies: PIT alone and EC-IN-PIT. We evaluated and compared the diagnostic abilities of PIT alone and EC-IN-PIT. We also examined the difference in the diagnostic abilities of an EC-IN-PIT diagnosis according to endoscopic inflammation severity. RESULTS: We analyzed 103 lesions from 62 patients; 23 lesions were UCAN and 80 were non-neoplastic. EC-IN-PIT diagnosis had a significantly higher specificity and accuracy compared with PIT alone: 84% versus 58% (P < 0.001), and 88% versus 67% (P < 0.01), respectively. The specificity and accuracy were significantly higher for Mayo endoscopic score (MES) 0-1 than MES 2-3: 93% versus 68% (P < 0.001) and 95% versus 74% (P < 0.001), respectively. CONCLUSIONS: Our novel EC-IN-PIT strategy had a better diagnostic ability than PIT alone to predict UCAN from suspected and initially detected lesions using conventional colonoscopy. UMIN clinical trial (UMIN000040698).

Recurrence of gastric cancer caused by implantation of tumor cells after curative endoscopic submucosal dissection.

A 93-year-old female underwent curative endoscopic submucosal dissection (ESD) for intramucosal gastric cancer (70 mm in diameter) in the antrum. The lesion showed an irregularly villous structure covered with mucus. En bloc resection was performed. The large resected specimen induced a longitudinal laceration on the right wall of the esophagogastric junction (EGJ) during retrieval. Unavoidably, we segmented the specimen in the stomach to facilitate retrieval. Histopathological evaluation of the specimen revealed well-to-moderately differentiated tubular and papillary adenocarcinoma. A new elevated lesion (15 mm in diameter) was found at the gastric side of the EGJ laceration scar 6 months after the first ESD, necessitating a second resection with ESD. Endoscopic, histopathological, and immunohistochemical features of the new lesion resembled those of the antral lesion. We assessed the new lesion as a recurrence of cancer caused by implantation of tumor cells in the mucosal laceration after ESD.We experienced recurrence caused by implantation of tumor cells in a mucosal laceration after curative gastric ESD. Endoscopist should be aware of the risk of implantation after gastric ESD.

A nationwide survey on esophageal gastrointestinal stromal tumors at accredited institutions by the Japan Esophageal Society.

BACKGROUND: As esophageal gastrointestinal stromal tumors (GISTs) are very rare, their clinicopathological features remain obscure. We conducted a nationwide survey to clarify the characteristics of these tumors and to establish a consensus on their diagnosis and treatment. METHODS: The clinicopathological information of patients with esophageal GISTs who underwent treatment between January 2010 and June 2016 at the accredited institutions by the Japan Esophageal Society was collected via a questionnaire method and analyzed statistically. RESULTS: Fifty-one patients (29 men and 22 women; median age, 68 years) were recruited from 31 institutions. Diagnosis was triggered most frequently during screening and other disease scrutiny. Symptoms were seen only in 17 patients: highest in 11 patients with dysphagia. Thirty-five patients underwent surgery alone; 15 patients, surgery with imatinib therapy; and one patient, endoscopic resection. The tumors preferentially occurred in the lower and middle parts of the thoracic esophagus, with a median size of 36.5 mm. Neoadjuvant and adjuvant imatinib therapies were performed in seven and eight patients, respectively. Administration of imatinib 400 mg/day was the standard regimen. Postoperative follow-up observations were conducted mostly via computed tomography (CT) scans every 3 or 6 months until 5 years after surgery. The tumors recurred in ten patients within 5 years postoperatively (high risk, 38.5%; intermediate risk, 20%; low risk, 0%; very low risk, 0%; three cases of relapse with an unknown risk assessment). A patient with a high-risk GIST died from the tumor 54 months after surgery. CONCLUSIONS: This nationwide survey revealed the current status of esophageal GISTs in Japan and provided important information for making a consensus on the treatment and follow-up method.

Distribution of Transplantation-Associated Thrombotic Microangiopathy (TA-TMA) and Comparison between Renal TA-TMA and Intestinal TA-TMA: Autopsy Study.

Transplantation-associated thrombotic microangiopathy (TA-TMA) is an important complication of hematopoietic stem cell transplantation. To date, information regarding the organs that are affected by TA-TMA as confirmed histologically remains limited; the clinicopathologic differences between renal TA-TMA and intestinal TA-TMA have not been examined despite being the well-known and commonly affected sites of TA-TMA. We therefore examined 165 autopsied patients after hematopoietic stem cell transplantation and compared the clinicopathologic factors of renal and intestinal TA-TMA. It was clear that 38 (23%) of our patients had TA-TMA. In the TA-TMA cases, the kidney (61%) and intestine (53%) were commonly affected, and the ileum and right colon were vulnerable. Other organs that we found to be affected by TA-TMA included the stomach (8%), gallbladder (5%), and oral cavity, pharynx, esophagus, liver, heart, urinary bladder, and ureter (all at 3%), and symptoms thought to be caused by TA-TMA of these organs were not observed in any patient. Histologically, TA-TMA only affected the arteriole, or small arteries, regardless of the organ, and the veins or larger arteries were not affected at all. In the kidney, the glomerular capillary was also affected, and mesangiolysis and double contours of the basement membranes were often in evidence. The histologic overlap of renal and intestinal TA-TMA was rare (13%), and the patients in the intestinal TA-TMA group exhibited more frequency of a history of intestinal acute graft-versus-host disease (GVHD) during the clinical course compared with that of the renal TA-TMA group (80% versus 22%, P = .0016). Although TA-TMA can affect many other organs, the frequency of these ancillary events was low, and the clinical effect may have been small. Our results suggest that in comparison to renal TA-TMA, intestinal GVHD could be more closely associated with intestinal TA-TMA as a risk factor.

Histopathological study on the prevalence of trichosporonosis in formalin-fixed and paraffin-embedded tissue autopsy sections by in situ hybridization with peptide nucleic acid probe.

Trichosporon species are some of the most common pathogenic yeasts in Asia, and many are resistant to echinocandin antifungal drugs. Effective treatment of fungal infections requires the selection of appropriate antifungals and the accurate identification of the causal organism. However, in histopathological specimens Trichosporon spp. are often misidentified as Candida species due to morphological similarities. In situ hybridization (ISH) is a useful technique for identifying fungal species in formalin-fixed and paraffin-embedded (FFPE) tissue sections. Although many novel probes for ISH are available, the practical use of ISH for identification of fungi remains limited, in part due to the lack of adequate verifications. We conducted a two-center retrospective observational study in which the ISH technique was used to differentiate Trichosporon spp. and C. albicans in FFPE tissue from autopsy specimens. The study included 88 cases with blood stream yeast infection without Cryptococci extracted from 459 autopsy files of cases with proven invasive fungal infection (IFI). Positive signals for the Trichosporon spp. protein nucleic acid (PNA) probe and C. albicans PNA probe were seen for 7 and 35 cases, respectively, whereas the remaining 46 were negative for both. For the Trichosporon spp.- positive specimens, 5/7 were reported as candidiasis in autopsy records. Our results suggested that accurate histological identification of fungal infections remains challenging, but ISH may be a suitable approach to support histological findings. In addition, this retrospective study suggested that trichosporonosis may have high prevalence among cases of bloodstream yeast infections in Japan.

Anterior enterocele immediately after cystectomy: A case report.

An enterocele is a peritoneal herniation through or into the vagina, typically as a posterior enterocele, which develops in the rectovaginal space (pouch of Douglas or cul-de-sac). An anterior enterocele in the vesicovaginal space is a rare condition, but a possible complication after cystectomy or hysterectomy. Herein, we report a rare case of anterior enterocele after cystectomy, which required semi-urgent intervention. The patient was a 78-year-old woman (gravida 2, para 2) who underwent laparoscopic radical cystectomy for bladder carcinoma 3 months earlier. Vaginal examination showed a large stage-3 anterior enterocele without the covering vaginal wall. A transvaginal surgery was performed to repair the vagina. Mesh and Martius flaps were needed to repair the vaginal defect. In conclusion, an anterior enterocele must be suspected when pelvic organ prolapse occurs after cystectomy, and surgical repair should be performed as soon as possible because an enterocele that lacks vaginal wall covering is at high risk of rupture.

Endocytoscopic intramucosal capillary network changes and crypt architecture abnormalities can predict relapse in patients with an ulcerative colitis Mayo endoscopic score of 1.

OBJECTIVES: Recent studies have suggested the necessity of therapeutic intervention for patients with ulcerative colitis at high risk of clinical relapse with a Mayo endoscopic score (MES) of 1. The aim of this retrospective cohort study was to demonstrate the impact of intramucosal capillary network changes and crypt architecture abnormalities to stratify the risk of relapse in patients with an MES of 1. METHODS: All included patients had an MES of ≤1 and confirmed sustained clinical remission between October 2016 and April 2019. We classified patients with an MES of 1 as "intramucosal capillary/crypt (ICC)-active" or "ICC-inactive" using endocytoscopic evaluation. We followed patients until October 2019 or until relapse; the main outcome measure was the difference in clinical relapse-free rates between ICC-active and ICC-inactive patients with an MES of 1. RESULTS: We included 224 patients and analyzed data for 218 (82 ICC-active and 54 ICC-active with an MES of 1 and 82 with an MES of 0). During follow-up, among the patients with an MES of 1, 30.5% (95% confidence interval 20.8-41.6; 25/82) of the patients relapsed in the ICC-active group and 5.6% (95% confidence interval 1.2-15.4; 3/54) of the patients relapsed in the ICC-inactive group. The ICC-inactive group had a significantly higher clinical relapse-free rate compared with the ICC-active group (P < 0.01). CONCLUSIONS: In vivo intramucosal capillary network and crypt architecture patterns stratified the risk of clinical relapse in patients with an MES of 1 (UMIN 000032580; UMIN 000036359).

Immunohistochemical analysis of tumor budding as predictor of lymph node metastasis from superficial esophageal squamous cell carcinoma.

BACKGROUND: Tumor budding is known predictors of lymph node metastasis from esophageal squamous cell carcinoma. However, it is not easy to detect such small cell clusters on hematoxylin-eosin (HE) staining. Therefore, we evaluated tumor budding using immunohistochemistry (IHC) for epithelial cell markers. METHOD: We analyzed tumor budding in 50 cases of superficial esophageal squamous cell carcinoma. We evaluated the impact of clinicopathological factors and tumor budding to predict lymph node metastasis. A total of 565 tumor sections were assessed using HE staining and IHC for cytokeratin 5/6. RESULTS: Based on receiver operating characteristic curves, the cut-off values for high-grade tumor budding evaluated using HE staining or IHC were 2 and 11, respectively. High-grade tumor budding evaluated using HE staining (P = 0.007) and IHC (P ≤ 0.001) were significantly correlated with lymph node metastasis. For tumors with pT1a-MM to pT1b-SM1, high-grade tumor budding evaluated using IHC was correlated with lymph node metastasis (P = 0.050). CONCLUSIONS: Tumor budding was significantly associated with lymph node metastasis. The optimal cut-off values of tumor budding on HE staining and tumor budding on IHC were 2 and 11, respectively. Even though both tumor budding on HE staining and tumor budding on IHC were significantly associated with lymph node metastasis, tumor budding on IHC tend to be more associated with lymph node metastasis.

Vasa recta hyalinosis reflects severe arteriolopathy in renal allografts.

AIM: We examined the clinicopathologic significance of hyalinosis in the vasa recta in the medulla of allograft kidney biopsies. METHOD: We analyzed biopsy specimens from January 2010 to December 2015, obtained from both the cortex and medulla (including the vasa recta) ≥ 1 year after living-donor kidney transplantation. We excluded biopsy specimens from recipients who had undergone transplantation due to diabetic nephropathy or who had diabetes mellitus after transplantation. We evaluated hyaline arteriolopathy in the cortex using the aah score determined by the Banff 2007 classification. RESULT: Among 381 biopsy specimens obtained from 248 transplant recipients ≥ 1 year after transplantation, 36 specimens obtained from 34 recipients showed vasa recta hyalinosis (VRH) in the medulla. Among these 36 specimens, 17 had a score of aah3, 16 had a score of aah2, and 3 had a score of aah1. The incidence of VRH was 1.9% at ≥ 1 to < 4 years, 7.1% at ≥ 4 to < 8 years, and 50.0% at ≥ 8 years. The aah scores and the proportion of hyalinosis in the arteriolar media among all muscular arterioles in the cortex were significantly higher in the VRH group at ≥ 8 years in the late-phase biopsy (P < 0.01). The graft survival was worse in the VRH group (P = 0.024), although there was no significant difference in the graft survival between the ≥ aah2 and < aah2 groups at ≥ 8 years in the late-phase biopsy (P = 0.159). CONCLUSION: VRH in renal allografts reflects severe arteriolopathy of the cortex. VRH in the late-phase biopsy may be a prognostic factor for graft survival.