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1.
Gastrointest Endosc ; 2024 Jan 10.
Artigo em Inglês | MEDLINE | ID: mdl-38215859

RESUMO

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.

2.
Dig Endosc ; 36(3): 341-350, 2024 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-37937532

RESUMO

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.


Assuntos
Pólipos do Colo , Neoplasias Colorretais , Humanos , Pólipos do Colo/diagnóstico , Pólipos do Colo/patologia , Colonoscopia/métodos , Neoplasias Colorretais/diagnóstico , Neoplasias Colorretais/cirurgia , Neoplasias Colorretais/patologia , Valor Preditivo dos Testes , Computadores , Imagem de Banda Estreita/métodos
3.
DEN Open ; 4(1): e324, 2024 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-38155928

RESUMO

Objectives: Japanese guidelines include high-grade (poorly differentiated) tumors as a risk factor for lymph node metastasis (LNM) in T1 colorectal cancer (CRC). However, whether the grading is based on the least or most predominant component when the lesion consists of two or more levels of differentiation varies among institutions. This study aimed to investigate which method is optimal for assessing the risk of LNM in T1 CRC. Methods: We retrospectively evaluated 971 consecutive patients with T1 CRC who underwent initial or additional surgical resection from 2001 to 2021 at our institution. Tumor grading was divided into low-grade (well- to moderately differentiated) and high-grade based on the least or predominant differentiation analyses. We investigated the correlations between LNM and these two grading analyses. Results: LNM was present in 9.8% of patients. High-grade tumors, as determined by least differentiation analysis, accounted for 17.0%, compared to 0.8% identified by predominant differentiation analysis. A significant association with LNM was noted for the least differentiation method (p < 0.05), while no such association was found for predominant differentiation (p = 0.18). In multivariate logistic regression, grading based on least differentiation was an independent predictor of LNM (p = 0.04, odds ratio 1.68, 95% confidence interval 1.00-2.83). Sensitivity and specificity for detecting LNM were 27.4% and 84.1% for least differentiation, and 2.1% and 99.3% for predominant differentiation, respectively. Conclusions: Tumor grading via least differentiation analysis proved to be a more reliable measure for assessing LNM risk in T1 CRC compared to grading by predominant differentiation.

4.
Pathol Res Pract ; 246: 154498, 2023 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-37207529

RESUMO

BACKGROUND: The histology of the cardiac mucosa at the esophagogastric junction (EGJ) at birth is still a controversy. We conducted a histopathological study of the EGJ to clarify the morphology, and to determine the presence or absence of cardiac mucosa at birth. SUBJECTS: We examined 43 Japanese neonates and infants that are born prematurely or at full term. Death had occurred between 1 and 231 days after birth. RESULTS: Cardiac mucosa without parietal cells showing positivity for anti-proton pump antibody, adjacent to the most distal squamous epithelium, was observed in 32 (74%) of the 43cases. Such mucosa was evident in neonates that were full-term and had died within 14 days after birth. On the other hand, cardiac mucosa with parietal cells adjacent to squamous epithelium was noted in 10 cases (23%); the remaining one (2%) had columnar-lined esophagus. Squamous and columnar islands were observed in a single histological section from the EGJ in 22 (51%) of the 43 cases. Parietal cells were sparsely or densely present in the gastric antral mucosa. CONCLUSIONS: On the basis of these histological findings, we consider that cardiac mucosa exists in neonates and infants and can be defined as such, irrespective of the presence or absence of parietal cells (so-called oxyntocardiac mucosa). Neonates born prematurely or at full-term have cardiac mucosa in the EGJ just after birth, as is the case for Caucasian neonates.


Assuntos
Esôfago de Barrett , Carcinoma de Células Escamosas , Recém-Nascido , Humanos , Mucosa/patologia , Junção Esofagogástrica/patologia , Esôfago de Barrett/patologia , Epitélio/patologia , Carcinoma de Células Escamosas/patologia , Mucosa Gástrica/patologia
5.
Dig Endosc ; 35(7): 902-908, 2023 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-36905308

RESUMO

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).


Assuntos
Inteligência Artificial , Neoplasias Colorretais , Humanos , Metástase Linfática/patologia , Estudos Retrospectivos , Endoscopia , Neoplasias Colorretais/cirurgia , Neoplasias Colorretais/patologia , Linfonodos/patologia
7.
PLoS One ; 17(10): e0273566, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36264865

RESUMO

BACKGROUND: Colorectal cancer (CRC) can be classified into four consensus molecular subtypes (CMS) according to genomic aberrations and gene expression profiles. CMS is expected to be useful in predicting prognosis and selecting chemotherapy regimens. However, there are still no reports on the relationship between the morphology and CMS. METHODS: This retrospective study included 55 subjects with T2 CRC undergoing surgical resection, of whom 30 had the depressed type and 25 the protruded type. In the classification of the CMS, we first defined cases with deficient mismatch repair as CMS1. And then, CMS2/3 and CMS4 were classified using an online classifier developed by Trinh et al. The staining intensity of CDX2, HTR2B, FRMD6, ZEB1, and KER and the percentage contents of CDX2, FRMD6, and KER are input into the classifier to obtain automatic output classifying the specimen as CMS2/3 or CMS4. RESULTS: According to the results yielded by the online classifier, of the 30 depressed-type cases, 15 (50%) were classified as CMS2/3 and 15 (50%) as CMS4. Of the 25 protruded-type cases, 3 (12%) were classified as CMS1 and 22 (88%) as CMS2/3. All of the T2 CRCs classified as CMS4 were depressed CRCs. More malignant pathological findings such as lymphatic invasion were associated with the depressed rather than protruded T2 CRC cases. CONCLUSIONS: Depressed-type T2 CRC had a significant association with CMS4, showing more malignant pathological findings such as lymphatic invasion than the protruded-type, which could explain the reported association between CMS4 CRC and poor prognosis.


Assuntos
Neoplasias Colorretais , Humanos , Biomarcadores Tumorais/genética , Neoplasias Colorretais/patologia , Prognóstico , Estudos Retrospectivos , Transcriptoma
8.
J Gastroenterol ; 57(12): 962-970, 2022 12.
Artigo em Inglês | MEDLINE | ID: mdl-36184701

RESUMO

BACKGROUND: Mucin depletion is one of the histological indicators of clinical relapse among patients with ulcerative colitis (UC). Mucin depletion is evaluated semiquantitatively by pathologists using histological images. Therefore, the interobserver concordance is not extremely high, and an objective evaluation method is needed. This study was conducted to demonstrate that our automated quantitative method using a deep learning-based model is useful in predicting the prognosis of patients with UC. METHODS: Deep learning-based models were trained to detect goblet cell mucus area from whole slide images of biopsy specimens. This study involved 114 patients with UC in endoscopic remission with a partial Mayo score of ≤ 1. Biopsy specimens were collected during colonoscopy, and the ratio of goblet cell mucus area to the epithelial cell and goblet cell mucus area was calculated as goblet cell ratio (GCR). The follow-up time was 12 months, and the primary outcome was the relapse rate. Clinical relapse was defined as partial Mayo score of ≥ 3. RESULTS: Sixteen patients (14%) experienced clinical relapse. In the relapsed group, the GCRs of specimens obtained from the cecum, ascending colon, and rectum were significantly lower than those of specimens in the relapse-free group (p = 0.010, p = 0.027, p < 0.01). In the rectum, patients with a GCR of ≤ 12% had a significantly higher relapse rate than those with a GCR of > 12% (45% [10/22] vs. 6.5% [6/92]; p < 0.01). CONCLUSIONS: Quantifying goblet cell mucus areas using a deep learning-based model is useful in predicting the clinical relapse in patients with UC in clinical and endoscopic remission.


Assuntos
Colite Ulcerativa , Aprendizado Profundo , Células Caliciformes , Mucinas , Humanos , Colite Ulcerativa/diagnóstico por imagem , Colite Ulcerativa/patologia , Colonoscopia , Células Caliciformes/patologia , Mucosa Intestinal/diagnóstico por imagem , Mucosa Intestinal/patologia , Mucinas/deficiência , Muco , Recidiva , Indução de Remissão , Índice de Gravidade de Doença
10.
Dig Endosc ; 34(7): 1297-1310, 2022 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-35445457

RESUMO

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.


Assuntos
Colite Ulcerativa , Neoplasias Colorretais , Neoplasias , Humanos , Colite Ulcerativa/diagnóstico , Colite Ulcerativa/cirurgia , Colite Ulcerativa/complicações , Colonoscopia/métodos , Hiperplasia/complicações , Tecnologia , Neoplasias Colorretais/diagnóstico , Neoplasias Colorretais/etiologia , Neoplasias Colorretais/cirurgia
11.
Gastrointest Endosc ; 95(4): 747-756.e2, 2022 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-34695422

RESUMO

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.).


Assuntos
Colite Ulcerativa , Inteligência Artificial , Estudos de Coortes , Colite Ulcerativa/diagnóstico por imagem , Colite Ulcerativa/tratamento farmacológico , Colonoscopia , Humanos , Mucosa Intestinal/patologia , Estudos Prospectivos , Recidiva , Índice de Gravidade de Doença
12.
Dig Endosc ; 34(1): 133-143, 2022 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-33641190

RESUMO

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).


Assuntos
Colite Ulcerativa , Neoplasias Colorretais , Colite Ulcerativa/diagnóstico por imagem , Colonoscopia , Humanos , Projetos Piloto , Estudos Retrospectivos
13.
Dig Endosc ; 34(5): 1030-1039, 2022 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-34816494

RESUMO

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.


Assuntos
Colite Ulcerativa , Colite Ulcerativa/patologia , Colonoscopia , Humanos , Mucosa Intestinal/patologia , Recidiva , Estudos Retrospectivos , Índice de Gravidade de Doença
14.
Dig Endosc ; 34(5): 901-912, 2022 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-34942683

RESUMO

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.


Assuntos
Neoplasias Colorretais , Ressecção Endoscópica de Mucosa , Neoplasias Colorretais/patologia , Neoplasias Colorretais/cirurgia , Humanos , Linfonodos/patologia , Linfonodos/cirurgia , Metástase Linfática , Invasividade Neoplásica/patologia , Estudos Retrospectivos , Fatores de Risco
15.
NEJM Evid ; 1(6): EVIDoa2200003, 2022 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-38319238

RESUMO

Real-Time AI-Based Diagnosis of Neoplastic PolypsColonoscopists diagnosed small colonic polyps as benign or malignant on the basis of their appearance. The results were compared in real time to see if CADx could distinguish among polyps requiring removal. For standard visual inspection versus CADx, we determined sensitivity for diagnosis (88.4% vs. 90.4%) and high confidence in assessment (74.2% vs. 92.6%).

16.
World J Clin Cases ; 9(33): 10088-10097, 2021 Nov 26.
Artigo em Inglês | MEDLINE | ID: mdl-34904078

RESUMO

BACKGROUND: Although small colorectal neoplasms (< 10 mm) are often easily resected endoscopically and are considered to have less malignant potential compared with large neoplasms (≥ 10 mm), some are invasive to the submucosa. AIM: To clarify the clinicopathological features of small T1 colorectal cancers. METHODS: Of 32025 colorectal lesions between April 2001 and March 2018, a total of 1152 T1 colorectal cancers resected endoscopically or surgically were included in this study and were divided into two groups by tumor size: a small group (< 10 mm) and a large group (≥ 10 mm). We compared clinicopathological factors including lymph node metastasis (LNM) between the two groups. RESULTS: The incidence of small T1 cancers was 10.1% (116/1152). The percentage of initial endoscopic treatment in small group was significantly higher than in large group (< 10 mm 74.1% vs ≥ 10 mm 60.2%, P < 0.01). In the surgical resection cohort (n = 798), the rate of LNM did not significantly differ between the two groups (small 12.3% vs large 10.9%, P = 0.70). In addition, there were also no significant differences between the two groups in pathological factors such as histological grade, vascular invasion, or lymphatic invasion. CONCLUSION: Because there was no significant difference in the rate of LNM between small and large T1 colorectal cancers, the requirement for additional surgical resection should be determined according to pathological findings, regardless of tumor size.

17.
Respirol Case Rep ; 9(9): e0830, 2021 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-34430032

RESUMO

It is important to distinguish tumour recurrence from other conditions that could show high accumulation on 18F-fluorodeoxyglucose-positron emission tomography (FDG-PET). We describe the case of a 78-year-old woman who underwent partial resection of the left lower lung lobe for carcinoid treatment 20 years previously. Five years earlier, chest radiography revealed an abnormal shadow, and chest computed tomography (CT) showed partial atelectasis in the left S8. Periodical CT showed that the atelectasis had developed into a mass. The patient was referred to our hospital. A mass of 45 mm diameter was detected on CT and it had a maximum standardized uptake value of 8.91 on FDG-PET. We suspected recurrence and performed surgery. Pathological examination revealed epithelioid cell granuloma (maximum diameter, 25 mm) with necrosis. Tissue culture showed no evidence of Mycobacterium tuberculosis. However, serum anti-MAC antibody level was elevated, suggesting epithelioid cell granuloma caused by non-tuberculous Mycobacterium infection.

18.
Endosc Int Open ; 9(7): E1004-E1011, 2021 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-34222622

RESUMO

Background and study aims Large adenomas are sometimes misidentified as cancers during colonoscopy and are surgically removed. To address this overtreatment, we developed an artificial intelligence (AI) tool that identified cancerous pathology in vivo with high specificity. We evaluated our AI tool under the supervision of a government agency to obtain regulatory approval. Patients and methods The AI tool outputted three pathological class predictions (cancer, adenoma, or non-neoplastic) for endocytoscopic images obtained at 520-fold magnification and previously trained on 68,082 images from six academic centers. A validation test was developed, employing 500 endocytoscopic images taken from various parts of randomly selected 50 large (≥ 20 mm) colorectal lesions (10 images per lesion). An expert board labelled each of the 500 images with a histopathological diagnosis, which was made using endoscopic and histopathological images. The validation test was performed using the AI tool under a controlled environment. The primary outcome measure was the specificity in identifying cancer. Results The validation test consisted of 30 cancers, 15 adenomas, and five non-neoplastic lesions. The AI tool could analyze 83.6 % of the images (418/500): 231 cancers, 152 adenomas, and 35 non-neoplastic lesions. Among the analyzable images, the AI tool identified the three pathological classes with an overall accuracy of 91.9 % (384/418, 95 % confidence interval [CI]: 88.8 %-94.3 %). Its sensitivity and specificity for differentiating cancer was 91.8 % (212/231, 95 % CI: 87.5 %-95.0 %) and 97.3 % (182/187, 95 % CI: 93.9 %-99.1 %), respectively. Conclusions The newly developed AI system designed for endocytoscopy showed excellent specificity in identifying colorectal cancer.

19.
Cancer Med ; 10(12): 3848-3861, 2021 06.
Artigo em Inglês | MEDLINE | ID: mdl-33991076

RESUMO

Head and neck cancers, especially in hypopharynx and oropharynx, are often detected at advanced stage with poor prognosis. Narrow band imaging enables detection of superficial cancers and transoral surgery is performed with curative intent. However, pathological evaluation and real-world safety and clinical outcomes have not been clearly understood. The aim of this nationwide multicenter study was to investigate the safety and efficacy of transoral surgery for superficial head and neck cancer. We collected the patients with superficial head and neck squamous cell carcinoma who were treated by transoral surgery from 27 hospitals in Japan. Central pathology review was undertaken on all of the resected specimens. The primary objective was effectiveness of transoral surgery, and the secondary objective was safety including incidence and severity of adverse events. Among the 568 patients, a total of 662 lesions were primarily treated by 575 sessions of transoral surgery. The median tumor diameter was 12 mm (range 1-75) endoscopically. Among the lesions, 57.4% were diagnosed as squamous cell carcinoma in situ. The median procedure time was 48 minutes (range 2-357). Adverse events occurred in 12.7%. Life-threatening complications occurred in 0.5%, but there were no treatment-related deaths. During a median follow-up period of 46.1 months (range 1-113), the 3-year overall survival rate, relapse-free survival rate, cause-specific survival rate, and larynx-preservation survival rate were 88.1%, 84.4%, 99.6%, and 87.5%, respectively. Transoral surgery for superficial head and neck cancer offers effective minimally invasive treatment. Clinical trials registry number: UMIN000008276.


Assuntos
Neoplasias de Cabeça e Pescoço/cirurgia , Carcinoma de Células Escamosas de Cabeça e Pescoço/cirurgia , Adulto , Idoso , Idoso de 80 Anos ou mais , Carcinoma in Situ/patologia , Carcinoma in Situ/cirurgia , Intervalo Livre de Doença , Feminino , Neoplasias de Cabeça e Pescoço/mortalidade , Neoplasias de Cabeça e Pescoço/patologia , Humanos , Incidência , Japão , Laringe , Masculino , Pessoa de Meia-Idade , Cirurgia Endoscópica por Orifício Natural , Segunda Neoplasia Primária/epidemiologia , Duração da Cirurgia , Tratamentos com Preservação do Órgão/estatística & dados numéricos , Complicações Pós-Operatórias/epidemiologia , Estudos Retrospectivos , Índice de Gravidade de Doença , Carcinoma de Células Escamosas de Cabeça e Pescoço/mortalidade , Carcinoma de Células Escamosas de Cabeça e Pescoço/patologia , Taxa de Sobrevida , Carga Tumoral
20.
Esophagus ; 18(3): 451-460, 2021 07.
Artigo em Inglês | MEDLINE | ID: mdl-33928490

RESUMO

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.


Assuntos
Tumores do Estroma Gastrointestinal , Idoso , Esôfago/patologia , Feminino , Tumores do Estroma Gastrointestinal/diagnóstico , Tumores do Estroma Gastrointestinal/epidemiologia , Tumores do Estroma Gastrointestinal/terapia , Humanos , Japão/epidemiologia , Masculino , Recidiva Local de Neoplasia , Inquéritos e Questionários
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