Clinical and pathological diagnosis and comparison of benign and malignant eyelid tumors

Background: Gastrointestinal stromal tumors (GISTs) are mesenchymal tumors and have some malignant potential. Mitotic count is important for predicting the malignant potential of GISTs. Proper treatment of GISTs requires accurate pathological diagnosis. In general, endoscopic ultrasound-guided fine-needle aspiration and deep biopsy are used for pathological diagnosis of GIST before making decisions about surgery. This study sought to evaluate the pathological uniformity of gastric GISTs for mitotic index of the center and periphery of the GIST. Methods: We retrospectively reviewed the data of 37 gastric GIST patients who underwent wedge resection at Hanyang University Hospital. We used Armed Forces Institute of Pathology criteria to classify gastric GISTs. To determine the pathological uniformity of gastric GISTs, we compared GIST risk stratification between the center and periphery of GISTs. Results: The mean size of GISTs was 3.56 ± 2.10 cm. Three lesions were located in the antrum, 11 in the fundus, 9 in the cardia, and 14 in the body. The mean age of patients was 58.65 ± 9.44 years; 18 patients were male and 19 were female. Thirty-five patients (94.6%) showed the same level of risk stratification between the center and periphery of gastric GISTs, while two patients (5.4%) presented different levels of risk between the two sites. No significant difference in mitotic count was observed between the two sites (kappa value = 0.863; p = 0.001). Conclusions: Mitotic index category (either more than five mitoses per high-power field or five or fewer mitoses per high-power field) of GISTs showed good concurrence between the center and periphery.

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Real-time intraoperative glioma diagnosis using fluorescence imaging and deep convolutional neural networks

European Journal of Nuclear Medicine and Molecular Imaging ◽

10.1007/s00259-021-05326-y ◽

2021 ◽

Author(s):

Biluo Shen ◽

Zhe Zhang ◽

Xiaojing Shi ◽

Caiguang Cao ◽

Zeyu Zhang ◽

...

Keyword(s):

Neural Networks ◽

Real Time ◽

Fluorescence Imaging ◽

Convolutional Neural Networks ◽

Frozen Section ◽

Fluorescent Imaging ◽

Pathological Diagnosis ◽

Pathological Examination ◽

Deep Convolutional Neural Networks ◽

Fluorescence Images

Abstract Purpose Surgery is the predominant treatment modality of human glioma but suffers difficulty on clearly identifying tumor boundaries in clinic. Conventional practice involves neurosurgeon’s visual evaluation and intraoperative histological examination of dissected tissues using frozen section, which is time-consuming and complex. The aim of this study was to develop fluorescent imaging coupled with artificial intelligence technique to quickly and accurately determine glioma in real-time during surgery. Methods Glioma patients (N = 23) were enrolled and injected with indocyanine green for fluorescence image–guided surgery. Tissue samples (N = 1874) were harvested from surgery of these patients, and the second near-infrared window (NIR-II, 1000–1700 nm) fluorescence images were obtained. Deep convolutional neural networks (CNNs) combined with NIR-II fluorescence imaging (named as FL-CNN) were explored to automatically provide pathological diagnosis of glioma in situ in real-time during patient surgery. The pathological examination results were used as the gold standard. Results The developed FL-CNN achieved the area under the curve (AUC) of 0.945. Comparing to neurosurgeons’ judgment, with the same level of specificity >80%, FL-CNN achieved a much higher sensitivity (93.8% versus 82.0%, P < 0.001) with zero time overhead. Further experiments demonstrated that FL-CNN corrected >70% of the errors made by neurosurgeons. FL-CNN was also able to rapidly predict grade and Ki-67 level (AUC 0.810 and 0.625) of tumor specimens intraoperatively. Conclusion Our study demonstrates that deep CNNs are better at capturing important information from fluorescence images than surgeons’ evaluation during patient surgery. FL-CNN is highly promising to provide pathological diagnosis intraoperatively and assist neurosurgeons to obtain maximum resection safely. Trial registration ChiCTR ChiCTR2000029402. Registered 29 January 2020, retrospectively registered

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Simplified Approach for Pathological Diagnosis of Diffuse Gliomas in Adult Patients

Pathology - Research and Practice ◽

10.1016/j.prp.2021.153483 ◽

2021 ◽

pp. 153483

Author(s):

Sakun Santisukwongchote ◽

Chinnachote Teerapakpinyo ◽

Piyamai Chankate ◽

Piti Techavichit ◽

Atthaporn Boongird ◽

...

Keyword(s):

Adult Patients ◽

Pathological Diagnosis ◽

Simplified Approach ◽

Diffuse Gliomas

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Disorganization of intercalated discs in dilated cardiomyopathy

Scientific Reports ◽

10.1038/s41598-021-90502-1 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Yukinobu Ito ◽

Makoto Yoshida ◽

Hirotake Masuda ◽

Daichi Maeda ◽

Yukitsugu Kudo-Asabe ◽

...

Keyword(s):

Dilated Cardiomyopathy ◽

Interstitial Fibrosis ◽

Left Ventricular ◽

Pathological Diagnosis ◽

Control Group ◽

Failure Group ◽

Intercalated Discs ◽

Group Reduction ◽

Group A ◽

Morphological Differences

AbstractDilated cardiomyopathy (DCM) is a primary myocardial disease, the pathology of which is left ventricular or biventricular dilation and impaired myocardial contractility. The clinical and pathological diagnosis of DCM is difficult, and other cardiac diseases must be ruled out. Several studies have reported pathological findings that are characteristic of DCM, including cardiomyocyte atrophy, nuclear pleomorphism, and interstitial fibrosis, but none of these findings are DCM-specific. In this study, we examined the morphological differences in the intercalated discs (ICDs) between three groups of patients, a DCM group, a chronic heart failure group, and a control group. A total of 22 autopsy cases, including five DCM cases, nine CHF cases and eight control cases, were retrieved from the archives of the Department of Pathology at Akita University, Japan. The morphological differences were examined using multiple methods: macroscopic examination, light microscopy, immunohistochemistry, electron microscopy, and gene expression analyses. We observed disorganized ICDs, clearly illustrated by N-cadherin immunostaining in the DCM group. “Reduction of N-cadherin immunostaining intensity” and “ICD scattering” was DCM-specific. The results suggest that disorganized ICDs contribute to the development of DCM, and that N-cadherin immunostaining is useful for determining the presence of disorganized ICDs and for the pathological diagnosis of DCM.

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