Assessment of the current and emerging criteria for the histopathological classification of lung neuroendocrine tumours in the lungNENomics project.

BACKGROUND: Six thoracic pathologists reviewed 259 lung neuroendocrine tumours (LNETs) from the lungNENomics project, with 171 of them having associated survival data. This cohort presents a unique opportunity to assess the strengths and limitations of current World Health Organization (WHO) classification criteria and to evaluate the utility of emerging markers. PATIENTS AND METHODS: Patients were diagnosed based on the 2021 WHO criteria, with atypical carcinoids (ACs) defined by the presence of focal necrosis and/or 2-10 mitoses per 2 mm2. We investigated two markers of tumour proliferation: the Ki-67 index and phospho-histone H3 (PHH3) protein expression, quantified by pathologists and automatically via deep learning. Additionally, an unsupervised deep learning algorithm was trained to uncover previously unnoticed morphological features with diagnostic value. RESULTS: The accuracy in distinguishing typical from ACs is hampered by interobserver variability in mitotic counting and the limitations of morphological criteria in identifying aggressive cases. Our study reveals that different Ki-67 cut-offs can categorise LNETs similarly to current WHO criteria. Counting mitoses in PHH3+ areas does not improve diagnosis, while providing a similar prognostic value to the current criteria. With the advantage of being time efficient, automated assessment of these markers leads to similar conclusions. Lastly, state-of-the-art deep learning modelling does not uncover undisclosed morphological features with diagnostic value. CONCLUSIONS: This study suggests that the mitotic criteria can be complemented by manual or automated assessment of Ki-67 or PHH3 protein expression, but these markers do not significantly improve the prognostic value of the current classification, as the AC group remains highly unspecific for aggressive cases. Therefore, we may have exhausted the potential of morphological features in classifying and prognosticating LNETs. Our study suggests that it might be time to shift the research focus towards investigating molecular markers that could contribute to a more clinically relevant morpho-molecular classification.

Transplant nephropathology: Wherefrom, wherein, and whereto.

Renal pathology is a relatively recent entry in nephrology. While diseases of the kidney are old, their study began in the 19th century with the report of Richard Bright of the lesions of end-stage kidney disease. Its easy diagnosis from albuminuria soon elevated Bright's nephritis into a leading cause of death. The transformative events in the care of these cases were renal replacement therapy that converted a fatal into a chronic disease, and kidney biopsy that allowed study of the course and pathogenesis of kidney disease. Apart from its fundamental contributions to clinical nephrology, biopsy of renal allografts became an integral component of the evaluation and care of kidney transplant recipients. The Banff transplant pathology conferences launched in 1991 led to developing the classification of allograft pathology into an essential element in the evaluation, treatment, and care of allograft recipients with spirit of discovery. That success came at the cost of increasing complexity leading to the recent realization that it may need the refinement of its consensus-based system into a more evidence-based system with graded statements that are easily accessible to the other disciplines involved in the care of transplanted patients. Collaboration with other medical disciplines, allowing public comment on meeting reports, and incorporation of generative artificial intelligence (AI) are important elements of a successful future. The increased pace of innovation brought about by AI will likely allow us to solve the organ shortage soon and require new classifications for xenotransplantation pathology, tissue engineering pathology, and bioartificial organ pathology.

Feasibility and efficiency of a new classification based on high-resolution MRI for carotid artery pseudo-occlusion and occlusion: Hybrid revascularization pilot study.

BACKGROUND AND PURPOSE: Studies on changes in the distal internal carotid artery based on high resolution magnetic resonance imaging (HRMRI) are scarce. Herein, we propose a histological classification system for patients with carotid artery pseudo-occlusion or occlusion based on preoperative HRMRI, for which we evaluated the feasibility and clinical implications. MATERIALS AND METHODS: From January 2017 to June 2021, 40 patients with Doppler ultrasound, CTA or MRA suggesting carotid artery occlusion were enrolled in this study. A new classification system based on HRMRI was established and subsequently verified by postoperative specimens. We recorded and analyzed patient characteristics, HRMRI data, recanalization rate, requirements of additional endovascular procedures, complications, and outcomes. RESULTS: Four histological classifications (type Ⅰ-Ⅳ) were identified. According to our classification system, 20 patients (50.00%) were type I, nine (22.50%) were type II, 7 (17.50%) were type III, and four (10.00%) were type Ⅳ. The success rate of recanalization was 88.89% (32/36) in type I-III patients. Four (44.44%) type Ⅱ patients and five (71.43%) type Ⅲ patients suffered from intraoperative dissection. CONCLUSION: Patients identified as types I (pseudo-occlusion) and II (thrombotic-occlusion) were able to be treated via hybrid revascularization with relatively low risk, while patients identified as type III (fibrous-occlusion) required more careful treatment. Recanalization is not suitable for patients identified as type Ⅳ. Our proposed classification system based on HRMRI data can be used as an adjunctive guide to predict the technical feasibility and success of revascularization via a hybrid technique.

Lymph node metastatic status could predict the prognosis of intracholecystic papillary neoplasm of gallbladder.

Intracholecystic papillary neoplasm (ICPN) is a non-invasive epithelial tumor that presents as a grossly identifiable mass arising in the mucosa and protruding into the lumen. ICPN is associated with invasive carcinoma. There are few studies on the clinicopathological features of ICPN, including that with invasive carcinoma. We evaluated the clinicopathological characteristics of 42 ICPNs and 41 conventional gallbladder adenocarcinomas (cGBAs). Subserosa or deeper (≥ss) invasion was significantly lower in ICPN (61.9%) than that in cGBA (90.2%) (P = 0.004). Cox regression analysis revealed that lymph node metastasis (hazard ratio [HR] [95% confidence interval (CI)]: 2.610 [1.131, 6.024], P = 0.025) and positive margin (HR [95% CI]: 5.143 [2.113, 12.516], P < 0.001), but not ≥ss invasion (HR [95% CI]: 1.541 [0.479, 4.959], P = 0.469), were independent prognostic factors. In addition, there was a significant interaction between histological type and lymph node metastasis (HR [95% CI]: 0.191 [0.042, 0.983], P = 0.033). In cGBA, the presence or absence of lymph node metastasis did not affect prognosis; however, ICPN without lymph node metastasis had better prognosis. Therefore, the histological classification of ICPN and cGBA and the pathological evaluation of lymph node metastasis in ICPN are crucial for determining prognosis.

Canine Mammary Tumor Histopathological Image Classification via Computer-Aided Pathology: An Available Dataset for Imaging Analysis.

Histopathology, the gold-standard technique in classifying canine mammary tumors (CMTs), is a time-consuming process, affected by high inter-observer variability. Digital (DP) and Computer-aided pathology (CAD) are emergent fields that will improve overall classification accuracy. In this study, the ability of the CAD systems to distinguish benign from malignant CMTs has been explored on a dataset-namely CMTD-of 1056 hematoxylin and eosin JPEG images from 20 benign and 24 malignant CMTs, with three different CAD systems based on the combination of a convolutional neural network (VGG16, Inception v3, EfficientNet), which acts as a feature extractor, and a classifier (support vector machines (SVM) or stochastic gradient boosting (SGB)), placed on top of the neural net. Based on a human breast cancer dataset (i.e., BreakHis) (accuracy from 0.86 to 0.91), our models were applied to the CMT dataset, showing accuracy from 0.63 to 0.85 across all architectures. The EfficientNet framework coupled with SVM resulted in the best performances with an accuracy from 0.82 to 0.85. The encouraging results obtained by the use of DP and CAD systems in CMTs provide an interesting perspective on the integration of artificial intelligence and machine learning technologies in cancer-related research.

Evaluation of a renal risk score for Japanese patients with ANCA-associated glomerulonephritis in a multi-center cohort study.

Background: In patients with anti-neutrophil cytoplasmic antibody (ANCA)-associated glomerulonephritis, prediction of renal survival should guide the choice of therapy, but a prediction of the histological classification has inconsistencies. Objectives: To evaluate the usefulness of renal risk score (RRS) for Japanese patients with ANCA-associated glomerulonephritis (AAGN) and compare the prediction for end-stage renal disease (ESRD) between RRS and the histological classification. Methods: We retrospectively analyzed 96 patients with AAGN who underwent a renal biopsy. Renal survival was categorized by RRS, and the histological classification was assessed separately. We compared the predictive values for RRS and the histological classification. Results: The median observational period was 37.5 (interquartile range [IQR] 21.5-77.0) months. The median RRS point at the time of renal biopsy was 2 (IQR 0-7.8), and the patients were categorized into low- (n = 29), medium- (n = 43), and high-risk groups (n = 24) using RRS. As expected, the renal prognosis was the worst in the "high-risk" group and the best in the "low-risk" group. In the histological classification, the survival deteriorated progressively from "focal" (best) to "mixed," "crescentic," and "sclerotic" (worst) classes, different from the order in the original proposal for this system. Multivariable Cox regression analysis revealed that RRS was independently associated with ESRD. The difference in prediction for renal survival between RRS and the histological classification was not significant using area under receiver-operating-characteristic curves. Conclusion: We evaluated the usefulness of RRS in Japanese patients with AAGN and found it a stable predictor of renal survival in such patients.

Extracranial Meningioma En Plaque With Skull Invasion.

The study reflects on a 69-year-old female patient with a history of cardio-respiratory disorders who was diagnosed with meningioma en plaque. Her clinical management entailed surgical resection of the tumor, which was followed by a complex postoperative course, including cardiorespiratory arrest and respiratory failure. Histologically, extracranial meningiomas are categorized into five subtypes based on predominant cellular morphology, with the meningothelial type being prevalent in this case. The report also examines the significance of complete tumor resection, noting a lower recurrence rate with gross total resection. Additionally, it discusses the increased susceptibility of extracranial meningiomas with advancing age and a higher incidence in females. Data from various studies underscore the importance of a surgical approach and extent of resection in predicting recurrence risk. The case report concludes by highlighting the critical aspects of the pathology of meningiomas and the surgical strategy that ensured the patient's recovery. The findings from this case contribute to the broader understanding of extracranial meningiomas, their diagnosis, and management.

[Analysis of strong invasive clinical features and poor prognosis in macrotrabecular-massive hepatocellular carcinoma].

Objective: To analyze the correlation between the histological classification of hepatocellular carcinoma (HCC), especially macrotrabecular-massive (MTM), tumor invasiveness, and prognosis. Methods: The clinical and follow-up data of 246 consecutive HCC cases who met the inclusion criteria from 2015 to 2018 were retrospectively analyzed. They were divided into trabecular/pseudoglandular, trabecular/patchy, and MTM types according to the histological classification. The relationship between each type and related clinicopathological features was analyzed. The Kaplan-Meier method was used to plot tumor-free survival (DFS) and overall survival (OS) curves. Log rank tests, COX univariate, and multivariate regression analyses were conducted to analyze the relationship between clinical features, including histological classification, DFS, and OS. Results: Trabecular/pseudoglandular, trabecular/nodular, and MTM type proportions were 44.7% (110 cases), 32.9% (81 cases), and 22.4% (55 cases), respectively. The results of the clinicopathological features showed that MTM-type HCC was significantly more invasive than the other two types, with alpha-fetoprotein (AFP) ≥400 ng/ml, tumor diameter≥8 cm, no tumor capsule, poor differentiation, and MVI positivity proportions, and the differences were statistically significant (P < 0.05).The proportion of MTM-type HCC patients with American Joint Committee on Cancer TNM Stage III to IV and Chinese Liver Cancer Staging (CNLC) II to II was significantly higher than that of the first two types, and the differences were statistically significant (P < 0.05). In addition, the proportion of MTM subtypes undergoing transcatheter arterial chemoembolization was also raised (P < 0.05). The DFS and OS were significantly lower for MTM-type HCC compared to trabecular/pseudoductal-type HCC at 1-, 3-, and 5-years, and the differences were statistically significant (P < 0.05). Univariate analysis indicated that strongly invasive clinical pathological features such as alpha fetoprotein (AFP) ≥400 ng/ml, tumor diameter ≥ 8 cm, no tumor capsule, poor differentiation, positive microvascular invasion, tumor stage, and MTM staging were all risk factors affecting DFS and OS (P < 0.05). Multivariate COX analysis showed that MTM histological staging, AFP ≥ 400 ng/ml, tumor non-encapsulation, satellite nodules, CNLC stages II~III, and TNM stages III~IV were independent risk factors for DFS (P < 0.05), while AFP ≥ 400 ng/ml, tumor non-encapsulation, and CNLC stage II~III were independent risk factors for OS ( P < 0.05). Conclusion: Histological classification is highly correlated with tumor invasiveness and HCC prognosis. Trabecular/pseudoglandular types have lower malignancy and a better prognosis, while MTM types exhibit strong invasive features and a poor prognosis.

Hierarchical identification of a transcriptional panel for the histological diagnosis of lung neuroendocrine tumors.

Background: Lung cancer is a complex disease composed of neuroendocrine (NE) and non-NE tumors. Accurate diagnosis of lung cancer is essential in guiding therapeutic management. Several transcriptional signatures have been reported to distinguish between adenocarcinoma (ADC) and squamous cell carcinoma (SCC) belonging to non-NE tumors. This study aims to identify a transcriptional panel that could distinguish the histological subtypes of NE tumors to complement the morphology-based classification of an individual. Methods: A public dataset with NE subtypes, including 21 small-cell lung cancer (SCLC), 56 large-cell NE carcinomas (LCNECs), and 24 carcinoids (CARCIs), and non-NE subtypes, including 85 ADC and 61 SCC, was used as a training set. In the training set, consensus clustering was first used to filter out the samples whose expression patterns disagreed with their histological subtypes. Then, a rank-based method was proposed to develop a panel of transcriptional signatures for determining the NE subtype for an individual, based on the within-sample relative gene expression orderings of gene pairs. Twenty-three public datasets with a total of 3,454 samples, which were derived from fresh-frozen, formalin-fixed paraffin-embedded, biopsies, and single cells, were used for validation. Clinical feasibility was tested in 10 SCLC biopsy specimens collected from cancer hospitals via bronchoscopy. Results: The NEsubtype-panel was composed of three signatures that could distinguish NE from non-NE, CARCI from non-CARCI, and SCLC from LCNEC step by step and ultimately determine the histological subtype for each NE sample. The three signatures achieved high average concordance rates with 97.31%, 98.11%, and 90.63%, respectively, in the 23 public validation datasets. It is worth noting that the 10 clinic-derived SCLC samples diagnosed via immunohistochemical staining were also accurately predicted by the NEsubtype-panel. Furthermore, the subtype-specific gene expression patterns and survival analyses provided evidence for the rationality of the reclassification by the NEsubtype-panel. Conclusion: The rank-based NEsubtype-panel could accurately distinguish lung NE from non-NE tumors and determine NE subtypes even in clinically challenging samples (such as biopsy). The panel together with our previously reported signature (KRT5-AGR2) for SCC and ADC would be an auxiliary test for the histological diagnosis of lung cancer.

Survival of 7,311 lung cancer patients by pathological stage and histological classification: a multicenter hospital-based study in China.

Background: Representative prognostic data by clinical characteristics for lung cancer is not yet available in China. This study aimed to calculate the survival of lung cancer patients with different pathological evaluations, explore their predictive effects and provide information for prognosis improvement. Methods: In this multicenter cohort study, primary lung cancer patients diagnosed in 17 hospitals at three distinct levels in China between 2011-2013 were enrolled and followed up till 2020. Overall survival and lung cancer specific survival were calculated by Kaplan-Meier method. Cox proportional hazards model was applied to assess the effects of predictors of lung cancer survival. Results: Of all the 7,311 patients, the 5-year overall and lung cancer specific survival rates were 37.0% and 41.6%, respectively. For lung cancer patients at stages I, II, III, and IV, the 5-year overall survival rates were 76.9%, 56.1%, 32.6%, and 21.4%, respectively; the lung cancer specific survival rates were 82.3%, 59.7%, 37.2%, and 26.4%, respectively. Differences of survival for each stage remained significant between histological classifications (P<0.01). The 5-year overall survival rates for patients with squamous cell carcinoma, adenocarcinoma (AC), and small cell carcinoma were 36.9%, 43.3% and 27.9%, respectively; the corresponding disease-specific rates were 41.5%, 48.6% and 31.0%, respectively. Such differences were non-statistically significant at advanced stages (P=0.09). After multivariate adjustments, stage and classification remained independent predictors for the survival of lung cancer. Conclusions: The prognosis of lung cancer varied with the pathological stages and histological classifications, and had room for improvement. Stage was the strongest predictor, so efforts on early detection and treatment are needed.

Ultrasound-based radiomics for predicting different pathological subtypes of epithelial ovarian cancer before surgery.

OBJECTIVE: To evaluate the value of ultrasound-based radiomics in the preoperative prediction of type I and type II epithelial ovarian cancer. METHODS: A total of 154 patients with epithelial ovarian cancer were enrolled retrospectively. There were 102 unilateral lesions and 52 bilateral lesions among a total of 206 lesions. The data for the 206 lesions were randomly divided into a training set (53 type I + 71 type II) and a test set (36 type I + 46 type II) by random sampling. ITK-SNAP software was used to manually outline the boundary of the tumor, that is, the region of interest, and 4976 features were extracted. The quantitative expression values of the radiomics features were normalized by the Z-score method, and the 7 features with the most differences were screened by using the Lasso regression tenfold cross-validation method. The radiomics model was established by logistic regression. The training set was used to construct the model, and the test set was used to evaluate the predictive efficiency of the model. On the basis of multifactor logistic regression analysis, combined with the radiomics score of each patient, a comprehensive prediction model was established, the nomogram was drawn, and the prediction effect was evaluated by analyzing the area under the receiver operating characteristic curve (AUC), calibration curve and decision curve. RESULTS: The AUCs of the training set and test set in the radiomics model and comprehensive model were 0.817 and 0.731 and 0.982 and 0.886, respectively. The calibration curve showed that the two models were in good agreement. The clinical decision curve showed that both methods had good clinical practicability. CONCLUSION: The radiomics model based on ultrasound images has a good predictive effect for the preoperative differential diagnosis of type I and type II epithelial ovarian cancer. The comprehensive model has higher prediction efficiency.

[Meningiomas: A review of current knowledge]. / Les méningiomes : mise au point sur les connaissances actuelles.

Meningiomas are the most frequent among intracranial tumors, and represent more than 30% of primitive central nervous system neoplasms. Arising from the meninges, they are generally benign lesions and can be treated by either radio-clinical follow-up or surgical resection with excellent outcome. However, more than 20% of meningiomas harbor atypical or malignant features and represent challenges for both prognostic evaluation and therapeutic strategy. The discovery of the genetic and epigenetic landscapes of meningiomas enabled the identification of new prognostic markers and potential therapeutic targets for refractory meningiomas. This review summarizes current epidemiology, histological and molecular characteristics, diagnosis and treatments for meningiomas, and highlights the close relationship between the development of meningiomas and hormonal intake, as illustrated by recent recommendations of the "Agence Nationale de Securité du Medicament", the French national drug safety agency.

Correlation between clinicopathological characteristics of lung adenocarcinoma and the risk of venous thromboembolism.

BACKGROUND: Patients with primary lung adenocarcinoma are at increased risk of venous thromboembolism (VTE). However, lung adenocarcinoma characteristics differ across histological subtypes. Therefore, we performed comprehensive analyses on the clinicopathological characteristics of lung adenocarcinoma and risk of VTE. METHODS: A total of 952 surgically resected lung adenocarcinoma cases were reviewed and classified according to criteria of the International Association for the Study of Lung Cancer (IASLC)/American Thoracic Society (ATS) /European Respiratory Society (ERS). The correlation between this classification and VTE risk was retrospectively analyzed. The risks of other clinicopathological features including pleural invasion, vascular invasion and associated surgical intervention risks were also assessed. RESULTS: Of the 952 patients, 100 (10.4%) cases experienced VTE events during the follow-up period. Among those with VTE, 28 (28%) were found before surgery, 47 (47%) were found within 1 month after surgery, and 91 (91%) were found in hospital. Univariate analysis revealed that ages, extent of resection and presence of micropapillary features were predictive of VTE risk. Furthermore, multivariable analysis demonstrated that the presence of micropapillary features (subdistribution hazard ratio [SHR] 1.560, 95% CI: 1.043-2.330) and age >60 (SHR: 2.270, 95% CI:1.491-3.470) were associated with increased risk of VTE. After one year, the probability of developing VTE was 13.1% and 8.3% in patients with micropapillary features and those without, respectively. CONCLUSIONS: VTE is a common complication for lung adenocarcinoma patients who undergo surgery, especially during the perioperative process and hospitalization. Presence of micropapillary subtype and age are positively associated with VTE risk.

Whole-genome characterization of large-cell lung carcinoma: A comparative analysis based on the histological classification.

Background: According to the 2015 World Health Organization classification, large cell neuroendocrine carcinoma (LCNEC) was isolated from Large-cell lung cancer (LCLC) tumors, which constitutes 2%-3% of non-small cell lung cancer (NSCLC). However, LCLC tumors are still fairly vaguely defined at the molecular level compared to other subgroups. Materials and Methods: In this study, whole-genome sequencing (WGS) was performed on 23 LCLC and 15 LCNEC tumor specimens. Meanwhile, data from the TCGA (586 LUADs and 511 LUSCs) and U Cologne (120 SCLCs) were analyzed and compared. Results: The most common driver mutations were found in TP53 (13/23, 57%), FAM135B (8/23, 35%) and FAT3 (7/23, 30%) in LCLC, while their counterparts in LCNEC were TP53 (13/15, 87%), LRP1B (6/15, 40%) and FAT1 (6/15, 40%). Notably, FAM135B mutations only occurred in LCLC (P = 0.013). Cosmic signature analysis revealed widespread defective DNA mismatch repair and tobacco-induced mutations in both LCLC and LCNEC. Additionally, LCNEC had a higher incidence of chromosomal copy number variations (CNVs) and structural variations (SVs) compared with LCLC, although the differences were not statistically significant. Particularly, chromothripsis SVs was significantly associated with CNVs. Furthermore, mutational landscape of different subtypes indicated differences between subtypes, and there seems to be more commonalty between our cohort and SCLC than with other subtypes. SMARCA4 mutations may be specific driver gene alteration in our cohort. Conclusion: Our results support that LCLC and LCNEC tumors follow distinct tumorigenic pathways. To our knowledge, this is the first genome-wide profiling comparison of LCLC and LCNEC.

Development and reliability of the histological THROMBEX-classification rule for thrombotic emboli of acute ischemic stroke patients.

BACKGROUND: Thrombus histology has become a potential diagnostic tool for the etiology assessment of patients with ischemic stroke caused by embolic proximal vessel occlusion. We validated a classification rule that differentiates between cardiac and arteriosclerotic emboli in individual stroke patients. We aim to describe in detail the development of this classification rule and disclose its reliability. METHODS: The classification rule is based on the hypothesis that cardiac emboli arise out of separation thrombi and arteriosclerotic emboli result from agglutinative thrombi. 125 emboli recovered by thrombectomy from stroke patients and 11 thrombi serving as references for cardiac (n = 5) and arteriosclerotic emboli (n = 6) were Hematoxylin and eosin, Elastica-van Gieson and CD61 stained and rated independently by two histopathologists blinded to the presumed etiology by several pre-defined criteria. Intra- and interobserver reliabilities of all criteria were determined. Out of the different criteria, three criteria with the most satisfactory reliability values were selected to compose the classification rule that was finally adjusted to the reference thrombi. Reliabilities of the classification rule were calculated by using the emboli of stroke patients. RESULTS: The classification rule reached intraobserver reliabilities for the two raters of 92.9% and 68.2%, respectively. Interobserver reliability was 69.9%. CONCLUSIONS: A new classification rule for emboli obtained from thrombectomy was established. Within the limitations of histological investigations, it is reliable and able to distinguish between cardioembolic and arteriosclerotic emboli.

Integrative Transcriptomic Analysis Reveals Distinctive Molecular Traits and Novel Subtypes of Collecting Duct Carcinoma.

Collecting duct carcinoma (CDC) is a rare and highly aggressive kidney cancer subtype with poor prognosis and no standard treatments. To date, only a few studies have examined the transcriptomic portrait of CDC. Through integration of multiple datasets, we compared CDC to normal tissue, upper-tract urothelial carcinomas, and other renal cancers, including clear cell, papillary, and chromophobe histologies. Association between CDC gene expression signatures and in vitro drug sensitivity data was evaluated using the Cancer Therapeutic Response Portal, Genomics of Drug Sensitivity in Cancer datasets, and connectivity map. We identified a CDC-specific gene signature that predicted in vitro sensitivity to different targeted agents and was associated to worse outcome in clear cell renal cell carcinoma. We showed that CDC are transcriptionally related to the principal cells of the collecting ducts providing evidence that this tumor originates from this normal kidney cell type. Finally, we proved that CDC is a molecularly heterogeneous disease composed of at least two subtypes distinguished by cell signaling, metabolic and immune-related alterations. Our findings elucidate the molecular features of CDC providing novel biological and clinical insights. The identification of distinct CDC subtypes and their transcriptomic traits provides the rationale for patient stratification and alternative therapeutic approaches.

Introduction of histological classification and cytology reporting format of the Japanese General Rules for the Description of Thyroid Cancer with a special focus on the differences of the WHO Histological Classification and The Bethesda System of Thyroid Cytology.

Histological classification and cytology reporting format described in General Rules for the Description of Thyroid Cancer, the 8th edition (2019) (the Japanese General Rules) were briefly introduced. Moreover, the differences between "the Japanese General Rules", and WHO Histological Classification, the 4th edition (2017) and The Bethesda System for Reporting Thyroid Cytopathology, the 2nd edition (2018) were also explained. The Japanese General Rules did not accept the borderline lesions of thyroid tumor which were newly shown in WHO Histological Classification. We believe it is not necessary to introduce these borderline lesions in daily practice in Japan. Borderline lesions were proposed for avoiding over-surgery for thyroid cancer patients. In the United States, when the patient is diagnosed as malignant on cytology, total thyroidectomy is generally recommended. However, there is no over-surgery in Japan, because surgeons have several choices of treatment for thyroid cancer patients. This article is the first that the Japanese General Rules was shown by foreign language. Therefore, this will be advantageous to us when we present our opinion concerning histology and cytology of thyroid tumor to the world.

Bladder Cancer: Update on Risk Factors, Molecular and Ultrastructural Patterns.

OBJECTIVE: The molecular mechanisms of bladder cancer development and progression are not clear. Bladder cancer is an important focus for epidemiological studies and understanding clinical implications. GOAL: The primary aim of prevention is achieved by limiting exposure to non-genetic risk factors, such as smoking, diet, arsenic in drinking water, or aromatic amines at work or elsewhere. Current therapies for bladder cancer are affected by tumor morphology and associated acquired genetic mutations. METHODS: A literature search was performed using PubMed, Scopus, ResearchGate, Google, MEDLINE, and ScienceDirect databases to find studies of bladder cancer published between 1984 and early 2020. The focus was articles that address epidemiological risk factors and underlying pathophysiological mechanisms. Articles were selected that enabled our review of these factors as well as molecular and structural patterns. RESULTS: There are multiple views of bladder cancer. The literature offers several novel insights regarding the development and progression of bladder cancer and possible biomarkers that may be useful in clinical and diagnostic practice. CONCLUSION: There are several molecular pathways associated with bladder cancer that are frequently updated. In addition, genetic subtypes of bladder tumors are not distinguished clearly which requires future more detailed analysis.

Utility of Tissue Classification in Invasive Ductal Carcinoma using Dynamic Magnetic Resonance Imaging of the Mammary Gland.

OBJECTIVES: In Japan, invasive ductal carcinomas, which account for 75% of breast cancer cases, are sub-classified as solid, tubule-forming, scirrhous, and other types based on the histopathological findings. Although time-intensity curve (TIC) analysis of magnetic resonance (MR) images has shown diagnostic ability in differentiating benign and malignant tumors, its ability to diagnose different tumor tissue types has not yet been achieved. In this study, we report a histological classification of invasive ductal carcinoma using the TIC analysis of dynamic MR images of the mammary gland. MATERIAL AND METHODS: A total of 312 invasive ductal carcinomas were analyzed, and each tissue type that indicated malignancy in the washout parts of the tumors was classified and characterized using the TIC. RESULTS: The tissue was classified, and the results were then compared to the pathohistological diagnosis. Using this method, the accuracy of tissue classification by quantitative analysis of TIC-MR images was 86.9% (271/312), which was higher than that obtained by ultrasonography 68.9% (215/312). CONCLUSION: This method is effective for classifying tissue types in invasive ductal carcinoma.

Dual pathology in a patient with temporal lobe epilepsy associated with neocortical glial scar after brain abscess and end folium sclerosis/hippocampal sclerosis type 3.

End folium sclerosis or hippocampal sclerosis (HS) type 3 is often associated with another coexisting epileptogenic lesion (dual pathology); however, the pathogenesis of HS type 3 remains elusive. A 46-year-old man presented with medically intractable focal aware seizures and focal impaired awareness seizures (FIAS) with occasional focal to bilateral tonic-clonic seizures (FBTCS) two years after surgical treatment with extensive cranial reconstruction for a brain abscess in the right temporal lobe associated with intracranial extension of ipsilateral cholesteatoma. Head magnetic resonance imaging (MRI) at age 49 revealed atrophy of the right cerebral hemisphere including the hippocampus and amygdala. The patient's first epilepsy surgery was a lateral temporal lobectomy, in which the mesial temporal structures were preserved because no epileptiform discharge was detected on the intraoperative electrocorticogram. However, FIAS with FBTCS started 15 months after the operation. The second surgery, amygdalohippocampectomy, at age 52, resulted in the patient being seizure-free again for one year before seizures of the right lateral temporal origin recurred. He underwent a third surgery, resection of the Heschl's and supramarginal gyri, at age 53, but he continued to have drug-resistant epilepsy over two years after that. Histopathological examination revealed dual pathology consisting of glial scar in the lateral temporal lobe and ipsilateral HS type 3 with an unusually severe lesion in the subiculum. No significant inflammatory change was observed. The clinicopathological features in the present case indicate that HS developed secondarily in the context of neocortical epilepsy due to glial scar, suggesting a role of repetitive abnormal electrical input from neocortical epileptogenic lesions into the hippocampus finally via the perforant pathway in the pathogenesis of HS type 3. Severe hippocampal atrophy on preoperative MRI together with its silent electrocorticogram recording at initial epilepsy surgery may represent clinically pre-epileptogenic HS in a seizure-free "silent or latent period" before completion of hippocampal epileptogenesis to the extent that clinical epileptic seizures occur.