Classification of low-grade neuroendocrine tumors of midgut and unknown origin

Abstract Background The World Health Organization's updated classification of digestive system neuroendocrine tumors in 2010 first proposed the classification of mixed adenoneuroendocrine carcinoma (MANEC). The incidence of biliary malignant tumors with neuroendocrine tumors accounts for less than 1% of all neuroendocrine tumors. Moreover, the incidence of hilar bile duct with MANEC is very rare. Case presentation A 65-year-old female patient came to our hospital for repeated abdominal pain for more than 4 months and skin sclera yellow staining for 1 week. Contrast-enhanced computed tomography imaging and magnetic resonance results suggested a hilar tumor for Bismuth-Corlette Type II. The patient underwent radical surgery for hilar cholangiocarcinoma. Finally, the patient was diagnosed with hilar bile duct MANEC, staged 1 (pT1N0M0) based on the eighth edition of the AJCC. Histopathology showed that the tumor was a biliary tumor with both adenocarcinoma and neuroendocrine carcinoma. No evidence of recurrence and metastasis after 20 months of follow-up. Conclusions We first reported a MANEC that originated in the hilar bile duct. As far as we known, there were few reports of biliary MANEC, and the overall prognosis was poor. We also found that the higher the Ki-67 index, the worse the prognosis of this type of patient. Radical surgery is the most effective treatment.

Download Full-text

Classification of low-grade and high-grade glioma using multi-modal image radiomics features

2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) ◽

10.1109/embc.2017.8037508 ◽

2017 ◽

Cited By ~ 12

Author(s):

Hwan-ho Cho ◽

Hyunjin Park

Keyword(s):

High Grade Glioma ◽

Low Grade ◽

High Grade

Download Full-text

Mammalian target of rapamycin signaling activation patterns in neuroendocrine tumors of the lung

Endocrine Related Cancer ◽

10.1677/erc-10-0157 ◽

2010 ◽

Vol 17 (4) ◽

pp. 977-987 ◽

Cited By ~ 64

Author(s):

Luisella Righi ◽

Marco Volante ◽

Ida Rapa ◽

Veronica Tavaglione ◽

Frediano Inzani ◽

...

Keyword(s):

Neuroendocrine Tumors ◽

Mammalian Target Of Rapamycin ◽

Mtor Pathway ◽

Differential Sensitivity ◽

Initiation Factor ◽

Target Of Rapamycin ◽

Low Grade ◽

Mtor Inhibition ◽

Signaling Activation ◽

Activation Status

Among alternative therapeutic strategies in clinically aggressive neuroendocrine tumors (NETs) of the lung, promising results have been obtained in experimental clinical trials with mammalian target of rapamycin (mTOR) inhibitors, though in the absence of a proven mTOR signaling activation status. This study analyzed the expression of phosphorylated mTOR (p-mTOR) and its major targets, the ribosomal p70S6-kinase (S6K) and the eukaryotic initiation factor 4E-binding protein 1 (4EBP1) in a large series of 218 surgically resected, malignant lung NETs, including 24 metastasizing typical carcinoids, 73 atypical carcinoids, 60 large cell neuroendocrine carcinomas (LCNECs), and 61 small cell carcinomas (SCLCs). By immunohistochemistry, low-to-intermediate-grade tumors as compared with high-grade tumors showed higher levels of p-mTOR and phosphorylated S6K (p-S6K) (P<0.001), at variance with phosphorylated 4EBP1 (p-4EBP1), which was mainly expressed in LCNECs and SCLCs (P<0.001). The activated status of mTOR pathway was proved by the strong correlation of p-mTOR with p-S6K and somatostatin receptor(s). Western blot analysis of NET tumor samples confirmed such findings, and differential sensitivity to mTOR inhibition according to mTOR pathway activation characteristics was determined in two lung carcinoid cell lines in vitro. None of the investigated molecules had an impact on survival. However, in low-grade tumors, low p-mTOR expression correlated with lymph node metastases (P=0.016), recurrent disease, and survival (P=0.005). In conclusion, these data demonstrate a differential mTOR activation status in the spectrum of pulmonary NETs, possibly suggesting that mTOR pathway profiling might play a predictive role in candidate patients for mTOR-targeted therapies.

Download Full-text

Lung Tumors With Neuroendocrine Morphology: Essential Radiologic and Pathologic Features

Archives of Pathology & Laboratory Medicine ◽

10.5858/2008-132-1055-ltwnme ◽

2008 ◽

Vol 132 (7) ◽

pp. 1055-1061 ◽

Cited By ~ 2

Author(s):

Teri J. Franks ◽

Jeffrey R. Galvin

Keyword(s):

Neuroendocrine Tumors ◽

Classification Systems ◽

World Health ◽

National Library ◽

Molecular Features ◽

Distinct Subset ◽

Pathologic Features ◽

The World ◽

Health Organization

Abstract Context.—Tumors with neuroendocrine morphology are a distinct subset of lung neoplasms sharing characteristic histologic, immunohistochemical, ultrastructural, and molecular features. Objective.—To review the current histologic classification and the diagnostic criteria for the major categories of neuroendocrine tumors of the lung. Data Sources.—Published classification systems from the World Health Organization and pertinent peer-reviewed articles indexed in PubMed (National Library of Medicine) form the basis of this review. Conclusions.—Accurate classification of the neuroendocrine tumors of the lung requires knowledge of specific criteria separating the major categories, which is essential for determining prognosis and treatment.

Download Full-text

Emerging Therapeutic Concepts and Latest Diagnostic Advancements Regarding Neuroendocrine Tumors of the Gynecologic Tract

Medicina ◽

10.3390/medicina57121338 ◽

2021 ◽

Vol 57 (12) ◽

pp. 1338

Author(s):

Tiberiu-Augustin Georgescu ◽

Roxana Elena Bohiltea ◽

Octavian Munteanu ◽

Florentina Furtunescu ◽

Antonia-Carmen Lisievici ◽

...

Keyword(s):

Neuroendocrine Tumors ◽

Neuroendocrine Carcinoma ◽

Classification System ◽

Who Classification ◽

Small Cell ◽

International Agency ◽

Low Grade ◽

High Grade ◽

Small Cell Neuroendocrine Carcinoma ◽

Female Genital

Neuroendocrine neoplasms (NENs) are particularly rare in all sites of the gynecological tract and include a variety of neoplasms with variable prognosis, dependent on histologic subtype and site of origin. Following the expert consensus proposal of the International Agency for Research on Cancer (IARC), the approach in the latest World Health Organization (WHO) Classification System of the Female Genital Tumours is to use the same terminology for NENs at all body sites. The main concept of this novel classification framework is to align it to all other body sites and make a clear distinction between well-differentiated neuroendocrine tumors (NETs) and poorly differentiated neuroendocrine carcinomas (NECs). The previous WHO Classification System of the Female Genital Tumours featured more or less the same principle, but used the terms ‘low-grade neuroendocrine tumor’ and ‘high-grade neuroendocrine carcinoma’. Regardless of the terminology used, each of these two main categories include two distinct morphological subtypes: NETs are represented by typical and atypical carcinoid and NEC are represented by small cell neuroendocrine carcinoma (SCNEC) and large cell neuroendocrine carcinoma (LCNEC). High-grade NECs, especially small cell neuroendocrine carcinoma tends to be more frequent in the uterine cervix, followed by the endometrium, while low-grade NETs usually occur in the ovary. NENs of the vulva, vagina and fallopian tube are exceptionally rare, with scattered case reports in the scientific literature.

Download Full-text

Interobserver reproducibility of The Paris System for Reporting Urinary Cytology

CytoJournal ◽

10.4103/cytojournal.cytojournal_12_17 ◽

2017 ◽

Vol 14 ◽

pp. 17 ◽

Cited By ~ 25

Author(s):

Theresa Long ◽

Lester J. Layfield ◽

Magda Esebua ◽

Shellaine R. Frazier ◽

D. Tamar Giorgadze ◽

...

Keyword(s):

Urothelial Carcinoma ◽

Urinary Cytology ◽

Low Grade ◽

High Grade ◽

Urothelial Cells ◽

Urothelial Carcinomas ◽

Absolute Agreement ◽

Potential Impact ◽

Urine Specimens

Background: The Paris System for Reporting Urinary Cytology represents a significant improvement in classification of urinary specimens. The system acknowledges the difficulty in cytologically diagnosing low-grade urothelial carcinomas and has developed categories to deal with this issue. The system uses six categories: unsatisfactory, negative for high-grade urothelial carcinoma (NHGUC), atypical urothelial cells, suspicious for high-grade urothelial carcinoma, high-grade urothelial carcinoma, other malignancies and a seventh subcategory (low-grade urothelial neoplasm). Methods: Three hundred and fifty-seven urine specimens were independently reviewed by four cytopathologists unaware of the previous diagnoses. Each cytopathologist rendered a diagnosis according to the Paris System categories. Agreement was assessed using absolute agreement and weighted chance-corrected agreement (kappa). Disagreements were classified as low impact and high impact based on the potential impact of a misclassification on clinical management. Results: The average absolute agreement was 65% with an average expected agreement of 44%. The average chance-corrected agreement (kappa) was 0.32. Nine hundred and ninety-nine of 1902 comparisons between rater pairs were in agreement, but 12% of comparisons differed by two or more categories for the category NHGUC. Approximately 15% of the disagreements were classified as high clinical impact. Conclusions: Our findings indicated that the scheme recommended by the Paris System shows adequate precision for the category NHGUC, but the other categories demonstrated unacceptable interobserver variability. This low level of diagnostic precision may negatively impact the applicability of the Paris System for widespread clinical application.

Download Full-text

Classification of Brain Tumor IDH Status using MRI and Deep Learning

10.1101/757344 ◽

2019 ◽

Author(s):

Sahil Nalawade ◽

Gowtham Murugesan ◽

Maryam Vejdani-Jahromi ◽

Ryan A. Fisicaro ◽

Chandan Ganesh Bangalore Yogananda ◽

...

Keyword(s):

Deep Learning ◽

Classification Accuracy ◽

Test Accuracy ◽

Low Grade ◽

Idh Mutation ◽

Validation Data ◽

Mutation Status ◽

Radiologic Imaging ◽

Address Data

AbstractIsocitrate dehydrogenase (IDH) mutation status is an important marker in glioma diagnosis and therapy. We propose a novel automated pipeline for predicting IDH status noninvasively using deep learning and T2-weighted (T2w) MR images with minimal preprocessing (N4 bias correction and normalization to zero mean and unit variance). T2w MRI and genomic data were obtained from The Cancer Imaging Archive dataset (TCIA) for 260 subjects (120 High grade and 140 Low grade gliomas). A fully automated 2D densely connected model was trained to classify IDH mutation status on 208 subjects and tested on another held-out set of 52 subjects, using 5-fold cross validation. Data leakage was avoided by ensuring subject separation during the slice-wise randomization. Mean classification accuracy of 90.5% was achieved for each axial slice in predicting the three classes of no tumor, IDH mutated and IDH wild-type. Test accuracy of 83.8% was achieved in predicting IDH mutation status for individual subjects on the test dataset of 52 subjects. We demonstrate a deep learning method to predict IDH mutation status using T2w MRI alone. Radiologic imaging studies using deep learning methods must address data leakage (subject duplication) in the randomization process to avoid upward bias in the reported classification accuracy.

Download Full-text