Molecular genetic evidence supporting the neoplastic nature of stromal cells in ‘fibrosis’ after chemotherapy for testicular germ cell tumours

2007 ◽  
Vol 213 (1) ◽  
pp. 65-71 ◽  
Author(s):  
L Cheng ◽  
S Zhang ◽  
M Wang ◽  
DD Davidson ◽  
MJ Morton ◽  
...  
Keyword(s):  
Germ Cell ◽  
Stromal Cells ◽  
Molecular Genetic ◽  
Genetic Evidence ◽  
Germ Cell Tumours ◽  
Testicular Germ Cell ◽  
Testicular Germ Cell Tumours ◽  
Molecular Genetic Evidence

scholarly journals The Potential of Artificial Intelligence to Detect Lymphovascular Invasion in Testicular Cancer

Cancers ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1325
Author(s):  
Abhisek Ghosh ◽  
Korsuk Sirinukunwattana ◽  
Nasullah Khalid Alham ◽  
Lisa Browning ◽  
Richard Colling ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Testicular Cancer ◽  
Germ Cell ◽  
Lymphovascular Invasion ◽  
Automatic Segmentation ◽  
Prognostic Significance ◽  
Germ Cell Tumours ◽  
Testicular Germ Cell ◽  
Testicular Germ Cell Tumours ◽  
Whole Slide Images

Testicular cancer is the most common cancer in men aged from 15 to 34 years. Lymphovascular invasion refers to the presence of tumours within endothelial-lined lymphatic or vascular channels, and has been shown to have prognostic significance in testicular germ cell tumours. In non-seminomatous tumours, lymphovascular invasion is the most powerful prognostic factor for stage 1 disease. For the pathologist, searching multiple slides for lymphovascular invasion can be highly time-consuming. The aim of this retrospective study was to develop and assess an artificial intelligence algorithm that can identify areas suspicious for lymphovascular invasion in histological digital whole slide images. Areas of possible lymphovascular invasion were annotated in a total of 184 whole slide images of haematoxylin and eosin (H&E) stained tissue from 19 patients with testicular germ cell tumours, including a mixture of seminoma and non-seminomatous cases. Following consensus review by specialist uropathologists, we trained a deep learning classifier for automatic segmentation of areas suspicious for lymphovascular invasion. The classifier identified 34 areas within a validation set of 118 whole slide images from 10 patients, each of which was reviewed by three expert pathologists to form a majority consensus. The precision was 0.68 for areas which were considered to be appropriate to flag, and 0.56 for areas considered to be definite lymphovascular invasion. An artificial intelligence tool which highlights areas of possible lymphovascular invasion to reporting pathologists, who then make a final judgement on its presence or absence, has been demonstrated as feasible in this proof-of-concept study. Further development is required before clinical deployment.

scholarly journals Vascularization of testicular germ cell tumours: evidence from experimental teratocarcinomas

2010 ◽  
Vol 33 (6) ◽  
pp. 765-774 ◽  
Author(s):  
U. Silván ◽  
A. Díez-Torre ◽  
L. Jiménez-Rojo ◽  
J. Aréchaga
Keyword(s):  
Germ Cell ◽  
Germ Cell Tumours ◽  
Testicular Germ Cell ◽  
Testicular Germ Cell Tumours

Bilateral Testicular Germ Cell Tumours: an Increasing Incidence and Prevention by Chemotherapy

1988 ◽  
Vol 62 (4) ◽  
pp. 374-376 ◽  
Author(s):  
JOYCE THOMPSON ◽  
C. J. WILLIAMS ◽  
J. M. A. WHITEHOUSE ◽  
G. M. MEAD
Keyword(s):  
Germ Cell ◽  
Germ Cell Tumours ◽  
Testicular Germ Cell ◽  
Testicular Germ Cell Tumours

Patterns of supradiaphragmatic metastases in testicular germ cell tumours

1996 ◽  
Vol 51 (4) ◽  
pp. 273-276 ◽  
Author(s):  
A. Wood ◽  
N. Robson ◽  
K. Tung ◽  
G. Mead
Keyword(s):  
Germ Cell ◽  
Germ Cell Tumours ◽  
Testicular Germ Cell ◽  
Testicular Germ Cell Tumours
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