Upper tract urothelial carcinoma (UTUC) is a rare and aggressive, yet understudied, urothelial carcinoma (UC). The more frequent UC of the bladder comprises several molecular subtypes, associated with different targeted therapies and overlapping with protein-based subtypes.
Prostate cancer (PCa) is a heterogeneous disease that is manifested in a diverse range of histologic patterns and its grading is therefore associated with an inter-observer variability among pathologists, which may lead to an under- or over-treatment of patients.
Prostate cancer remains the second deadliest cancer for American men despite clinical advancements. Currently, Magnetic Resonance Imaging (MRI) is considered the most sensitive non-invasive imaging modality that enables visualization, detection and localization of prostate cancer, and is increasingly used to guide targeted biopsies for prostate cancer diagnosis.
The tumor microenvironment (TME), including immune cells, cancer-associated fibroblasts, endothelial cells, adjacent normal cells, and others, plays a crucial role in influencing tumor behavior and progression.
Prostate cancer (PCa) is the most frequent tumor among men in Europe and has both indolent and aggressive forms. There are several treatment options, the choice of which depends on multiple factors.
To evaluate if a deep learning algorithm can be trained to identify tumour-infiltrating lymphocytes (TILs) in tissue samples of testicular germ cell tumours and to assess whether the TIL counts correlate with relapse status of the patient.
Bladder cancer (BlCa) is the tenth most frequent malignancy worldwide and the costliest to treat and monitor. Muscle-invasive BlCa (MIBC) has a dismal prognosis, entailing the need for alternative therapies for the standard radical cystectomy.
Immune checkpoint inhibitors (ICI) therapies have demonstrated significant benefit in the treatment of many tumors including high grade urothelial cancer (HGUC) of the bladder. However, variability in patients' clinical responses highlights the need for biomarkers to aid patient stratification.
To evaluate intra-observer diagnostic reproducibility using traditional slides (TS) versus whole slide images (WSI).
TS and WSI of 1427 prostatic biopsies (107 consecutive patients) were evaluated by a single pathologist.
A microscopic analysis of tissue is the gold standard for cancer detection. Hematoxylin-eosin (HE) for the reporting of prostate biopsy (PB) is conventionally based on fixation, processing, acquisition of glass slides, and analysis with an analog microscope by a local pathologist.
Tumour-infiltrating lymphocytes (TIL), known to be of prognostic value in various solid tumours, have been in the focus of research in the last years. TIL are often quantified via IMMUNOSCORE ® (IS), a scoring system based on TIL cell densities.
Characterizing likelihood of response to neoadjuvant chemotherapy (NAC) in muscle-invasive bladder cancer (MIBC) is an important yet unmet challenge. In this study, a machine-learning framework is developed using imaging of biopsy pathology specimens to generate models of likelihood of NAC response.
There has been particular interest in the deployment of digital pathology (DP) and artificial intelligence (AI) in the diagnosis of prostate cancer, but little is known about the views of the public on their use.
Pathological grading of non-invasive urothelial carcinoma has a direct impact upon management. This study evaluates the reproducibility of grading these tumours on glass slides and digital pathology.
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