Deep Learning on Histopathological Images for Colorectal Cancer Diagnosis: A Systematic Review

Davri, Athena; Birbas, Effrosyni; Kanavos, Theofilos; Ntritsos, Georgios; Γιαννακέας, Νικόλαος; Tzallas, Alexandros T.; Batistatou, Anna

doi:10.3390/diagnostics12040837

Cited by 66 publications

(28 citation statements)

References 120 publications

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“…In another systematic review focused on CRC pathology image analysis using artificial intelligence found that while applications were still in early stages, the results were still promising with respect to accurately diagnosing CRC ( 16 ). Furthermore, in another systematic review focused on the use of deep learning for the diagnosis of CRC via histopathological images found that various studies have promise in aiding the diagnosis, predicting relevant molecular features, identifying prognostic features with correlations to metastasis, and assessing tumor microenvironments ( 17 ).…”

Section: Role Of Ai In Crc Diagnosticsmentioning

confidence: 99%

Role of artificial intelligence in risk prediction, prognostication, and therapy response assessment in colorectal cancer: current state and future directions

et al. 2023

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Artificial Intelligence (AI) is a branch of computer science that utilizes optimization, probabilistic and statistical approaches to analyze and make predictions based on a vast amount of data. In recent years, AI has revolutionized the field of oncology and spearheaded novel approaches in the management of various cancers, including colorectal cancer (CRC). Notably, the applications of AI to diagnose, prognosticate, and predict response to therapy in CRC, is gaining traction and proving to be promising. There have also been several advancements in AI technologies to help predict metastases in CRC and in Computer-Aided Detection (CAD) Systems to improve miss rates for colorectal neoplasia. This article provides a comprehensive review of the role of AI in predicting risk, prognosis, and response to therapies among patients with CRC.

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Section: Role Of Ai In Crc Diagnosticsmentioning

confidence: 99%

Role of artificial intelligence in risk prediction, prognostication, and therapy response assessment in colorectal cancer: current state and future directions

et al. 2023

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“…Since early detection of metastatic cancer has been absolutely emphasized for treatment and prognosis, innovative diagnostic methods are being studied [9][10][11][12][13][14], such as detecting cancerspecific markers through liquid biopsy besides the common diagnosis, including imaging examinations and histopathologic examinations. A liquid biopsy is a biological fluid sample that can be obtained from the body, such as blood, saliva, urine, or spinal fluid [15].…”

Section: Introductionmentioning

confidence: 99%

NCK-associated protein 1 regulates metastasis and is a novel prognostic marker for colorectal cancer

et al. 2023

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Metastatic colorectal cancer (CRC) remains a substantial problem for mortality and requires screening and early detection efforts to increase survival. Epithelial-mesenchymal transition (EMT) and circulation of tumor cells in the blood play important roles in metastasis. To identify a novel target for metastasis of CRC, we conducted a gene microarray analysis using extracted RNA from the blood of preclinical models. We found that NCK-associated protein 1 (NCKAP1) was significantly increased in the blood RNA of patient-derived xenograft (PDX) models of colon cancer. In the NCKAP1 gene knockdown-induced human colon cancer cell lines HCT116 and HT29, there was a reduced wound healing area and significant inhibition of migration and invasion. As the result of marker screening for cytoskeleton and cellular interactions, CRC treated with siRNA of NCKAP1 exhibited significant induction of CDH1 and phalloidin expression, which indicates enhanced adherent cell junctions and cytoskeleton. In HCT116 cells with a mesenchymal state induced by TGFβ1, metastasis was inhibited by NCKAP1 gene knockdown through the inhibition of migration, and there was increased CTNNB1 expression and decreased FN expression. We established metastasis models for colon cancer to liver transition by intrasplenic injection shRNA of NCKAP1-transfected HCT116 cells or by implanting tumor tissue generated with the cells on cecal pouch. In metastasis xenograft models, tumor growth and liver metastasis were markedly reduced. Taken together, these data demonstrate that NCKAP1 is a novel gene regulating EMT that can contribute to developing a diagnostic marker for the progression of metastasis and new therapeutics for metastatic CRC treatment.

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“…The majority of the works on CRC diagnosis direct their focus towards the classification of cropped regions of interest, or small tiles, instead of tackling the challenging task of diagnosing the entire WSI [18,19,17,20]. Notwithstanding, some authors already presented methods to assess the grading of the complete slide of colorectal samples.…”

Section: Introductionmentioning

confidence: 99%

A CAD System for Colorectal Cancer from WSI: A Clinically Validated Interpretable ML-based Prototype

Neto¹,

Montezuma²,

Oliveira³

et al. 2023

Preprint

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The integration of Artificial Intelligence (AI) and Digital Pathology has been increasing over the past years. Nowadays, applications of deep learning (DL) methods to diagnose cancer from whole-slide images (WSI) are, more than ever, a reality within different research groups. Nonetheless, the development of these systems was limited by a myriad of constraints regarding the lack of training samples, the scaling difficulties, the opaqueness of DL methods, and, more importantly, the lack of clinical validation. As such, we propose a system designed specifically for the diagnosis of colorectal samples. The construction of such a system consisted of four stages: (1) a careful data collection and annotation process, which resulted in one of the largest WSI colorectal samples datasets; (2) the design of an interpretable

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Deep Learning on Histopathological Images for Colorectal Cancer Diagnosis: A Systematic Review

Cited by 66 publications

References 120 publications

Role of artificial intelligence in risk prediction, prognostication, and therapy response assessment in colorectal cancer: current state and future directions

Role of artificial intelligence in risk prediction, prognostication, and therapy response assessment in colorectal cancer: current state and future directions

NCK-associated protein 1 regulates metastasis and is a novel prognostic marker for colorectal cancer

A CAD System for Colorectal Cancer from WSI: A Clinically Validated Interpretable ML-based Prototype

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