Assessing pathological prognostic factors of resectable rectal cancer: comparison of a monoexponential model and multiple advanced DWI models

Motivation: Diffusion-weighted imaging (DWI) can help to predicti rectal cancer prognosis; however, inconsistencies in its effectiveness necessitate exploring advanced DWI models to improve diagnostic accuracy. Goal(s): We investigated the value of the stretched exponential (SEM), fractional-order calculus (FROC), and continuous-time random-walk (CTRW) models in assessing prognostic factors for rectal cancer. Approach: This study included 181 rectal cancer patients with using traditional and advanced DWI models to explore correlations between DWI parameters and histopathological indicators. Results: The parameters of advanced DWI models were significantly correlated with histopathological prognostic factors. CTRW-α was the superior predictor for histological type and pT stage. Impact: Our study demonstrates the value of CTRW model in predicting prognostic factors for rectal cancer. Utilizing these noninvasive and accurate advanced DWI models before surgery can help physicians to make appropriate surgical plan to help patients achieve better prognosis.

Authors

Publication Details

Journal
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Published
2024-11-26
DOI
https://doi.org/10.58530/2024/0553
Primary Topic
Colorectal Cancer Surgical Treatments
Type
article
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article

Assessing pathological prognostic factors of resectable rectal cancer: comparison of a monoexponential model and multiple advanced DWI models

Meining Chen, Mi Zhou, Hongyun Huang, Qin Zhang
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Colorectal Cancer Surgical Treatments
article

Assessing pathological prognostic factors of resectable rectal cancer: comparison of a monoexponential model and multiple advanced DWI models

Meining Chen, Mi Zhou, Hongyun Huang, Qin Zhang
article en

Abstract

Motivation: Diffusion-weighted imaging (DWI) can help to predicti rectal cancer prognosis; however, inconsistencies in its effectiveness necessitate exploring advanced DWI models to improve diagnostic accuracy. Goal(s): We investigated the value of the stretched exponential (SEM), fractional-order calculus (FROC), and continuous-time random-walk (CTRW) models in assessing prognostic factors for rectal cancer. Approach: This study included 181 rectal cancer patients with using traditional and advanced DWI models to explore correlations between DWI parameters and histopathological indicators. Results: The parameters of advanced DWI models were significantly correlated with histopathological prognostic factors. CTRW-α was the superior predictor for histological type and pT stage. Impact: Our study demonstrates the value of CTRW model in predicting prognostic factors for rectal cancer. Utilizing these noninvasive and accurate advanced DWI models before surgery can help physicians to make appropriate surgical plan to help patients achieve better prognosis.

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Good health and well-being
Openalex Percentile: Top 62%
Colorectal Cancer Surgical Treatments
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Assessing pathological prognostic factors of resectable rectal cancer: comparison of a monoexponential model and multiple advanced DWI models — Meining Chen, Mi Zhou, et al. · Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition (2024) | TGRS Research Map | TGRS