Nutrients

Journal Browser

► Journal Browser

Novel Insight on Nutrition and Colorectal Cancer

Share This Special Issue

Special Issue Editor

Dr. Kai Wang

E-Mail Website
Guest Editor

Harvard T.H. Chan School of Public Health, Department of Epidemiology, Boston, MA 02115, USA
Interests: nutrition; colorectal cancer; gut microbiome; metabolic biomarker; bile acid metabolism

Special Issue Information

Dear Colleagues,

Nutrition is an established etiologic factor for colorectal cancer (CRC) and is estimated to account for more than 40% of CRC cases and deaths. Although a number of diets have been established, only some, e.g., Empirical Dietary Inflammatory Pattern (EDIP) and Empirical Dietary Index for Hyperinsulinaemia (EDIH), have been proven to be CRC-related. Therefore, more evidence of a diet that is more colon-targeted for CRC prevention is warranted to optimize the existing knowledge for an improved dietary CRC prevention, for example, through certain more colon-specific pathways like gut microbial metabolism. In this context, a Special Issue summarizing recent data on novel insights into dietary association, effects, or pathways relevant to CRC risk, early detection, and prognosis would be very interesting and of clinical value to the readers.

Our ambition in this Special Issue is to provide a creative prospective towards the understanding of the nutritional role in any of colorectal cancer-relevant health outcomes. I encourage authors to submit their original research on this attractive topic. An up-to-date mechanistic review article describing the current research progress in the association between diet and CRC would fit very well as the initiating paper of this Special Issue. Any other suggestions from experts in the field are more than welcome.

Dr. Kai Wang
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Nutrients is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

colorectal cancer
nutrition
food
dietary pattern
colorectal cancer precursor
early colorectal cancer
epidemiology
biological mechanism
the gut microbiome
dietary metabolism

Published Papers (1 paper)

Order results

Result details

Show export options Show export options

Select all

Export citation of selected articles as:

Research

11 pages, 3046 KiB

Open AccessArticle

AI-Assisted Body Composition Assessment Using CT Imaging in Colorectal Cancer Patients: Predictive Capacity for Sarcopenia and Malnutrition Diagnosis

by Virginia Soria-Utrilla, Francisco José Sánchez-Torralvo, Fiorella Ximena Palmas-Candia, Rocío Fernández-Jiménez, Fernanda Mucarzel-Suarez-Arana, Patricia Guirado-Peláez, Gabriel Olveira, José Manuel García-Almeida and Rosa Burgos-Peláez

Nutrients 2024, 16(12), 1869; https://doi.org/10.3390/nu16121869 - 14 Jun 2024

Viewed by 565

Abstract

(1) Background: The assessment of muscle mass is crucial in the nutritional evaluation of patients with colorectal cancer (CRC), as decreased muscle mass is linked to increased complications and poorer prognosis. This study aims to evaluate the utility of AI-assisted L3 CT for assessing body composition and determining low muscle mass using both the Global Leadership Initiative on Malnutrition (GLIM) criteria for malnutrition and the European Working Group on Sarcopenia in Older People (EWGSOP2) criteria for sarcopenia in CRC patients prior to surgery. Additionally, we aim to establish cutoff points for muscle mass in men and women and propose their application in these diagnostic frameworks. (2) Methods: This retrospective observational study included CRC patients assessed by the Endocrinology and Nutrition services of the Regional University Hospitals of Malaga, Virgen de la Victoria of Malaga, and Vall d’Hebrón of Barcelona from October 2018 to July 2023. A morphofunctional assessment, including anthropometry, bioimpedance analysis (BIA), and handgrip strength, was conducted to apply the GLIM criteria for malnutrition and the EWGSOP2 criteria for sarcopenia. Body composition evaluation was performed through AI-assisted analysis of CT images at the L3 level. ROC analysis was used to determine the predictive capacity of variables derived from the CT analysis regarding the diagnosis of low muscle mass and to describe cutoff points. (3) Results: A total of 586 patients were enrolled, with a mean age of 68.4 ± 10.2 years. Using the GLIM criteria, 245 patients (41.8%) were diagnosed with malnutrition. Applying the EWGSOP2 criteria, 56 patients (9.6%) were diagnosed with sarcopenia. ROC curve analysis for the skeletal muscle index (SMI) showed a strong discriminative capacity of muscle area to detect low fat-free mass index (FFMI) (AUC = 0.82, 95% CI 0.77–0.87, p < 0.001). The identified SMI cutoff for diagnosing low FFMI was 32.75 cm²/m² (Sn 77%, Sp 64.3%; AUC = 0.79, 95% CI 0.70–0.87, p < 0.001) in women, and 39.9 cm²/m² (Sn 77%, Sp 72.7%; AUC = 0.85, 95% CI 0.80–0.90, p < 0.001) in men. Additionally, skeletal muscle area (SMA) showed good discriminative capacity for detecting low appendicular skeletal muscle mass (ASMM) (AUC = 0.71, 95% CI 0.65–0.76, p < 0.001). The identified SMA cutoff points for diagnosing low ASMM were 83.2 cm² (Sn 76.7%, Sp 55.3%; AUC = 0.77, 95% CI 0.69–0.84, p < 0.001) in women and 112.6 cm² (Sn 82.3%, Sp 58.6%; AUC = 0.79, 95% CI 0.74–0.85, p < 0.001) in men. (4) Conclusions: AI-assisted body composition assessment using CT is a valuable tool in the morphofunctional evaluation of patients with colorectal cancer prior to surgery. CT provides quantitative data on muscle mass for the application of the GLIM criteria for malnutrition and the EWGSOP2 criteria for sarcopenia, with specific cutoff points established for diagnostic use. Full article

(This article belongs to the Special Issue Novel Insight on Nutrition and Colorectal Cancer)

► Show Figures

Journal Menu

Journal Browser

Novel Insight on Nutrition and Colorectal Cancer

Share This Special Issue

Special Issue Editor

Special Issue Information

Keywords

Published Papers (1 paper)

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI