Impact of image enhancement on the radiomics stability of diffusion-weighted MRI images of cervical cancer

The diffusion-weighted imaging (DWI) technique is known for its capability to differentiate the diffusion of water molecules between cancerous and non-cancerous cervix tissues, which enhances the accuracy of detection. Despite the potential of DWI-MRI, its accuracy is limited by technical factors in...

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Main Authors: Ramli, Zarina, Farizan, Aishah, Tamchek, Nizam, Haron, Zaharudin, Abdul Karim, Muhammad Khalis
Format: Article
Language:English
Published: Springer Science and Business Media LLC 2024
Online Access:http://psasir.upm.edu.my/id/eprint/117350/
http://psasir.upm.edu.my/id/eprint/117350/1/117350.pdf
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author Ramli, Zarina
Farizan, Aishah
Tamchek, Nizam
Haron, Zaharudin
Abdul Karim, Muhammad Khalis
author_facet Ramli, Zarina
Farizan, Aishah
Tamchek, Nizam
Haron, Zaharudin
Abdul Karim, Muhammad Khalis
author_sort Ramli, Zarina
building UPM Institutional Repository
collection Online Access
description The diffusion-weighted imaging (DWI) technique is known for its capability to differentiate the diffusion of water molecules between cancerous and non-cancerous cervix tissues, which enhances the accuracy of detection. Despite the potential of DWI-MRI, its accuracy is limited by technical factors influencing in vivo data acquisition, thus impacting the quantification of radiomics features. This study aimed to measure the radiomics stability of manual and semi-automated segmentation on contrast limited adaptive histogram equalization (CLAHE)-enhanced DWI-MRI cervical images. Eighty diffusion-weighted MRI images were obtained from patients diagnosed with cervical cancer, and an active contour model was used to analyze the data. Radiomics analysis was conducted to extract the first statistical order, shape, and textural features with intraclass correlation coefficient (ICC) measurement. The results of the CLAHE segmentation approach showed a marked improvement when compared to the manual and semi-automated segmentation methods, with an ICC value of 0.990 ± 0.005 (p<0.05), compared to 0.864 ± 0.033 (p<0.05) and 0.554 ± 0.185 (p>0.05), respectively. The CLAHE segmentation displayed a higher level of robustness than the manual groups in terms of the features present in both categories. Thus, CLAHE segmentation is owing to its potential to generate radiomics features that are more durable and consistent.
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spelling upm-1173502025-05-15T00:01:52Z http://psasir.upm.edu.my/id/eprint/117350/ Impact of image enhancement on the radiomics stability of diffusion-weighted MRI images of cervical cancer Ramli, Zarina Farizan, Aishah Tamchek, Nizam Haron, Zaharudin Abdul Karim, Muhammad Khalis The diffusion-weighted imaging (DWI) technique is known for its capability to differentiate the diffusion of water molecules between cancerous and non-cancerous cervix tissues, which enhances the accuracy of detection. Despite the potential of DWI-MRI, its accuracy is limited by technical factors influencing in vivo data acquisition, thus impacting the quantification of radiomics features. This study aimed to measure the radiomics stability of manual and semi-automated segmentation on contrast limited adaptive histogram equalization (CLAHE)-enhanced DWI-MRI cervical images. Eighty diffusion-weighted MRI images were obtained from patients diagnosed with cervical cancer, and an active contour model was used to analyze the data. Radiomics analysis was conducted to extract the first statistical order, shape, and textural features with intraclass correlation coefficient (ICC) measurement. The results of the CLAHE segmentation approach showed a marked improvement when compared to the manual and semi-automated segmentation methods, with an ICC value of 0.990 ± 0.005 (p<0.05), compared to 0.864 ± 0.033 (p<0.05) and 0.554 ± 0.185 (p>0.05), respectively. The CLAHE segmentation displayed a higher level of robustness than the manual groups in terms of the features present in both categories. Thus, CLAHE segmentation is owing to its potential to generate radiomics features that are more durable and consistent. Springer Science and Business Media LLC 2024-11-01 Article PeerReviewed text en cc_by_4 http://psasir.upm.edu.my/id/eprint/117350/1/117350.pdf Ramli, Zarina and Farizan, Aishah and Tamchek, Nizam and Haron, Zaharudin and Abdul Karim, Muhammad Khalis (2024) Impact of image enhancement on the radiomics stability of diffusion-weighted MRI images of cervical cancer. Cureus, 16 (1). art. no. e52132. pp. 1-13. ISSN 2168-8184 https://www.cureus.com/articles/208707-impact-of-image-enhancement-on-the-radiomics-stability-of-diffusion-weighted-mri-images-of-cervical-cancer 10.7759/cureus.52132
spellingShingle Ramli, Zarina
Farizan, Aishah
Tamchek, Nizam
Haron, Zaharudin
Abdul Karim, Muhammad Khalis
Impact of image enhancement on the radiomics stability of diffusion-weighted MRI images of cervical cancer
title Impact of image enhancement on the radiomics stability of diffusion-weighted MRI images of cervical cancer
title_full Impact of image enhancement on the radiomics stability of diffusion-weighted MRI images of cervical cancer
title_fullStr Impact of image enhancement on the radiomics stability of diffusion-weighted MRI images of cervical cancer
title_full_unstemmed Impact of image enhancement on the radiomics stability of diffusion-weighted MRI images of cervical cancer
title_short Impact of image enhancement on the radiomics stability of diffusion-weighted MRI images of cervical cancer
title_sort impact of image enhancement on the radiomics stability of diffusion-weighted mri images of cervical cancer
url http://psasir.upm.edu.my/id/eprint/117350/
http://psasir.upm.edu.my/id/eprint/117350/
http://psasir.upm.edu.my/id/eprint/117350/
http://psasir.upm.edu.my/id/eprint/117350/1/117350.pdf