{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,22]],"date-time":"2026-06-22T15:43:17Z","timestamp":1782142997001,"version":"3.54.5"},"reference-count":34,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2025,8,14]],"date-time":"2025-08-14T00:00:00Z","timestamp":1755129600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002383","name":"ngoing research funding program","doi-asserted-by":"publisher","award":["ORF-2025-1148"],"award-info":[{"award-number":["ORF-2025-1148"]}],"id":[{"id":"10.13039\/501100002383","id-type":"DOI","asserted-by":"publisher"}]},{"name":"King Saud University","award":["ORF-2025-1148"],"award-info":[{"award-number":["ORF-2025-1148"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Background\/Objectives: This study aimed to evaluate the diagnostic performance of simplified intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) parameters in distinguishing malignant from benign breast lesions, and to explore their association with clinicopathological features. Methods: This retrospective study included 108 women who underwent breast MRI with multi-b-value DWI (0, 20, 200, 500, 800 s\/mm2). Of those 108 women, 73 had pathologically confirmed malignant lesions. IVIM maps (ADC_map, D, D*, and perfusion fraction f) were generated using IB-Diffusion\u2122 software version 21.12. Lesions were manually segmented by radiologists, and clinicopathological data including receptor status, Ki-67 index, cancer type, histologic grade, and molecular subtype were extracted from medical records. Nonparametric tests and ROC analysis were used to assess group differences and diagnostic performance. Additionally, a binary logistic regression model combining D, D*, and f was developed to evaluate their joint diagnostic utility, with ROC analysis applied to the model\u2019s predicted probabilities. Results: Malignant lesions demonstrated significantly lower diffusion parameters compared to benign lesions, including ADC_map (p = 0.004), D (p = 0.009), and D* (p = 0.016), indicating restricted diffusion in cancerous tissue. In contrast, the perfusion fraction (f) did not show a significant difference (p = 0.202). ROC analysis revealed moderate diagnostic accuracy for ADC_map (AUC = 0.671), D (AUC = 0.657), and D* (AUC = 0.644), while f showed poor discrimination (AUC = 0.576, p = 0.186). A combined logistic regression model using D, D*, and f significantly improved diagnostic performance, achieving an AUC of 0.725 (p &lt; 0.001), with 67.1% sensitivity and 74.3% specificity. ADC_map achieved the highest sensitivity (100%) but had low specificity (11.4%). Among clinicopathological features, only histologic grade was significantly associated with IVIM metrics, with higher-grade tumors showing lower ADC_map and D* values (p = 0.042 and p = 0.046, respectively). No significant associations were found between IVIM parameters and ER, PR, HER2 status, Ki-67 index, cancer type, or molecular subtype. Conclusions: Simplified IVIM DWI offers moderate accuracy in distinguishing malignant from benign breast lesions, with diffusion-related parameters (ADC_map, D, D*) showing the strongest diagnostic value. Incorporating D, D*, and f into a combined model enhanced diagnostic performance compared to individual IVIM metrics, supporting the potential of multivariate IVIM analysis in breast lesion characterization. Tumor grade was the only clinicopathological feature consistently associated with diffusion metrics, suggesting that IVIM may reflect underlying tumor differentiation but has limited utility for molecular subtype classification.<\/jats:p>","DOI":"10.3390\/diagnostics15162033","type":"journal-article","created":{"date-parts":[[2025,8,14]],"date-time":"2025-08-14T14:51:46Z","timestamp":1755183106000},"page":"2033","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Evaluating Simplified IVIM Diffusion Imaging for Breast Cancer Diagnosis and Pathological Correlation"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6608-6922","authenticated-orcid":false,"given":"Abdullah Hussain","family":"Abujamea","sequence":"first","affiliation":[{"name":"Department of Radiology and Medical Imaging, College of Medicine, King Saud University (KSU), Riyadh 11461, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Salma Abdulrahman","family":"Salem","sequence":"additional","affiliation":[{"name":"Department of Radiology and Medical Imaging, College of Medicine, King Saud University (KSU), Riyadh 11461, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-5944-0381","authenticated-orcid":false,"given":"Hend Samir","family":"Ibrahim","sequence":"additional","affiliation":[{"name":"Royal Commission Medical Centre, Yanbu 46457, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Manal Ahmed","family":"ElRefaei","sequence":"additional","affiliation":[{"name":"Alahrar Teaching Hospital, General Organization for Teaching Hospitals and Institutes, Cairo 11697, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6646-6378","authenticated-orcid":false,"given":"Areej Saud","family":"Aloufi","sequence":"additional","affiliation":[{"name":"Department of Radiological Sciences, College of Applied Medical Sciences, King Saud University (KSU), P.O. Box 145111, Riyadh 11433, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9132-4569","authenticated-orcid":false,"given":"Abdulmajeed","family":"Alotabibi","sequence":"additional","affiliation":[{"name":"Department of Radiological Sciences, College of Applied Medical Sciences, King Saud bin Abdulaziz University for Health Sciences, Riyadh 11426, Saudi Arabia"},{"name":"King Abdullah International Medical Research Centre, National Guard Health Affairs, Riyadh 11426, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8612-1721","authenticated-orcid":false,"given":"Salman Mohammed","family":"Albeshan","sequence":"additional","affiliation":[{"name":"Department of Radiological Sciences, College of Applied Medical Sciences, King Saud University (KSU), P.O. Box 145111, Riyadh 11433, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fatma","family":"Eliraqi","sequence":"additional","affiliation":[{"name":"The General Organization for Teaching Hospitals and Institutes, (National Institute of Neurology and Urology), Cairo 11765, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,8,14]]},"reference":[{"key":"ref_1","first-page":"229","article-title":"Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries","volume":"73","author":"Sung","year":"2023","journal-title":"CA Cancer J. 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