{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T04:22:40Z","timestamp":1787026960991,"version":"build-2736575974"},"reference-count":35,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2022,2,3]],"date-time":"2022-02-03T00:00:00Z","timestamp":1643846400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Oncol."],"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To explore the value of quantitative parameters derived from diffusion spectrum imaging (DSI) in preoperatively predicting human epidermal growth factor receptor 2 (HER2) status in patients with breast cancer.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>In this prospective study, 114 and 56 female patients with invasive ductal carcinoma were consecutively included in a derivation cohort and an independent validation cohort, respectively. Each patient was categorized into HER2-positive or HER2-negative groups based on the pathologic result. All patients underwent DSI and conventional MRI including dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted imaging (DWI). The tumor size, type of the time-signal intensity curve (TIC) from DCE-MRI, apparent diffusion coefficient (ADC) from DWI, and quantitative parameters derived from DSI, including diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), mean apparent propagator (MAP), and neurite orientation dispersion and density imaging (NODDI) of primary tumors, were measured and compared between the HER2-positive and HER2-negative groups in the derivation cohort. Univariable and multivariable logistic regression analyses were used to determine the potential independent predictors of HER2 status. The discriminative ability of quantitative parameters was assessed by receiver operating characteristic (ROC) curve analyses and validated in the independent cohort.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      In the derivation cohort, the tumor size, TIC type, and ADC values did not differ between the HER2-positive and HER2-negative groups (\n                      <jats:italic>p<\/jats:italic>\n                      = 0.126\u20130.961). DSI quantitative parameters including axial kurtosis of DKI (DKI_AK), non-Gaussianity (MAP_NG), axial non-Gaussianity (MAP_NG\n                      <jats:sub>Ax<\/jats:sub>\n                      ), radial non-Gaussianity (MAP_NG\n                      <jats:sub>Rad<\/jats:sub>\n                      ), return-to-origin probability (MAP_RTOP), return-to-axis probability of MAP (MAP_RTAP), and intracellular volume fraction of NODDI (NODDI_ICVF) were lower in the HER2-positive group than in the HER2-negative group (\n                      <jats:italic>p<\/jats:italic>\n                      \u2264 0.001\u20130.035). DSI quantitative parameters including radial diffusivity (DTI_RD), mean diffusivity of DTI (DTI_MD), mean squared diffusion (MAP_MSD), and q-space inverse variance of MAP (MAP_QIV) were higher in the HER2-positive group than in the HER2-negative group (\n                      <jats:italic>p<\/jats:italic>\n                      = 0.016\u20130.049). The ROC analysis showed that the area under the curve (AUC) of ADC was 0.632 and 0.568, respectively, in the derivation and validation cohorts. The AUC values of DSI quantitative parameters ranged from 0.628 to 0.700 and from 0.673 to 0.721, respectively, in the derivation and validation cohorts. Logistic regression analysis showed that only NODDI_ICVF was an independent predictor of HER2 status (\n                      <jats:italic>p<\/jats:italic>\n                      = 0.001), with an AUC of 0.700 and 0.721, respectively, in the derivation and validation cohorts.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>DSI could be helpful for preoperative prediction of HER2, but DSI alone may not be sufficient in predicting HER2 status preoperatively in patients with breast cancer.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fonc.2022.817070","type":"journal-article","created":{"date-parts":[[2022,2,3]],"date-time":"2022-02-03T00:55:39Z","timestamp":1643849739000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":22,"title":["Quantitative Parameters of Diffusion Spectrum Imaging: HER2 Status Prediction in Patients With Breast Cancer"],"prefix":"10.3389","volume":"12","author":[{"given":"Chunping","family":"Mao","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiayi","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mengzhu","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xu","family":"Yan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zehong","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dongye","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiang","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jun","family":"Shen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2022,2,3]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"394","DOI":"10.3322\/caac.21492","article-title":"Global Cancer Statistics 2018: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries [Published Correction Appears in CA Cancer J Clin","volume":"68","author":"Bray","year":"2018","journal-title":"CA Cancer J Clin"},{"key":"B2","doi-asserted-by":"publisher","first-page":"288","DOI":"10.1001\/jama.2018.19323","article-title":"Breast Cancer Treatment: A Review","volume":"321","author":"Waks","year":"2019","journal-title":"JAMA"},{"key":"B3","article-title":"HER-2\/Neu (C-Erb-B2) Gene and Protein in Breast Cancer","volume":"112","author":"Ross","year":"1999","journal-title":"Am J Clin Pathol"},{"key":"B4","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa1914510","article-title":"Trastuzumab Deruxtecan in Previously Treated HER2-Positive Breast Cancer","volume":"382","author":"Modi","year":"2020","journal-title":"N Engl J Med"},{"key":"B5","doi-asserted-by":"publisher","DOI":"10.1186\/1477-7819-12-289","article-title":"HER-2 Positive Breast Cancer is Associated With an Increased Risk of Positive Cavity Margins After Initial Lumpectomy","volume":"12","author":"Jia","year":"2014","journal-title":"World J Surg Oncol"},{"key":"B6","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa1703643","article-title":"Adjuvant Pertuzumab and Trastuzumab in Early HER2-Positive Breast Cancer [Published Correction Appears in N Engl J Med","volume":"377","author":"von Minckwitz","year":"2017","journal-title":"N Engl J Med"},{"key":"B7","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.26575","article-title":"Analysis of the Effects of Noise, DWI Sampling, and Value of Assumed Parameters in Diffusion MRI Models","volume":"78","author":"Hutchinson","year":"2017","journal-title":"Magn Reson Med"},{"key":"B8","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.20642","article-title":"Mapping Complex Tissue Architecture With Diffusion Spectrum Magnetic Resonance Imaging","volume":"54","author":"Wedeen","year":"2005","journal-title":"Magn Reson Med"},{"key":"B9","doi-asserted-by":"publisher","DOI":"10.2463\/mrms.mp.2019-0015","article-title":"Comparison of Q-Space Reconstruction Methods for Undersampled Diffusion Spectrum Imaging Data","volume":"19","author":"Varela-Mattatall","year":"2020","journal-title":"Magn Reson Med Sci"},{"key":"B10","doi-asserted-by":"publisher","DOI":"10.1017\/S0033291715002767","article-title":"Different Neural Substrates for Executive Functions in Youths With ADHD: A Diffusion Spectrum Imaging Tractography Study","volume":"46","author":"Chiang","year":"2016","journal-title":"Psychol Med"},{"key":"B11","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-021-07878-x","article-title":"Quantitative Visual Pathway Abnormalities Predict Visual Field Defects in Patients With Pituitary Adenomas: A Diffusion Spectrum Imaging Study","volume":"31","author":"Liang","year":"2021","journal-title":"Eur Radiol"},{"key":"B12","doi-asserted-by":"publisher","DOI":"10.1016\/j.acra.2018.09.003","article-title":"The Role of Diffusion Weighted Imaging as Supplement to Dynamic Contrast Enhanced Breast MRI: Can it Help Predict Malignancy, Histologic Grade and Recurrence","volume":"26","author":"Roknsharifi","year":"2019","journal-title":"Acad Radiol"},{"key":"B13","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.24519","article-title":"Correlations Between Apparent Diffusion Coefficient Values of Invasive Ductal Carcinoma and Pathologic Factors on Diffusion-Weighted MRI at 3.0 Tesla","volume":"41","author":"Park","year":"2015","journal-title":"J Magn Reson Imaging"},{"key":"B14","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.25481","article-title":"Diagnostic Performance of Diffusion Tensor Imaging Parameters in Breast Cancer and Correlation With the Prognostic Factors","volume":"45","author":"Onaygil","year":"2017","journal-title":"J Magn Reson Imaging"},{"key":"B15","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-020-07169-x","article-title":"A Comparative Study of the Value of Amide Proton Transfer-Weighted Imaging and Diffusion Kurtosis Imaging in the Diagnosis and Evaluation of Breast Cancer","volume":"31","author":"Meng","year":"2021","journal-title":"Eur Radiol"},{"key":"B16","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1016\/j.neuroimage.2013.04.016","article-title":"Mean Apparent Propagator (MAP) MRI: A Novel Diffusion Imaging Method for Mapping Tissue Microstructure","volume":"78","author":"\u00d6zarslan","year":"2013","journal-title":"Neuroimage"},{"key":"B17","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2006.01.015","article-title":"User-Guided 3D Active Contour Segmentation of Anatomical Structures: Significantly Improved Efficiency and Reliability","volume":"31","author":"Yushkevich","year":"2006","journal-title":"Neuroimage"},{"key":"B18","doi-asserted-by":"publisher","DOI":"10.1148\/radiology.211.1.r99ap38101","article-title":"Dynamic Breast MR Imaging: Are Signal Intensity Time Course Data Useful for Differential Diagnosis of Enhancing Lesions","volume":"211","author":"Kuhl","year":"1999","journal-title":"Radiol"},{"key":"B19","doi-asserted-by":"publisher","first-page":"3997","DOI":"10.1200\/JCO.2013.50.9984","article-title":"Recommendations for Human Epidermal Growth Factor Receptor 2 Testing in Breast Cancer: American Society of Clinical Oncology\/College of American Pathologists Clinical Practice Guideline Update","volume":"31","author":"Wolff","year":"2013","journal-title":"J Clin Oncol"},{"key":"B20","doi-asserted-by":"publisher","DOI":"10.1159\/000512174","article-title":"Estrogen Receptor Is Expressed in Uveal Melanoma: A Potential Target for Therapy","volume":"7","author":"Schoenfield","year":"2021","journal-title":"Ocul Oncol Pathol"},{"key":"B21","doi-asserted-by":"publisher","DOI":"10.1093\/annonc\/mdr304","article-title":"Strategies for Subtypes\u2013Dealing With the Diversity of Breast Cancer: Highlights of the St. Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2011","volume":"22","author":"Goldhirsch","year":"2011","journal-title":"Ann Oncol"},{"key":"B22","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.24934","article-title":"Histogram Analysis of Apparent Diffusion Coefficient at 3.0t: Correlation With Prognostic Factors and Subtypes of Invasive Ductal Carcinoma","volume":"42","author":"Kim","year":"2015","journal-title":"J Magn Reson Imaging"},{"key":"B23","doi-asserted-by":"publisher","DOI":"10.1155\/2019\/2972189","article-title":"Histogram Analysis and Visual Heterogeneity of Diffusion-Weighted Imaging With Apparent Diffusion Coefficient Mapping in the Prediction of Molecular Subtypes of Invasive Breast Cancers","volume":"2019","author":"Horvat","year":"2019","journal-title":"Contrast Media Mol Imaging"},{"key":"B24","doi-asserted-by":"publisher","DOI":"10.1016\/j.mri.2020.12.001","article-title":"Improved Discrimination of Molecular Subtypes in Invasive Breast Cancer: Comparison of Multiple Quantitative Parameters From Breast MRI","volume":"77","author":"Du","year":"2021","journal-title":"Magn Reson Imaging"},{"key":"B25","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-021-08166-4","article-title":"Characterization of Breast Cancer Subtypes Based on Quantitative Assessment of Intratumoral Heterogeneity Using Dynamic Contrast-Enhanced and Diffusion-Weighted Magnetic Resonance Imaging","author":"Kim","year":"2021","journal-title":"Eur Radiol"},{"key":"B26","doi-asserted-by":"publisher","DOI":"10.3389\/fonc.2019.01229","article-title":"Diagnostic Performance of Diffusion Tensor Imaging for Characterizing Breast Tumors: A Comprehensive Meta-Analysis","volume":"9","author":"Wang","year":"2019","journal-title":"Front Oncol"},{"key":"B27","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.27489","article-title":"Diffusivity in Breast Malignancies Analyzed for B\u2009>\u20091000\u2009s\/Mm2 at 1\u2009Mm in-Plane Resolutions: Insight From Gaussian and non-Gaussian Behaviors","volume":"53","author":"Otikovs","year":"2021","journal-title":"J\u00a0Magn Reson Imaging"},{"key":"B28","doi-asserted-by":"publisher","first-page":"182","DOI":"10.1186\/s12967-019-1911-6","article-title":"The Volumetric-Tumour Histogram-Based Analysis of Intravoxel Incoherent Motion and non-Gaussian Diffusion MRI: Association With Prognostic Factors in HER2-Positive Breast Cancer","volume":"17","author":"You","year":"2019","journal-title":"J Transl Med"},{"key":"B29","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2008.12.018","article-title":"Does Diffusion Kurtosis Imaging Lead to Better Neural Tissue Characterization","volume":"45","author":"Cheung","year":"2009","journal-title":"A Rodent Brain Maturation Study NeuroImage"},{"key":"B30","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.26697","article-title":"Diffusion-Weighted Imaging (DWI) With Apparent Diffusion Coefficient (ADC) Mapping as a Quantitative Imaging Biomarker for Prediction of Immunohistochemical Receptor Status, Proliferation Rate, and Molecular Subtypes of Breast Cancer","volume":"50","author":"Horvat","year":"2019","journal-title":"J Magn Reson Imaging"},{"key":"B31","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.20508","article-title":"Diffusional Kurtosis Imaging: The Quantification of non-Gaussian Water Diffusion by Means of Magnetic Resonance Imaging","volume":"53","author":"Jensen","year":"2005","journal-title":"Magn Reson Med"},{"key":"B32","doi-asserted-by":"publisher","DOI":"10.1259\/bjr.20150614","article-title":"Apparent Diffusion Coefficient Value in Invasive Ductal Carcinoma at 3.0 Tesla: Is it Correlated With Prognostic Factors","volume":"89","author":"Guvenc","year":"2016","journal-title":"Br J Radiol"},{"key":"B33","doi-asserted-by":"publisher","DOI":"10.3389\/fnagi.2020.563595","article-title":"Mean Apparent Propagator MRI Is Better Than Conventional Diffusion Tensor Imaging for the Evaluation of Parkinson's Disease: A Prospective Pilot Study","volume":"12","author":"Le","year":"2020","journal-title":"Front Aging Neurosci"},{"key":"B34","doi-asserted-by":"publisher","first-page":"124","DOI":"10.1186\/s12880-020-00524-w","article-title":"Differentiation Between High-Grade Gliomas and Solitary Brain Metastases: A Comparison of Five Diffusion-Weighted MRI Models","volume":"20","author":"Mao","year":"2020","journal-title":"BMC Med Imaging"},{"key":"B35","doi-asserted-by":"publisher","DOI":"10.1007\/s11547-018-0908-1","article-title":"Role of DCE-MR in Predicting Breast Cancer Subtypes","volume":"123","author":"Macchini","year":"2018","journal-title":"Radiol Med"}],"container-title":["Frontiers in Oncology"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fonc.2022.817070\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,2,3]],"date-time":"2022-02-03T00:55:48Z","timestamp":1643849748000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fonc.2022.817070\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,2,3]]},"references-count":35,"alternative-id":["10.3389\/fonc.2022.817070"],"URL":"https:\/\/doi.org\/10.3389\/fonc.2022.817070","relation":{},"ISSN":["2234-943X"],"issn-type":[{"value":"2234-943X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,2,3]]},"article-number":"817070"}}