Colleen Bailey, Bernard Siow, Eleftheria Panagiotaki, John H Hipwell, Thomy Mertzanidou, Julie Owen, Patrycja Gazinska, Sarah E Pinder, Daniel C Alexander, David J Hawkes
{"title":"乳腺癌及其周围基质弥散磁共振成像的微结构模型:一项体外研究。","authors":"Colleen Bailey, Bernard Siow, Eleftheria Panagiotaki, John H Hipwell, Thomy Mertzanidou, Julie Owen, Patrycja Gazinska, Sarah E Pinder, Daniel C Alexander, David J Hawkes","doi":"10.1002/nbm.3679","DOIUrl":null,"url":null,"abstract":"<p><p>The diffusion signal in breast tissue has primarily been modelled using apparent diffusion coefficient (ADC), intravoxel incoherent motion (IVIM) and diffusion tensor (DT) models, which may be too simplistic to describe the underlying tissue microstructure. Formalin-fixed breast cancer samples were scanned using a wide range of gradient strengths, durations, separations and orientations. A variety of one- and two-compartment models were tested to determine which best described the data. Models with restricted diffusion components and anisotropy were selected in most cancerous regions and there were no regions in which conventional ADC or DT models were selected. Maps of ADC generally related to cellularity on histology, but maps of parameters from more complex models suggest that both overall cell volume fraction and individual cell size can contribute to the diffusion signal, affecting the specificity of ADC to the tissue microstructure. The areas of coherence in diffusion anisotropy images were small, approximately 1 mm, but the orientation corresponded to stromal orientation patterns on histology.</p>","PeriodicalId":55035,"journal":{"name":"IBM systems journal","volume":"3 2","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5244665/pdf/","citationCount":"0","resultStr":"{\"title\":\"Microstructural models for diffusion MRI in breast cancer and surrounding stroma: an ex vivo study.\",\"authors\":\"Colleen Bailey, Bernard Siow, Eleftheria Panagiotaki, John H Hipwell, Thomy Mertzanidou, Julie Owen, Patrycja Gazinska, Sarah E Pinder, Daniel C Alexander, David J Hawkes\",\"doi\":\"10.1002/nbm.3679\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The diffusion signal in breast tissue has primarily been modelled using apparent diffusion coefficient (ADC), intravoxel incoherent motion (IVIM) and diffusion tensor (DT) models, which may be too simplistic to describe the underlying tissue microstructure. Formalin-fixed breast cancer samples were scanned using a wide range of gradient strengths, durations, separations and orientations. A variety of one- and two-compartment models were tested to determine which best described the data. Models with restricted diffusion components and anisotropy were selected in most cancerous regions and there were no regions in which conventional ADC or DT models were selected. Maps of ADC generally related to cellularity on histology, but maps of parameters from more complex models suggest that both overall cell volume fraction and individual cell size can contribute to the diffusion signal, affecting the specificity of ADC to the tissue microstructure. The areas of coherence in diffusion anisotropy images were small, approximately 1 mm, but the orientation corresponded to stromal orientation patterns on histology.</p>\",\"PeriodicalId\":55035,\"journal\":{\"name\":\"IBM systems journal\",\"volume\":\"3 2\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5244665/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IBM systems journal\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1002/nbm.3679\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2016/12/21 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IBM systems journal","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1002/nbm.3679","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2016/12/21 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
Microstructural models for diffusion MRI in breast cancer and surrounding stroma: an ex vivo study.
The diffusion signal in breast tissue has primarily been modelled using apparent diffusion coefficient (ADC), intravoxel incoherent motion (IVIM) and diffusion tensor (DT) models, which may be too simplistic to describe the underlying tissue microstructure. Formalin-fixed breast cancer samples were scanned using a wide range of gradient strengths, durations, separations and orientations. A variety of one- and two-compartment models were tested to determine which best described the data. Models with restricted diffusion components and anisotropy were selected in most cancerous regions and there were no regions in which conventional ADC or DT models were selected. Maps of ADC generally related to cellularity on histology, but maps of parameters from more complex models suggest that both overall cell volume fraction and individual cell size can contribute to the diffusion signal, affecting the specificity of ADC to the tissue microstructure. The areas of coherence in diffusion anisotropy images were small, approximately 1 mm, but the orientation corresponded to stromal orientation patterns on histology.