Computational approach to radiogenomics of breast cancer: Luminal A and luminal B molecular subtypes are associated with imaging features on routine breast MRI extracted using computer vision algorithms. Issue 4 (17th March 2015)
- Record Type:
- Journal Article
- Title:
- Computational approach to radiogenomics of breast cancer: Luminal A and luminal B molecular subtypes are associated with imaging features on routine breast MRI extracted using computer vision algorithms. Issue 4 (17th March 2015)
- Main Title:
- Computational approach to radiogenomics of breast cancer: Luminal A and luminal B molecular subtypes are associated with imaging features on routine breast MRI extracted using computer vision algorithms
- Authors:
- Grimm, Lars J.
Zhang, Jing
Mazurowski, Maciej A. - Abstract:
- <abstract abstract-type="main"> <title> <x xml:space="preserve">Abstract</x> </title> <sec id="jmri24879-sec-0001" sec-type="section"> <title>Purpose</title> <p>To identify associations between semiautomatically extracted MRI features and breast cancer molecular subtypes.</p> </sec> <sec id="jmri24879-sec-0002" sec-type="section"> <title>Methods</title> <p>We analyzed routine clinical pre‐operative breast MRIs from 275 breast cancer patients at a single institution in this retrospective, Institutional Review Board‐approved study. Six fellowship‐trained breast imagers reviewed the MRIs and annotated the cancers. Computer vision algorithms were then used to extract 56 imaging features from the cancers including morphologic, texture, and dynamic features. Surrogate markers (estrogen receptor [ER], progesterone receptor [PR], human epidermal growth factor receptor‐2 [HER2]) were used to categorize tumors by molecular subtype: ER/PR+, HER2− (luminal A); ER/PR+, HER2+ (luminal B); ER/PR−, HER2+ (HER2); ER/PR/HER2− (basal). A multivariate analysis was used to determine associations between the imaging features and molecular subtype.</p> </sec> <sec id="jmri24879-sec-0003" sec-type="section"> <title>Results</title> <p>The imaging features were associated with both luminal A (<italic>P</italic> = 0.0007) and luminal B (<italic>P</italic> = 0.0063) molecular subtypes. No association was found for either HER2 (<italic>P</italic> = 0.2465) or basal (<italic>P</italic> = 0.1014)<abstract abstract-type="main"> <title> <x xml:space="preserve">Abstract</x> </title> <sec id="jmri24879-sec-0001" sec-type="section"> <title>Purpose</title> <p>To identify associations between semiautomatically extracted MRI features and breast cancer molecular subtypes.</p> </sec> <sec id="jmri24879-sec-0002" sec-type="section"> <title>Methods</title> <p>We analyzed routine clinical pre‐operative breast MRIs from 275 breast cancer patients at a single institution in this retrospective, Institutional Review Board‐approved study. Six fellowship‐trained breast imagers reviewed the MRIs and annotated the cancers. Computer vision algorithms were then used to extract 56 imaging features from the cancers including morphologic, texture, and dynamic features. Surrogate markers (estrogen receptor [ER], progesterone receptor [PR], human epidermal growth factor receptor‐2 [HER2]) were used to categorize tumors by molecular subtype: ER/PR+, HER2− (luminal A); ER/PR+, HER2+ (luminal B); ER/PR−, HER2+ (HER2); ER/PR/HER2− (basal). A multivariate analysis was used to determine associations between the imaging features and molecular subtype.</p> </sec> <sec id="jmri24879-sec-0003" sec-type="section"> <title>Results</title> <p>The imaging features were associated with both luminal A (<italic>P</italic> = 0.0007) and luminal B (<italic>P</italic> = 0.0063) molecular subtypes. No association was found for either HER2 (<italic>P</italic> = 0.2465) or basal (<italic>P</italic> = 0.1014) molecular subtype and the imaging features. A <italic>P</italic>‐value of 0.0125 (0.05/4) was considered significant.</p> </sec> <sec id="jmri24879-sec-0004" sec-type="section"> <title>Conclusion</title> <p>Luminal A and luminal B molecular subtype breast cancer are associated with semiautomatically extracted features from routine contrast enhanced breast MRI. J. Magn. Reson. Imaging 2015;42:902–907.</p> </sec> </abstract> … (more)
- Is Part Of:
- Journal of magnetic resonance imaging. Volume 42:Issue 4(2015)
- Journal:
- Journal of magnetic resonance imaging
- Issue:
- Volume 42:Issue 4(2015)
- Issue Display:
- Volume 42, Issue 4 (2015)
- Year:
- 2015
- Volume:
- 42
- Issue:
- 4
- Issue Sort Value:
- 2015-0042-0004-0000
- Page Start:
- 902
- Page End:
- 907
- Publication Date:
- 2015-03-17
- Subjects:
- Magnetic resonance imaging -- Periodicals
616 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1522-2586 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/jmri.24879 ↗
- Languages:
- English
- ISSNs:
- 1053-1807
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5010.791000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 3507.xml