Minkowski functionals: An MRI texture analysis tool for determination of the aggressiveness of breast cancer.
Background: This work aims to see whether Minkowski Functionals can be used to distinguish between cancer types before chemotherapy treatment has begun, and whether a response to treatment can be predicted by an initial scan alone. Methods: Fat-nulled T1w 3T DCE-MRI scans were taken of 100 cases of...
| Published in: | Journal of Magnetic Resonance Imaging Vol. 43; no. 4; pp. 903 - 911 |
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| Main Authors: | , , |
| Format: | pictorial research tables/charts Journal Article |
| Published: |
Wiley-Blackwell
Apr2016
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=113962398&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 113962398 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10531807 O63 jtl: Journal of Magnetic Resonance Imaging issn: 10531807 maglogo: Y pubinfo: dt: Apr2016 vid: 43 iid: 4 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 113962398 113962398 NLM26453892 113962398 10.1002/jmri.25057 NLM26453892 113962398 ppf: 903 ppct: 8 formats: tig: atl: Minkowski functionals: An MRI texture analysis tool for determination of the aggressiveness of breast cancer. aug: au: Fox, Michael J. Gibbs, Peter Pickles, Martin D. affil: Centre for Magnetic Resonance Investigations, HYMS at University of Hull, Hull United Kingdom sug: subj: Image Processing, Computer Assisted Methods Breast Neoplasms Pathology Magnetic Resonance Imaging Breast Neoplasms Nonparametric Statistics Female Human Adult Antineoplastic Agents, Combined Administration and Dosage Algorithms Pharmacokinetics Epirubicin Administration and Dosage Prognosis Middle Age Software Treatment Outcomes Breast Neoplasms Drug Therapy Biopsy Drug Therapy Methods Aged Reproducibility of Results Cyclophosphamide Administration and Dosage Hydrocarbons Administration and Dosage Retrospective Design Neoplasm Metastasis Validation Studies Comparative Studies Evaluation Research Multicenter Studies Adult: 19-44 years Middle Aged: 45-64 years Aged: 65+ years Female ab: Background: This work aims to see whether Minkowski Functionals can be used to distinguish between cancer types before chemotherapy treatment has begun, and whether a response to treatment can be predicted by an initial scan alone. Methods: Fat-nulled T1w 3T DCE-MRI scans were taken of 100 cases of biopsy confirmed breast cancer and a series of binary images created on lesion containing slices. Minkowski Functionals were calculated for each binary image and the change in these values as the binary threshold was raised was described using 6(th) order polynomials. These polynomials were used to compare between patient subgroups, for triple negative breast cancer (TNBC) status, chemotherapy response, biopsy grade, nodal status, and lymphovascular invasion status. Results: When using Minkowski Functionals statistically significant (P < 0.05) differences were found between TNBC status, biopsy grade, and lymphovascular invasion status subgroups for all methodologies. The analysis performance did not appear to be affected by the number of threshold steps used. Most notably, very strong differences (P ≤ 0.01) were found between TNBC and other intrinsic subtype patients. When analyzed with a binary logistic regression model, an area under the curve value of 0.917 (0.846-0.987, 95% confidence interval) for TNBC classification was found. Conclusion: The method of texture analysis presented here provides a novel way to characterize tumors, and demonstrates clear differences between cancer groups which are detectable before treatment begins, and can help with treatment planning as a valuable prognosis tool. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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