Residual analysis of the water resonance signal in breast lesions imaged with high spectral and spatial resolution (HiSS) MRI: A pilot study. Issue 1 (2nd January 2014)
- Record Type:
- Journal Article
- Title:
- Residual analysis of the water resonance signal in breast lesions imaged with high spectral and spatial resolution (HiSS) MRI: A pilot study. Issue 1 (2nd January 2014)
- Main Title:
- Residual analysis of the water resonance signal in breast lesions imaged with high spectral and spatial resolution (HiSS) MRI: A pilot study
- Authors:
- Weiss, William A.
Medved, Milica
Karczmar, Gregory S.
Giger, Maryellen L. - Abstract:
- Abstract : Purpose: : High spectral and spatial resolution magnetic resonance imaging (HiSS MRI) yields information on the local environment of suspicious lesions. Previous work has demonstrated the advantages of HiSS (complete fat‐suppression, improved image contrast, no required contrast agent, etc.), leading to initial investigations of water resonance lineshape for the purpose of breast lesion classification. The purpose of this study is to investigate a quantitative imaging biomarker, which characterizes non‐Lorentzian components of the water resonance in HiSS MRI datasets, for computer‐aided diagnosis (CADx). Methods: : The inhomogeneous broadening and non‐Lorentzian or "off‐peak" components seen in the water resonance of proton spectra of breast HiSS images are analyzed by subtracting a Lorentzian fit from the water peak spectra and evaluating the difference spectrum or "residual." The maxima of these residuals (referred to hereafter as "off‐peak components") tend to be larger in magnitude in malignant lesions, indicating increased broadening in malignant lesions. The authors considered only those voxels with the highest magnitude off‐peak components in each lesion, with the number of selected voxels dependent on lesion size. Our voxel‐based method compared the magnitudes and frequencies of off‐peak components of all voxels from all lesions in a database that included 15 malignant and 8 benign lesions (yielding ∼3900 voxels) based on the lesions' biopsy‐confirmedAbstract : Purpose: : High spectral and spatial resolution magnetic resonance imaging (HiSS MRI) yields information on the local environment of suspicious lesions. Previous work has demonstrated the advantages of HiSS (complete fat‐suppression, improved image contrast, no required contrast agent, etc.), leading to initial investigations of water resonance lineshape for the purpose of breast lesion classification. The purpose of this study is to investigate a quantitative imaging biomarker, which characterizes non‐Lorentzian components of the water resonance in HiSS MRI datasets, for computer‐aided diagnosis (CADx). Methods: : The inhomogeneous broadening and non‐Lorentzian or "off‐peak" components seen in the water resonance of proton spectra of breast HiSS images are analyzed by subtracting a Lorentzian fit from the water peak spectra and evaluating the difference spectrum or "residual." The maxima of these residuals (referred to hereafter as "off‐peak components") tend to be larger in magnitude in malignant lesions, indicating increased broadening in malignant lesions. The authors considered only those voxels with the highest magnitude off‐peak components in each lesion, with the number of selected voxels dependent on lesion size. Our voxel‐based method compared the magnitudes and frequencies of off‐peak components of all voxels from all lesions in a database that included 15 malignant and 8 benign lesions (yielding ∼3900 voxels) based on the lesions' biopsy‐confirmed diagnosis. Lesion classification was accomplished by comparing the average off‐peak component magnitudes and frequencies in malignant and benign lesions. The area under the ROC curve (AUC) was used as a figure of merit for both the voxel‐based and lesion‐based methods. Results: : In the voxel‐based task of distinguishing voxels from malignant and benign lesions, off‐peak magnitude yielded an AUC of 0.88 (95% confidence interval [0.84, 0.91]). In the lesion‐based task of distinguishing malignant and benign lesions, average off‐peak magnitude yielded an AUC 0.83 (95% confidence interval [0.61, 0.98]). Conclusions: : These promising AUC values suggest that analysis of the water‐resonance in each HiSS image voxel using "residual analysis" could have high diagnostic utility and could be used to enhance current CADx methods and allow detection of breast cancer without the need to inject contrast agents. … (more)
- Is Part Of:
- Medical physics. Volume 41:Issue 1(2014)
- Journal:
- Medical physics
- Issue:
- Volume 41:Issue 1(2014)
- Issue Display:
- Volume 41, Issue 1 (2014)
- Year:
- 2014
- Volume:
- 41
- Issue:
- 1
- Issue Sort Value:
- 2014-0041-0001-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2014-01-02
- Subjects:
- Functional imaging -- Image analysis -- Cancer
biomedical MRI -- cancer -- image classification -- medical image processing
echo planar spectroscopic imaging (EPSI) -- breast computer‐aided diagnosis -- lesion classification -- water resonance lineshape -- spectroscopic imaging
Involving electronic [emr] or nuclear [nmr] magnetic resonance, e.g. magnetic resonance imaging -- Biological material, e.g. blood, urine; Haemocytometers -- Digital computing or data processing equipment or methods, specially adapted for specific applications -- Image data processing or generation, in general
Medical imaging -- Magnetic resonance imaging -- Cancer -- Medical image noise -- Computer aided diagnosis -- Medical image quality -- Medical image spatial resolution -- Medical image contrast -- Spatial resolution -- Image analysis
Medical physics -- Periodicals
Medical physics
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Toepassingen
Biophysics
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Periodicals
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610.153 - Journal URLs:
- http://scitation.aip.org/content/aapm/journal/medphys ↗
https://aapm.onlinelibrary.wiley.com/journal/24734209 ↗
http://www.aip.org/ ↗ - DOI:
- 10.1118/1.4851615 ↗
- Languages:
- English
- ISSNs:
- 0094-2405
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
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- British Library DSC - 5531.130000
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British Library HMNTS - ELD Digital store - Ingest File:
- 9915.xml