title: Optimization of image reconstruction for magnetic resonance imaging-guided near-infrared diffuse optical spectroscopy in breast.
abstract: An optimized approach to nonlinear iterative reconstruction of magnetic resonance imaging (MRI)-guided near-infrared spectral tomography (NIRST) images was developed using an L-curve-based algorithm for the choice of regularization parameter. This approach was applied to clinical exam data to maximize the reconstructed values differentiating malignant and benign lesions. MRI/NIRST data from 25 patients with abnormal breast readings (BI-RADS category 4-5) were analyzed using this optimal regularization methodology, and the results showed enhanced p values and area under the curve (AUC) for the task of differentiating malignant from benign lesions. Of the four absorption parameters and two scatter parameters, the most significant differences for benign versus malignant were total hemoglobin (HbT) and tissue optical index (TOI) with p values = 0.01 and 0.001, and AUC values = 0.79 and 0.94, respectively, in terms of HbT and TOI. This dramatically improved the values relative to fixed regularization (p value = 0.02 and 0.003; AUC = 0.75 and 0.83) showing that more differentiation was possible with the optimal method. Through a combination of both biomarkers, HbT and TOI, the AUC increased from 82.9% (fixed regulation = 0.1) to 94.3% (optimal method).
authors.affiliation: Dartmouth College, Thayer School of Engineering, Hanover, New Hampshire 03755, United States.
authors.forename: Yan
authors.initials: Y
authors.lastname: Zhao
authors.affiliation: Dartmouth College, Thayer School of Engineering, Hanover, New Hampshire 03755, United States.
authors.forename: Michael A
authors.initials: MA
authors.lastname: Mastanduno
authors.affiliation: Dartmouth College, Thayer School of Engineering, Hanover, New Hampshire 03755, United States.
authors.forename: Shudong
authors.initials: S
authors.lastname: Jiang
authors.affiliation: Dartmouth College, Thayer School of Engineering, Hanover, New Hampshire 03755, United States.
authors.forename: Fadi
authors.initials: F
authors.lastname: Ei-Ghussein
authors.affiliation: Dartmouth College, Geisel School of Medicine, Department of Community and Family Medicine, Hanover, New Hampshire 03755, United States.
authors.forename: Jiang
authors.initials: J
authors.lastname: Gui
authors.affiliation: Dartmouth College, Thayer School of Engineering, Hanover, New Hampshire 03755, United States.
authors.forename: Brian W
authors.initials: BW
authors.lastname: Pogue
authors.affiliation: Dartmouth College, Thayer School of Engineering, Hanover, New Hampshire 03755, United StatesbDartmouth College, Geisel School of Medicine, Department of Community and Family Medicine, Hanover, New Hampshire 03755, United StatescDartmouth College, Geisel S.
authors.forename: Keith D
authors.initials: KD
authors.lastname: Paulsen
mesh_terms: D000465:Algorithms; D014408:Biomarkers, Tumor / Q000032:analysis*; D001943:Breast Neoplasms / Q000737:chemistry* / Q000175:diagnosis*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods*; D057054:Molecular Imaging / Q000379:methods*; D064847:Multimodal Imaging / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D019265:Spectroscopy, Near-Infrared / Q000379:methods*
chemical_list: D014408:Biomarkers, Tumor