MR-Guided Near-Infrared Spectral Tomography Increases Diagnostic Performance of Breast MRI

Abstract

Purpose The purpose of this study was to determine the diagnostically most important molecular biomarkers quantified by magnetic resonance-guided (MR) near-infrared spectral tomography (NIRST) that distinguish malignant breast lesions from benign abnormalities when combined with outcomes from clinical breast MRI. Experimental Design The study was HIPAA compliant and approved by the Dartmouth Institutional Review Board, the NIH, the United States State Department, and Xijing Hospital. MR-guided NIRST evaluated hemoglobin, water, and lipid content in regions of interest defined by concurrent dynamic contrast-enhanced MRI (DCE-MRI) in the breast. MRI plus NIRST was performed in 44 subjects (median age, 46, age range, 20–81 years), 28 of whom had subsequent malignant pathologic diagnoses, and 16 had benign conditions. A subset of 30 subject examinations yielded optical data that met minimum sensitivity requirements to the suspicious lesion and were included in the analyses of diagnostic performance. Results In the subset of 30 subject examinations meeting minimum optical data sensitivity criterion, the MR-guided NIRST separated malignant from benign lesions using total hemoglobin (HbT; P < 0.01) and tissue optical index (TOI; P < 0.001). Combined MRI plus TOI data caused one false positive and 1 false negative, and produced the best diagnostic performance, yielding an AUC of 0.95, sensitivity of 95%, specificity of 89%, positive predictive value of 95%, and negative predictive value of 89%, respectively. Conclusions MRI plus NIRST results correlated well with histopathologic diagnoses and could provide additional information to reduce the number of MRI-directed biopsies.

Portable, parallel 9-wavelength near-infrared spectral tomography (NIRST) system for efficient characterization of breast cancer within the clinical oncology infusion suite

“…Mean StO 2 within the breast varied from 58.5% to 88.0% with an overall group mean value of 70.5%. The results reported here are consistent with several other studies of asymptomatic breast tissue [38,40,41], which also indicate that optical and physiological parameters are significantly affected by biological factors such as age, menopausal status, hormone use, and BMI. Because of the small number of normal subjects evaluated in this study, discussion focuses on the effects of breast density on the recovered optical parameters.…”

“…Unlike some other image-guided NIRS systems [20,38], where 2D/3D meshes are constructed from additional image data obtained with MRI and ultrasound, the portable NIRST system depends on the fiber-breast interface to make case-specific meshes. Two types of meshes were created with surface curvature matching the corresponding interfaces, and the non-contacting area extended to mimic the natural shape of the breast under a modest amount of compression.…”

Quantitative photoacoustic image reconstruction improves accuracy in deep tissue structures

“…Spectral endpoints of HbT, StO 2 , and water are more clinically relevant, and could provide insight into the functional status of a suspicious lesion [40]. This example of a spectral reconstruction demonstrates that it is possible to recover spectral images with similar accuracy to the single wavelength case.…”

Multiobjective guided priors improve the accuracy of near-infrared spectral tomography for breast imaging

“…1,2 However, most studies indicate that NIRST alone may not be capable of providing the quantitative accuracy required for clinical applications because of spatial resolution limitations. 3 High-spatial resolution guidance from structural images, such as x-ray or MRI, has improved the quantitative accuracy of NIRST.…”

“…2 To incorporate prior information from MRI into NIRST, previous approaches have segmented the MRI images into tumor and nontumor regions, each of which is assumed to be optically homogeneous. This "hard-prior" strategy reduces the size of the inversion problem by lumping regions together into a few super pixels or zones.…”