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.

AbstractThe lack of information regarding the metabolism and pathophysiology of individual tumors limits, in part, both the development of new anti-cancer therapies and the optimal implementation of currently available treatments. Magnetic resonance [MR, including magnetic resonance imaging (MRI), magnetic resonance spectroscopy (MRS), and electron paramagnetic resonance (EPR)] provides a powerful tool to assess many aspects of tumor metabolism and pathophysiology. Moreover, since this information can be obtained non-destructively, pre-clinical results from cellular or animal models are often easily translated into the clinic. This review presents selected examples of how MR has been used to identify metabolic changes associated with apoptosis, detect therapeutic response prior to a change in tumor volume, optimize the combination of metabolic inhibitors with chemotherapy and/or radiation, characterize and exploit the influence of tumor pH on the effectiveness of chemotherapy, characterize tumor reoxygenation and the effects of modifiers of tumor oxygenation in individual tumors, image transgene expression and assess the efficacy of gene therapy. These examples provide an overview of several of the areas in which cellular and animal model studies using MR have contributed to our understanding of the effects of treatment on tumor metabolism and pathophysiology and the importance of tumor metabolism and pathophysiology as determinants of therapeutic response.

Background

High b-value diffusion-weighted images (DWI) are used for detection of clinically significant prostate cancer (csPCa). This study qualitatively and quantitatively compares synthesized DWI (sDWI) to acquired (aDWI) for detection of csPCa.

Methods

One hundred fifty-one consecutive patients who underwent prostate MRI and biopsy were included in the study. Axial DWI with b = 0, 500, 1000, and 2000 s/mm² using a 3T clinical scanner using a 32-channel phased-array body coil were acquired. We retrospectively synthesized DWI for b = 2000 s/mm² via extrapolation based on mono-exponential decay, using b = 0 and b = 500 s/mm² (sDWI₅₀₀) and b = 0, b = 500 s/mm², and b = 1000 s/mm² (sDWI₁₀₀₀). Differences in signal intensity between sDWI and aDWI were evaluated within different regions of interest (prostate alone, prostate plus 5 mm, 30 mm and 70 mm margin and full field of view). The maximum DWI value within each ROI was evaluated for prediction of csPCa. Classification accuracy was compared to Restriction Spectrum Imaging restriction score (RSIrs), a previously validated biomarker based on multi-exponential DWI. Discrimination of csPCa was evaluated via area under the receiver operating characteristic curve (AUC).

Results

Within the prostate, mean ± standard deviation of percent mean differences between sDWI and aDWI signal were -46 ± 35% for sDWI₁₀₀₀ and -67 ± 24% for sDWI₅₀₀. AUC for aDWI, sDWI_500, sDWI₁₀₀₀, and RSIrs within the prostate 0.62[95% confidence interval: 0.53, 0.71], 0.63[0.54, 0.72], 0.65[0.56, 0.73] and 0.78[0.71, 0.86], respectively.

Conclusion

sDWI is qualitatively comparable to aDWI within the prostate. However, hyperintense artifacts are introduced with sDWI in the surrounding pelvic tissue that interfere with quantitative cancer detection and might mask metastases. In the prostate, RSIrs yields superior quantitative csPCa detection than sDWI or aDWI.