Evaluation of an Automated Analysis Tool for Prostate Cancer Prediction Using Multiparametric Magnetic Resonance Imaging

Objective To evaluate the diagnostic performance of an automated analysis tool for the assessment of prostate cancer based on multiparametric magnetic resonance imaging (mpMRI) of the prostate. Methods A fully automated analysis tool was used for a retrospective analysis of mpMRI sets (T2-weighted, T1-weighted dynamic contrast-enhanced, and diffusion-weighted sequences). The software provided a malignancy prediction value for each image pixel, defined as Malignancy Attention Index (MAI) that can be depicted as a colour map overlay on the original images. The malignancy maps were compared to histopathology derived from a combination of MRI-targeted and systematic transperineal MRI/TRUS-fusion biopsies. Results In total, mpMRI data of 45 patients were evaluated. With a sensitivity of 85.7% (with 95% CI of 65.4-95.0), a specificity of 87.5%(with 95% CI of 69.0-95.7) and a diagnostic accuracy of 86.7% (with 95% CI of 73.8-93.8) for detection of prostate cancer, the automated analysis results corresponded well with the reported diagnostic accuracies by human readers based on the PI-RADS system in the current literature. Conclusion The study revealed comparable diagnostic accuracies for the detection of prostate cancer of a user-independent MAI-based automated analysis tool and PI-RADS-scoring-based human reader analysis of mpMRI. Thus, the analysis tool could serve as a detection support system for less experienced readers. The results of the study also suggest the potential of MAI-based analysis for advanced lesion assessments, such as cancer extent and staging prediction

Comparison of susceptibility weighted imaging and TOF-angiography for the detection of Thrombi in acute stroke.

BACKGROUND AND PURPOSE: Time-of-flight (TOF) angiography detects embolic occlusion of arteries in patients with acute ischemic stroke due to the absence of blood flow in the occluded vessel. In contrast, susceptibility weighted imaging (SWI) directly enables intravascular clot visualization due to hypointense susceptibility vessel signs (SVS) in the occluded vessel. The aim of this study was to compare the diagnostic accuracy of both methods to determine vessel occlusion in patients with acute stroke. METHODS: 94 patients were included who presented with clinical symptoms for acute stroke and displayed a delay on the time-to-peak perfusion map in the territory of the anterior (ACA), middle (M1, M1/M2, M2/M3) or posterior (PCA) cerebral artery. The frequency of SVS on SWI and vessel occlusion or stenosis on TOF-angiography was compared using the McNemar-Test. RESULTS: 87 of 94 patients displayed a clearly definable SVS on SWI. In 72 patients the SVS was associated with occlusion or stenosis on TOF-angiography. Fifteen patients exclusively displayed SVS on SWI (14 M2/M3, 1 M1), whereas no patient revealed exclusively occlusion or stenosis on TOF-angiography. Sensitivity for detection of embolic occlusion within major vessel segments (M1, M1/M2, ACA, and PCA) did not show any significant difference between both techniques (97% for SWI versus 96% for TOF-angiography) while the sensitivity for detection of embolic occlusion within M2/M3 was significantly different (84% for SWI versus 39% for TOF-angiography, p<0.00012). CONCLUSIONS: SWI and TOF-angiography provide similar sensitivity for central thrombi while SWI is superior for the detection of peripheral thrombi in small arterial vessel segments

Quantitative susceptibility mapping differentiates between blood depositions and calcifications in patients with glioblastoma.

OBJECTIVES: The application of susceptibility weighted imaging (SWI) in brain tumor imaging is mainly used to assess tumor-related "susceptibility based signals" (SBS). The origin of SBS in glioblastoma is still unknown, potentially representing calcifications or blood depositions. Reliable differentiation between both entities may be important to evaluate treatment response and to identify glioblastoma with oligodendroglial components that are supposed to present calcifications. Since calcifications and blood deposits are difficult to differentiate using conventional MRI, we investigated whether a new post-processing approach, quantitative susceptibility mapping (QSM), is able to distinguish between both entities reliably. MATERIALS AND METHODS: SWI, FLAIR, and T1-w images were acquired from 46 patients with glioblastoma (14 newly diagnosed, 24 treated with radiochemotherapy, 8 treated with radiochemotherapy and additional anti-angiogenic medication). Susceptibility maps were calculated from SWI data. All glioblastoma were evaluated for the appearance of hypointense or hyperintense correlates of SBS on the susceptibility maps. RESULTS: 43 of 46 glioblastoma presented only hyperintense intratumoral SBS on susceptibility maps, indicating blood deposits. Additional hypointense correlates of tumor-related SBS on susceptibility maps, indicating calcification, were identified in 2 patients being treated with radiochemotherapy and in one patient being treated with additional anti-angiogenic medication. Histopathologic reports revealed an oligodendroglial component in one patient that presented calcifications on susceptibility maps. CONCLUSIONS: QSM provides a quantitative, local MRI contrast, which reliably differentiates between blood deposits and calcifications. Thus, quantitative susceptibility mapping appears promising to identify rare variants of glioblastoma with oligodendroglial components non-invasively and may allow monitoring the role of calcification in the context of different therapy regimes

Examples of MAI profiles.

<p>Confirmed Gleason score 7a (3+4, left) and Gleason score 8 (4+4, right) lesions.</p

Example of a MAI map on a T2W image overlay.

<p>Example of a MAI map on a T2W image overlay.</p

Sensitivity, specificity and Youden index of MAI-based prostate cancer detection at different mean MAI threshold values.

<p>Sensitivity, specificity and Youden index of MAI-based prostate cancer detection at different mean MAI threshold values.</p