IMPORTANCEPer the World Health Organization 2016 integrative classification, newly diagnosed glioblastomas are separated into isocitrate dehydrogenase gene 1 or 2 (IDH)-wild-type and IDH-mutant subtypes, with median patient survival of 1.2 and 3.6 years, respectively. Although maximal resection of contrast-enhanced (CE) tumor is associated with longer survival, the prognostic importance of maximal resection within molecular subgroups and the potential importance of resection of non-contrast-enhanced (NCE) disease is poorly understood.OBJECTIVE To assess the association of resection of CE and NCE tumors in conjunction with molecular and clinical information to develop a new road map for cytoreductive surgery.

Background Magnetic resonance fingerprinting (MRF) allows rapid simultaneous quantification of T1 and T2 relaxation times. This study assesses the utility of MRF in differentiating between common types of adult intra-axial brain tumors. Methods MRF acquisition was performed in 31 patients with untreated intra-axial brain tumors: 17 glioblastomas, 6 WHO grade II lower-grade gliomas and 8 metastases. T1, T2 of the solid tumor (ST), immediate peritumoral white matter (PW), and contralateral white matter (CW) were summarized within each region of interest. Statistical comparisons on mean, standard deviation, skewness and kurtosis were performed using univariate Wilcoxon rank sum test across various tumor types. Bonferroni correction was used to correct for multiple comparisons testing. Multivariable logistic regression analysis was performed for discrimination between glioblastomas and metastases and area under the receiver operator curve (AUC) was calculated. Results Mean T2 values could differentiate solid tumor regions of lower-grade gliomas from metastases (mean±sd: 172±53ms and 105±27ms respectively, p =0.004, significant after Bonferroni correction). Mean T1 of PW surrounding lower-grade gliomas differed from PW around glioblastomas (mean±sd: 1066±218ms and 1578±331ms respectively, p=0.004, significant after Bonferroni correction). Logistic regression analysis revealed that mean T2 of ST offered best separation between glioblastomas and metastases with AUC of 0.86 (95% CI 0.69–1.00, p<0.0001). Conclusion MRF allows rapid simultaneous T1, T2 measurement in brain tumors and surrounding tissues. MRF based relaxometry can identify quantitative differences between solid-tumor regions of lower grade gliomas and metastases and between peritumoral regions of glioblastomas and lower grade gliomas.

Purpose To develop and evaluate an examination consisting of magnetic resonance (MR) fingerprinting-based T1, T2, and standard apparent diffusion coefficient (ADC) mapping for multiparametric characterization of prostate disease. Materials and Methods This institutional review board-approved, HIPAA-compliant retrospective study of prospectively collected data included 140 patients suspected of having prostate cancer. T1 and T2 mapping was performed with fast imaging with steady-state precession-based MR fingerprinting with ADC mapping. Regions of interest were drawn by two independent readers in peripheral zone lesions and normal-appearing peripheral zone (NPZ) tissue identified on clinical images. T1, T2, and ADC were recorded for each region. Histopathologic correlation was based on systematic transrectal biopsy or cognitively targeted biopsy results, if available. Generalized estimating equations logistic regression was used to assess T1, T2, and ADC in the differentiation of (a) cancer versus NPZ, (b) cancer versus prostatitis, (c) prostatitis versus NPZ, and (d) high- or intermediate-grade tumors versus low-grade tumors. Analysis was performed for all lesions and repeated in a targeted biopsy subset. Discriminating ability was evaluated by using the area under the receiver operating characteristic curve (AUC). Results In this study, 109 lesions were analyzed, including 39 with cognitively targeted sampling. T1, T2, and ADC from cancer (mean, 1628 msec ± 344, 73 msec ± 27, and 0.773 × 10 mm/sec ± 0.331, respectively) were significantly lower than those from NPZ (mean, 2247 msec ± 450, 169 msec ± 61, and 1.711 × 10 mm/sec ± 0.269) (P < .0001 for each) and together produced the best separation between these groups (AUC = 0.99). ADC and T2 together produced the highest AUC of 0.83 for separating high- or intermediate-grade tumors from low-grade cancers. T1, T2, and ADC in prostatitis (mean, 1707 msec ± 377, 79 msec ± 37, and 0.911 × 10 mm/sec ± 0.239) were significantly lower than those in NPZ (P < .0005 for each). Interreader agreement was excellent, with an intraclass correlation coefficient greater than 0.75 for both T1 and T2 measurements. Conclusion This study describes the development of a rapid MR fingerprinting- and diffusion-based examination for quantitative characterization of prostatic tissue. RSNA, 2017 Online supplemental material is available for this article.