Association of Radiomics and Metabolic Tumor Volumes in Radiation Treatment of Glioblastoma Multiforme.

PURPOSE: To build a framework for investigation of the associations between imaging, clinical target volumes (CTVs), and metabolic tumor volumes (MTVs) features for better understanding of the underlying information in the CTVs and dependencies between these volumes. High-throughput extraction of imaging and metabolomic quantitative features from magnetic resonance imaging (MRI) and magnetic resonance spectroscopic imaging of glioblastoma multiforme (GBM) results in tens of variables per patient. In radiation therapy of GBM the relevant metabolic tumor volumes (MTVs) are related to aberrant levels of N-acetyl aspartate (NAA) and choline (Cho). The corresponding clinical target volumes (CTVs) for radiation therapy are based on contrast-enhanced T1-weighted (CE-T1w) and T2-weighted (T2w)/fluid-attenuated inversion recovery MRI. METHODS AND MATERIALS: Necrotic portions, enhancing lesion, and edema were manually contoured on CE-T1w/T2w images for 17 GBM patients. Clinical target volumes and MTVs for NAA (MTVNAA) and Cho (MTVCho) were constructed. Imaging and metabolic features related to size, shape, and signal intensities of the volumes were extracted. Tumors were also scored categorically for 10 semantic imaging traits by a neuroradiologist. All features were investigated for redundancy. Two-way correlations between imaging and CTVs/MTVs features were visualized as heatmaps. Associations between MTVNAA and MTVCho and imaging features were studied using Spearman correlation. RESULTS: Forty-eight imaging features were extracted per patient. Half of the imaging traits were replaced with automatically extracted continuous variables. Twenty features were extracted from CTVs and MTVs. A series of semantic imaging traits were replaced with automatically extracted continuous variables. There were multiple (22) significant correlations of imaging measures with CTVs/MTVNAA, whereas there were only 6 with CTVs/MTVCho. CONCLUSIONS: A framework for investigation of codependencies between MRI and magnetic resonance spectroscopic imaging radiomic features and CTVs/MTVs has been established. The MTV for NAA was found to be closely associated with MRI volumes, whereas very few imaging features were related to MTVCho, indicating that Cho provides additional information to imaging.

The role of adjuvant radiotherapy after gross total resection of atypical meningiomas.

BACKGROUND: Atypical meningiomas (AMs) frequently recur after gross total resection (GTR). OBJECTIVE: We conducted a meta-analysis to evaluate the benefit of adjuvant therapy after GTR of AMs. METHODS: A PubMed/MEDLINE search identified studies detailing AMs treated by GTR alone or GTR and adjuvant radiotherapy (RT) published between 1984 and 2012. Original data from 14 retrospective studies were combined and analyzed. Odds ratio (OR) and χ(2) testing were used when appropriate. Selected datasets were used to generate each variable, where available. RESULTS: A total of 757 patients (male/female ratio 9:10) with AMs were included; 72.52% (n = 549) of AMs were treated by GTR alone, and 27.47% (n = 208) underwent adjuvant RT after GTR to a median dose of 54 Gy. The crude recurrence rate was twice as high without adjuvant RT (33.7% vs. 15%, P = 0.005). The 1-year local control rate was 90% for GTR and 97% for GTR + RT (OR = 3.36, P = 0.11). The median 5-year local control rate was 62% for GTR and 73% for GTR + RT, respectively (OR = 1.71, P = 0.06). The 5-year overall survival for each group was 90% (OR = 0.97, P = 0.95). A total of 85% of recurrences were salvaged, 33% by RT and 67% by surgery. Radiation-related toxicity was <10%, at a median follow-up of 42 months. CONCLUSIONS: Postoperative RT for AMs may decrease risk for relapse of disease and improve local control, although most tumors are salvageable with surgery or radiation. Although the data suggest little or no impact of postoperative RT on survival, further investigation regarding the long-term efficacy and toxicity of radiation is warranted.

Volumetric spectroscopic imaging of glioblastoma multiforme radiation treatment volumes.

PURPOSE: Magnetic resonance (MR) imaging and computed tomography (CT) are used almost exclusively in radiation therapy planning of glioblastoma multiforme (GBM), despite their well-recognized limitations. MR spectroscopic imaging (MRSI) can identify biochemical patterns associated with normal brain and tumor, predominantly by observation of choline (Cho) and N-acetylaspartate (NAA) distributions. In this study, volumetric 3-dimensional MRSI was used to map these compounds over a wide region of the brain and to evaluate metabolite-defined treatment targets (metabolic tumor volumes [MTV]). METHODS AND MATERIALS: Volumetric MRSI with effective voxel size of ∼1.0 mL and standard clinical MR images were obtained from 19 GBM patients. Gross tumor volumes and edema were manually outlined, and clinical target volumes (CTVs) receiving 46 and 60 Gy were defined (CTV46 and CTV60, respectively). MTVCho and MTVNAA were constructed based on volumes with high Cho and low NAA relative to values estimated from normal-appearing tissue. RESULTS: The MRSI coverage of the brain was between 70% and 76%. The MTVNAA were almost entirely contained within the edema, and the correlation between the 2 volumes was significant (r=0.68, P=.001). In contrast, a considerable fraction of MTVCho was outside of the edema (median, 33%) and for some patients it was also outside of the CTV46 and CTV60. These untreated volumes were greater than 10% for 7 patients (37%) in the study, and on average more than one-third (34.3%) of the MTVCho for these patients were outside of CTV60. CONCLUSIONS: This study demonstrates the potential usefulness of whole-brain MRSI for radiation therapy planning of GBM and revealed that areas of metabolically active tumor are not covered by standard RT volumes. The described integration of MTV into the RT system will pave the way to future clinical trials investigating outcomes in patients treated based on metabolic information.