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BACKGROUND: To report the final results of a prospective, one-armed, single-center phase I/II trial (NCT01566123). METHODS: Between 2007 and 2017, 37 patients with primary or recurrent (N = 6) retroperitoneal sarcomas were enrolled. Treatment included preoperative IMRT of 45-50 Gy with a simultaneous integrated boost of 50-56 Gy, surgery and IORT. The primary endpoint was local control (LC) at 5 years. The most common histology was dedifferentiated liposarcoma (51%), followed by leiomyosarcoma (24%) and well-differentiated liposarcoma (14%). The majority of lesions were high-grade (FNCLCC G1: 30%, G2: 38%, G3: 27%, two missing). Five patients were excluded from LC analysis per protocol. RESULTS: The minimum follow-up of the survivors was 62 months (median: 109; maximum 162). IORT was performed for 27 patients. Thirty-five patients underwent gross total resection; the pathological resection margin was mostly R+ (80%) and, less often, R0 (20%). We observed 10 local recurrences. The 5-year LC of the whole cohort was 59.6%. Eleven patients received a dose > 50 Gy plus IORT boost; LC was 64.8%; the difference, however, was not significant (p = 0.588). Of 37 patients, 15 were alive and 22 deceased at the time of final analysis. The 5-year OS was 59.5% (68.8% per protocol). CONCLUSIONS: The primary endpoint of a 5-year LC of 70% was not met. This might be explained by the inclusion of recurrent disease and the high rate of G3 lesions and leiomyosarcoma, which have been shown to profit less from radiotherapy. Stratification by grading and histology should be considered for future studies.
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BACKGROUND: MR image classification in datasets collected from multiple sources is complicated by inconsistent and missing DICOM metadata. Therefore, we aimed to establish a method for the efficient automatic classification of MR brain sequences. METHODS: Deep convolutional neural networks (DCNN) were trained as one-vs-all classifiers to differentiate between six classes: T1 weighted (w), contrast-enhanced T1w, T2w, T2w-FLAIR, ADC, and SWI. Each classifier yields a probability, allowing threshold-based and relative probability assignment while excluding images with low probability (label: unknown, open-set recognition problem). Data from three high-grade glioma (HGG) cohorts was assessed; C1 (320 patients, 20,101 MRI images) was used for training, while C2 (197, 11,333) and C3 (256, 3522) were for testing. Two raters manually checked images through an interactive labeling tool. Finally, MR-Class' added value was evaluated via radiomics model performance for progression-free survival (PFS) prediction in C2, utilizing the concordance index (C-I). RESULTS: Approximately 10% of annotation errors were observed in each cohort between the DICOM series descriptions and the derived labels. MR-Class accuracy was 96.7% [95% Cl: 95.8, 97.3] for C2 and 94.4% [93.6, 96.1] for C3. A total of 620 images were misclassified; manual assessment of those frequently showed motion artifacts or alterations of anatomy by large tumors. Implementation of MR-Class increased the PFS model C-I by 14.6% on average, compared to a model trained without MR-Class. CONCLUSIONS: We provide a DCNN-based method for the sequence classification of brain MR images and demonstrate its usability in two independent HGG datasets.
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PURPOSE: This study investigates the impact of different intensity normalization (IN) methods on the overall survival (OS) radiomics models' performance of MR sequences in primary (pHGG) and recurrent high-grade glioma (rHGG). METHODS: MR scans acquired before radiotherapy were retrieved from two independent cohorts (rHGG C1: 197, pHGG C2: 141) from multiple scanners (15, 14). The sequences are T1 weighted (w), contrast-enhanced T1w (T1wce), T2w, and T2w-FLAIR. Sequence-specific significant features (SF) associated with OS, extracted from the tumour volume, were derived after applying 15 different IN methods. Survival analyses were conducted using Cox proportional hazard (CPH) and Poisson regression (POI) models. A ranking score was assigned based on the 10-fold cross-validated (CV) concordance index (C-I), mean square error (MSE), and the Akaike information criterion (AICs), to evaluate the methods' performance. RESULTS: Scatter plots of the 10-CV C-I and MSE against the AIC showed an impact on the survival predictions between the IN methods and MR sequences (C1/C2 C-I range: 0.62-0.71/0.61-0.72, MSE range: 0.20-0.42/0.13-0.22). White stripe showed stable results for T1wce (C1/C2 C-I: 0.71/0.65, MSE: 0.21/0.14). Combat (0.68/0.62, 0.22/0.15) and histogram matching (HM, 0.67/0.64, 0.22/0.15) showed consistent prediction results for T2w models. They were also the top-performing methods for T1w in C2 (Combat: 0.67, 0.13; HM: 0.67, 0.13); however, only HM achieved high predictions in C1 (0.66, 0.22). After eliminating IN impacted SF using Spearman's rank-order correlation coefficient, a mean decrease in the C-I and MSE of 0.05 and 0.03 was observed in all four sequences. CONCLUSION: The IN method impacted the predictive power of survival models; thus, performance is sequence-dependent.
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Background: Selective uptake of (18)F-fluoro-ethyl-tyrosine (18F-FET) is used in high-grade glioma (HGG) to assess tumor metabolic activity via positron emission tomography (PET). We aim to investigate its value for target volume definition, as a prognosticator, and associations with whole-blood transcriptome liquid biopsy (WBT lbx) for which we recently reported feasibility to mirror tumor characteristics and response to particle irradiation in recurrent HGG (rHGG). Methods: 18F-FET-PET data from n = 43 patients with primary glioblastoma (pGBM) and n = 33 patients with rHGG were assessed. pGBM patients were irradiated with photons and sequential proton/carbon boost, and rHGG patients were treated with carbon re-irradiation (CIR). WBT (Illumina HumanHT-12 Expression BeadChips) lbx was available for n = 9 patients from the rHGG cohort. PET isocontours (40%-70% SUVmax, 10% steps) and MRI-based treatment volumes (MRIvol) were compared using the conformity index (CI) (pGBM, n = 16; rHGG, n = 27). Associations with WBT lbx data were tested on gene expression level and inferred pathways activity scores (PROGENy) and from transcriptome estimated cell fractions (CIBERSORT, xCell). Results: In pGBM, median SUVmax was higher in PET acquired pre-radiotherapy (4.1, range (R) 1.5-7.8; n = 20) vs. during radiotherapy (3.3, R 1.5-5.7, n = 23; p = 0.03) and in non-resected (4.7, R 2.9-7.9; n = 11) vs. resected tumors (3.3, R 1.5-7.8, n = 32; p = 0.01). In rHGG, a trend toward higher SUVmax values in grade IV tumors was observed (p = 0.13). Median MRIvol was 32.34 (R 8.75-108.77) cm3 in pGBM (n = 16) and 20.77 (R 0.63-128.44) cm3 in rHGG patients (n = 27). The highest median CI was observed for 40% (pGBM, 0.31) and 50% (rHGG, 0.43, all tumors) isodose, with 70% (40%) isodose in grade III (IV) rHGG tumors (median CI, 0.38 and 0.49). High SUVmax was linked to shorter survival in pGBM (>3.3, p = 0.001, OR 6.0 [2.1-17.4]) and rHGG (>2.8, p = 0.02, OR 4.1 [1.2-13.9]). SUVmax showed associations with inferred monocyte fractions, hypoxia, and TGFbeta pathway activity and links to immune checkpoint gene expression from WBT lbx. Conclusion: The benefits of 18F-FET-PET imaging on gross tumor volume (GTV) definition for particle radiotherapy warrant further evaluation. SUVmax might assist in prognostic stratification of HGG patients for particle radiotherapy, highlights heterogeneity in rHGG, and is positively associated with unfavorable signatures in peripheral whole-blood transcriptomes.
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Background: To report survival of craniofacial osteosarcoma patients treated by particle radiotherapy. Methods: Between January 2010 and December 2021, 51 patients with primary (N = 35) or recurrent (N = 16) inoperable or incompletely resected craniofacial osteosarcoma were treated. In most cases, intracranial infiltration (59%) and macroscopic tumor on MRI/CT (75%) were present. Thirteen had a secondary osteosarcoma (25%). Treatment concepts included combined ion beam radiotherapy (CIBRT, N = 18), protons only (N = 3), carbon ions only (N = 12), IMRT with a carbon ion boost (N = 5), and carbon ion re-irradiation (N = 13). Eighty percent (N = 41) received additionally chemotherapy, most frequently EURAMOS-1 (47%) or EURO-B.O.S.S. (18%). Results: The median age was 38, and all patients finished treatment predominantly as outpatients (N = 44). Information on overall survival was available for N = 49 patients. The median follow-up of the survivors was 55 months. For the whole cohort 1-, 2-, 3-, and 5-year overall survival (OS) was 82.8%, 60.4%, 55.2%, and 51.7%, respectively. Those treated by CIBRT (N = 17) demonstrated a superior OS with 92.9% after 1 and 2 years and 83.6% after 3 and 5 years. The median clinical target volume (CTV) was 192.7 and 95.2 cc for the primary and boost plan, respectively. CIBRT, primary diagnosis, age ≤40a, and no macroscopic residual tumor were associated with improved survival in univariate analysis (p = 0.006, p = 0.004, p = 0.002, p = 0.026, respectively), while any foregoing resection compared to biopsy was not identified as a prognostic factor. CIBRT and no macroscopic residual tumor were confirmed as independent predictors of OS on multivariate analysis (HR = 0.107, 95% CI = [0.014, 0.797], p = 0.029 and HR = 0.130, 95% CI = [0.023, 0.724], p = 0.020, respectively). No acute toxicity > grade III was observed. Conclusion: CIBRT shows promising results for patients with inoperable or incompletely resected craniofacial osteosarcoma.
