Debra H. Brinkmann

Background: Post-treatment prognosis and monitoring are critical for determining the timing of salvage treatment in glioblastoma patients but has been challenging due to difficulties differentiating progression from treatment effects in conventional images. This exploratory study aimed to establish the correlation of radiomics image features from time series of amino acid tracer ¹⁸F-DOPA PET images, with outcomes, using machine learning and dimension reduction analysis. Methods: ¹⁸F-DOPA PET images were collected for a patient cohort with wild-type IDH and unmethylated MGMT who underwent dose-escalated radiation therapy. Quantitative features were derived from the high uptake region (T/N > 2.0) in pre- and post-radiation therapy follow-up ¹⁸F-DOPA PET images. A customized workflow was utilized for pre-selecting predictive features, followed by manifold learning. Machine learning algorithms were employed to establish associations between imaging features and remaining survival (RS), defined as the time between a follow-up scan and date of death. Results: The ML models exhibited 81–83% ROC_AUC in predicting RS evaluated on an independent test dataset. A RS map is proposed for monitoring tumor alterations through serial ¹⁸F-DOPA PET scans, demonstrating superior sensitivity and better correlation with survival compared to the RANO criteria. Conclusions: Our study demonstrates that ML models utilizing FU ¹⁸F-DOPA PET images have the potential to effectively predict future survival outcomes in patients with glioblastoma treated with dose-escalated radiation therapy. The capability to assess changes in tumor over time through imaging can potentially assist in patient stratification and the selection of salvage treatments, while also aiding in distinguishing treatment effects from genuine tumor progression.

Background/objectives: ¹⁸F-DOPA is an amino acid radiotracer with high uptake in glioblastoma and low uptake in normal brain. Patients underwent pre-radiation and post-radiation ¹⁸F-DOPA PET scans on a prospective clinical trial. This analysis investigates quantitative image features correlated with prognosis and treatment response to identify patients who benefit the most from dose-escalated therapy.Methods: Quantitative image features from ¹⁸F-DOPA PET scans of 58 glioblastoma patients were extracted from the high uptake region (TBR>2.0) in both pre-RT and early post-RT follow-up PET images, which were then refined using Pearson pair correlation. To explore the possibility to identify patients who benefit the most from dose-escalated therapy, pre-irradiation features were identified with univariate Cox regression analysis. Classifications with simple threshold or with Decision Tree models were carried out to categorize patients into distinct survival groups. Additionally, the features with notable changes before and after RT were identified and the temporal patterns of these changes between the survival groups were compared. Multivariates cox analysis was performed to assess the prognostic value of delta features in survival analysis.Results: The pre-irradiation features demonstrated predictive capability in distinguishing survival groups, yielding an accuracy of 0.78 on the reserved test dataset. We also pinpointed eight quantitative features that exhibited a significant difference before and after radiotherapy in patients with MGMT-unmethylated glioblastoma. The change of the features presented different patterns between the survival groups separated by median overall survival and the inclusion of delta features can enhance the accuracy of survival analysis. Conversely, for patients with methylated MGMT, no feature displayed such significant changes between preRT and early postRT.Conclusions: Our study showcased the potential of employing quantitative features derived from ¹⁸F-DOPA images to refine the stratification of patients with unmethylated MGMT for dose escalated therapy. Moreover, the change of these features can serve as valuable tools for monitoring treatment responses following radiotherapy.

Purpose:Outcomes for resistant metastatic castration-resistant prostate cancer (CRPC) are poor. Stereotactic ablative radiotherapy (SABR) induces antitumor immunity in clinical and preclinical studies, but immunologic biomarkers are lacking.Patients and Methods:Eighty-nine patients with oligometastatic CRPC were identified by 11C-Choline-PET (Choline-PET) from August 2016 to December 2019 and treated with SABR. Prespecified coprimary endpoints were 2-year overall survival (OS) and PSA progression. Secondary endpoints included 2-year SABR-treated local failure and 6-month adverse events. Correlative studies included peripheral blood T-cell subpopulations before and after SABR.Results:128 lesions in 89 patients were included in this analysis. Median OS was 29.3 months, and 1- and 2-year OS were 96% and 80%, respectively. PSA PFS was 40% at 1 year and 21% at 2 years. Local PFS was 84.4% and 75.3% at 1 and 2 years, respectively, and no grade ≥3 AEs were observed. Baseline high levels of tumor-reactive T cells (TTR; CD8+CD11ahigh) predicted superior local, PSA, and distant PFS. Baseline high levels of effector memory T cells (TEM; CCR7−CD45RA−) were associated with improved PSA PFS. An increase in TTR at day 14 from baseline was associated with superior OS.Conclusions:This is the first comprehensive effector T-cell immunophenotype analysis in a phase II trial before and after SABR in CRPC. Results are favorable and support the incorporation of immune-based markers in the design of future randomized trials in patients with oligometastatic CRPC treated with SABR.

Supplementary Figure 3. Changes in CD8+CD11ahigh populations from baseline to days 1, 7, and 14.

Supplementary Table 1. PSA progression by number of sites treated. 1Kaplan-Meier method; 2Cox model; 3Logrank test; 4Wald Chi-Square test.

Supplementary Table 3. Baseline TTR and changes after SBRT predict outcomes in oligometastatic CRPC. Median event-free survival survival (in months) and hazard ratio for each outcome and group is given, stratified by baseline TTR levels (left) or change in TTR levels from baseline to day 14 post-SBRT. ns not significant; N/A not applicable

Purpose:Outcomes for resistant metastatic castration-resistant prostate cancer (CRPC) are poor. Stereotactic ablative radiotherapy (SABR) induces antitumor immunity in clinical and preclinical studies, but immunologic biomarkers are lacking.Patients and Methods:Eighty-nine patients with oligometastatic CRPC were identified by 11C-Choline-PET (Choline-PET) from August 2016 to December 2019 and treated with SABR. Prespecified coprimary endpoints were 2-year overall survival (OS) and PSA progression. Secondary endpoints included 2-year SABR-treated local failure and 6-month adverse events. Correlative studies included peripheral blood T-cell subpopulations before and after SABR.Results:128 lesions in 89 patients were included in this analysis. Median OS was 29.3 months, and 1- and 2-year OS were 96% and 80%, respectively. PSA PFS was 40% at 1 year and 21% at 2 years. Local PFS was 84.4% and 75.3% at 1 and 2 years, respectively, and no grade ≥3 AEs were observed. Baseline high levels of tumor-reactive T cells (TTR; CD8+CD11ahigh) predicted superior local, PSA, and distant PFS. Baseline high levels of effector memory T cells (TEM; CCR7−CD45RA−) were associated with improved PSA PFS. An increase in TTR at day 14 from baseline was associated with superior OS.Conclusions:This is the first comprehensive effector T-cell immunophenotype analysis in a phase II trial before and after SABR in CRPC. Results are favorable and support the incorporation of immune-based markers in the design of future randomized trials in patients with oligometastatic CRPC treated with SABR.

Supplementary Figure 3. Changes in CD8+CD11ahigh populations from baseline to days 1, 7, and 14.

Supplementary Table 2. Distant radiographic progression by number of sites treated. 1Kaplan-Meier method; 2Cox model; 3Logrank test; 4Wald Chi-Square test.