Open Access Policy Deposits

Proof-of-concept study of artificial intelligence-assisted review of CBCT image guidance.

(2023)

PURPOSE: Automation and computer assistance can support quality assurance tasks in radiotherapy. Retrospective image review requires significant human resources, and automation of image review remains a noteworthy missing element in previous work. Here, we present initial findings from a proof-of-concept clinical implementation of an AI-assisted review of CBCT registrations used for patient setup. METHODS: An automated pipeline was developed and executed nightly, utilizing python scripts to interact with the clinical database through DICOM networking protocol and automate data retrieval and analysis. A previously developed artificial intelligence (AI) algorithm scored CBCT setup registrations based on misalignment likelihood, using a scale from 0 (most unlikely) through 1 (most likely). Over a 45-day period, 1357 pre-treatment CBCT registrations from 197 patients were retrieved and analyzed by the pipeline. Daily summary reports of the previous days registrations were produced. Initial action levels targeted 10% of cases to highlight for in-depth physics review. A validation subset of 100 cases was scored by three independent observers to characterize AI-model performance. RESULTS: Following an ROC analysis, a global threshold for model predictions of 0.87 was determined, with a sensitivity of 100% and specificity of 82%. Inspecting the observer scores for the stratified validation dataset showed a statistically significant correlation between observer scores and model predictions. CONCLUSION: In this work, we describe the implementation of an automated AI-analysis pipeline for daily quantitative analysis of CBCT-guided patient setup registrations. The AI-model was validated against independent expert observers, and appropriate action levels were determined to minimize false positives without sacrificing sensitivity. Case studies demonstrate the potential benefits of such a pipeline to bolster quality and safety programs in radiotherapy. To the authors knowledge, there are no previous works performing AI-assisted assessment of pre-treatment CBCT-based patient alignment.

Immune checkpoint blockade induces distinct alterations in the microenvironments of primary and metastatic brain tumors.

(2023)

In comparison with responses in recurrent glioblastoma (rGBM), the intracranial response of brain metastases (BrM) to immune checkpoint blockade (ICB) is less well studied. Here, we present an integrated single-cell RNA-Seq (scRNA-Seq) study of 19 ICB-naive and 9 ICB-treated BrM samples from our own and published data sets. We compared them with our previously published scRNA-Seq data from rGBM and found that ICB led to more prominent T cell infiltration into BrM than rGBM. These BrM-infiltrating T cells exhibited a tumor-specific phenotype and displayed greater activated/exhausted features. We also used multiplex immunofluorescence and spatial transcriptomics to reveal that ICB reduced a distinct CD206+ macrophage population in the perivascular space, which may modulate T cell entry into BrM. Furthermore, we identified a subset of progenitor exhausted T cells that correlated with longer overall survival in BrM patients. Our study provides a comprehensive immune cellular landscape of ICBs effect on metastatic brain tumors and offers insights into potential strategies for improving ICB efficacy for brain tumor patients.

Cover page of Predicting Overall Survival for Patients with Malignant Mesothelioma Following Radiotherapy via Interpretable Machine Learning.

Predicting Overall Survival for Patients with Malignant Mesothelioma Following Radiotherapy via Interpretable Machine Learning.

(2023)

PURPOSE/OBJECTIVES: Malignant pleural mesothelioma (MPM) is a rare but aggressive cancer arising from the cells of the thoracic pleura with a poor prognosis. We aimed to develop a model, via interpretable machine learning (ML) methods, predicting overall survival for MPM following radiotherapy based on dosimetric metrics as well as patient characteristics. MATERIALS/METHODS: Sixty MPM (37 right, 23 left) patients treated on a Tomotherapy unit between 2013 and 2018 were retrospectively analyzed. All patients received 45 Gy (25 fractions). The multivariable Cox regression (Cox PH) model and Survival Support Vector Machine (sSVM) were applied to build predictive models of overall survival (OS) based on clinical, dosimetric, and combined variables. RESULTS: Significant differences in dosimetric endpoints for critical structures, i.e., the lung, heart, liver, kidney, and stomach, were observed according to target laterality. The OS was found to be insignificantly different (p = 0.18) between MPM patients who tested left- and right-sided, with 1-year OS of 77.3% and 75.0%, respectively. With Cox PH regression, considering dosimetric variables for right-sided patients alone, an increase in PTV_Min, Total_Lung_PTV_Mean, Contra_Lung_Volume, Contra_Lung_V20, Esophagus_Mean, and Heart_Volume had a greater hazard to all-cause death, while an increase in Total_Lung_PTV_V20, Contra_Lung_V5, and Esophagus_Max had a lower hazard to all-cause death. Considering clinical variables alone, males and increases in N stage had greater hazard to all-cause death; considering both clinical and dosimetric variables, increases in N stage, PTV_Mean, PTV_Min, and esophagus_Mean had greater hazard to all-cause death, while increases in T stage and Heart_V30 had lower hazard to all-cause-death. In terms of C-index, the Cox PH model and sSVM performed similarly and fairly well when considering clinical and dosimetric variables independently or jointly. CONCLUSIONS: Clinical and dosimetric variables may predict the overall survival of mesothelioma patients, which could guide personalized treatment planning towards a better treatment response. The identified predictors and their impact on survival offered additional value for translational application in clinical practice.

Cover page of PKM2 rewires glucose metabolism during radiation therapy to promote an antioxidant response and glioblastoma radioresistance.

PKM2 rewires glucose metabolism during radiation therapy to promote an antioxidant response and glioblastoma radioresistance.

(2023)

Background

Resistance to existing therapies is a significant challenge in improving outcomes for glioblastoma (GBM) patients. Metabolic plasticity has emerged as an important contributor to therapy resistance, including radiation therapy (RT). Here, we investigated how GBM cells reprogram their glucose metabolism in response to RT to promote radiation resistance.

Methods

Effects of radiation on glucose metabolism of human GBM specimens were examined in vitro and in vivo with the use of metabolic and enzymatic assays, targeted metabolomics, and FDG-PET. Radiosensitization potential of interfering with PKM2 activity was tested via gliomasphere formation assays and in vivo human GBM models.

Results

Here, we show that RT induces increased glucose utilization by GBM cells, and this is accompanied with translocation of GLUT3 transporters to the cell membrane. Irradiated GBM cells route glucose carbons through the pentose phosphate pathway (PPP) to harness the antioxidant power of the PPP and support survival after radiation. This response is regulated in part by the M2 isoform of pyruvate kinase (PKM2). Activators of PKM2 can antagonize the radiation-induced rewiring of glucose metabolism and radiosensitize GBM cells in vitro and in vivo.

Conclusions

These findings open the possibility that interventions designed to target cancer-specific regulators of metabolic plasticity, such as PKM2, rather than specific metabolic pathways, have the potential to improve the radiotherapeutic outcomes in GBM patients.

Multi-nuclear sodium, diffusion, and perfusion MRI in human gliomas.

(2023)

Purpose

There is limited knowledge about the associations between sodium and proton MRI measurements in brain tumors. The purpose of this study was to quantify intra- and intertumoral correlations between sodium, diffusion, and perfusion MRI in human gliomas.

Methods

Twenty glioma patients were prospectively studied on a 3T MRI system with multinuclear capabilities. Three mutually exclusive tumor volumes of interest (VOIs) were segmented: contrast-enhancing tumor (CET), T2/FLAIR hyperintense non-enhancing tumor (NET), and necrosis. Median and voxel-wise associations between apparent diffusion coefficient (ADC), normalized relative cerebral blood volume (nrCBV), and normalized sodium measurements were quantified for each VOI.

Results

Both relative sodium concentration and ADC were significantly higher in areas of necrosis compared to NET (P = 0.003 and P = 0.008, respectively) and CET (P = 0.02 and P = 0.02). Sodium concentration was higher in CET compared to NET (P = 0.04). Sodium and ADC were higher in treated compared to treatment-naïve gliomas within NET (P = 0.006 and P = 0.01, respectively), and ADC was elevated in CET (P = 0.03). Median ADC and sodium concentration were positively correlated across patients in NET (r = 0.77, P < 0.0001) and CET (r = 0.84, P < 0.0001), but not in areas of necrosis (r = 0.45, P = 0.12). Median nrCBV and sodium concentration were negatively correlated across patients in areas of NET (r=-0.63, P = 0.003). Similar associations were observed when examining voxel-wise correlations within VOIs.

Conclusion

Sodium MRI is positively correlated with proton diffusion MRI measurements in gliomas, likely reflecting extracellular water. Unique areas of multinuclear MRI contrast may be useful in future studies to understand the chemistry of the tumor microenvironment.

Actionable Genomic Alterations in Prostate Cancer Among Black and White United States Veterans.

(2023)

Black Veterans have higher a incidence of localized and metastatic prostate cancer compared to White Veterans yet are underrepresented in reports of frequencies of somatic and germline alterations. This retrospective analysis of somatic and putative germline alterations was conducted in a large cohort of Veterans with prostate cancer (N = 835 Black, 1613 White) who underwent next generation sequencing through the VA Precision Oncology Program, which facilitates molecular testing for Veterans with metastatic cancer. No differences were observed in gene alterations for FDA approved targetable therapies (13.5% in Black Veterans vs. 15.5% in White Veterans, P = .21), nor in any potentially actionable alterations (25.5% vs. 28.7%, P =.1). Black Veterans had higher rates of BRAF (5.5% vs. 2.6%, P < .001) alterations, White Veterans TMPRSS2 fusions (27.2% vs. 11.7%, P < .0001). Putative germline alteration rates were higher in White Veterans (12.0% vs. 6.1%, P < .0001). Racial disparities in outcome are unlikely attributable to acquired somatic alterations in actionable pathways.

Decoding and geometry of ten finger movements in human posterior parietal cortex and motor cortex

(2023)

Objective. Enable neural control of individual prosthetic fingers for participants with upper-limb paralysis.Approach. Two tetraplegic participants were each implanted with a 96-channel array in the left posterior parietal cortex (PPC). One of the participants was additionally implanted with a 96-channel array near the hand knob of the left motor cortex (MC). Across tens of sessions, we recorded neural activity while the participants attempted to move individual fingers of the right hand. Offline, we classified attempted finger movements from neural firing rates using linear discriminant analysis with cross-validation. The participants then used the neural classifier online to control individual fingers of a brain-machine interface (BMI). Finally, we characterized the neural representational geometry during individual finger movements of both hands.Main Results. The two participants achieved 86% and 92% online accuracy during BMI control of the contralateral fingers (chance = 17%). Offline, a linear decoder achieved ten-finger decoding accuracies of 70% and 66% using respective PPC recordings and 75% using MC recordings (chance = 10%). In MC and in one PPC array, a factorized code linked corresponding finger movements of the contralateral and ipsilateral hands.Significance. This is the first study to decode both contralateral and ipsilateral finger movements from PPC. Online BMI control of contralateral fingers exceeded that of previous finger BMIs. PPC and MC signals can be used to control individual prosthetic fingers, which may contribute to a hand restoration strategy for people with tetraplegia.

A pilot study of closed-loop neuromodulation for treatment-resistant post-traumatic stress disorder.

(2023)

The neurophysiological mechanisms in the human amygdala that underlie post-traumatic stress disorder (PTSD) remain poorly understood. In a first-of-its-kind pilot study, we recorded intracranial electroencephalographic data longitudinally (over one year) in two male individuals with amygdala electrodes implanted for the management of treatment-resistant PTSD (TR-PTSD) under clinical trial NCT04152993. To determine electrophysiological signatures related to emotionally aversive and clinically relevant states (trial primary endpoint), we characterized neural activity during unpleasant portions of three separate paradigms (negative emotional image viewing, listening to recordings of participant-specific trauma-related memories, and at-home-periods of symptom exacerbation). We found selective increases in amygdala theta (5-9 Hz) bandpower across all three negative experiences. Subsequent use of elevations in low-frequency amygdala bandpower as a trigger for closed-loop neuromodulation led to significant reductions in TR-PTSD symptoms (trial secondary endpoint) following one year of treatment as well as reductions in aversive-related amygdala theta activity. Altogether, our findings provide early evidence that elevated amygdala theta activity across a range of negative-related behavioral states may be a promising target for future closed-loop neuromodulation therapies in PTSD.

Identifying predictors of on-table adaptation for pancreas stereotactic body radiotherapy (SBRT).

(2023)

Purpose

To identify any clinical or dosimetric parameters that predict which individuals may benefit from on-table adaptation during pancreas stereotactic body radiotherapy (SBRT) with MRI-guided radiotherapy.

Methods and materials

This was a retrospective study of patients undergoing MRI-guided SBRT from 2016 to 2022. Pre-treatment clinical variables and dosimetric parameters on the patient's simulation scan were recorded for each SBRT course, and their ability to predict for on-table adaptation was analyzed using ordinal logistic regression. The outcome measure was number of fractions adapted.

Results

Sixty-three SBRT courses consisting of 315 fractions were analyzed. Median prescription dose was 40 Gy in five fractions (range, 33-50 Gy); 52% and 48% of courses were prescribed ≤40 Gy and >40 Gy, respectively. The median minimum dose delivered to 95% (D95) of the gross tumor volume (GTV) and planning target volume (PTV) was 40.1 Gy and 37.0 Gy, respectively. Median number of fractions adapted per course was three, with 58% (183 out of 315) total fractions adapted. On univariable analysis, the prescription dose (>40 Gy vs ≤40 Gy), GTV volume, stomach V20 and V25, duodenum V20 and dose maximum, large bowel V33 and V35, GTV dose minimum, PTV dose minimum, and gradient index were significant determinants for adaptation (all p < 0.05). On multivariable analysis, only the prescription dose was significant (adjusted odds ratio 19.7, p = 0.005), but did not remain significant after multiple test correction (p = 0.08).

Conclusions

The likelihood of needing on-table adaptation could not be reliably predicted a priori using pre-treatment clinical characteristics, dosimetry to nearby organs at risk, or other dosimetric parameters based on the patient's anatomy at the time of simulation, suggesting the critical importance of day-to-day variations in anatomy and increasing access to adaptive technology for pancreas SBRT. A higher (ablative) prescription dose was associated with increased use of adaptation.

Significant changes in macrophage and CD8 T cell densities in primary prostate tumors 2 weeks after SBRT.

(2023)

Background

Radiotherapy impacts the local immune response to cancers. Prostate Stereotactic Body Radiotherapy (SBRT) is a highly focused method to deliver radiotherapy often used to treat prostate cancer. This is the first direct comparison of immune cells within prostate cancers before and after SBRT in patients.

Methods

Prostate cancers before and 2 weeks after SBRT are interrogated by multiplex immune fluorescence targeting various T cells and macrophages markers and analyzed by cell and pixel density, as part of a clinical trial of SBRT neoadjuvant to radical prostatectomy.

Results

Two weeks after SBRT, CD68, and CD163 macrophages are significantly increased while CD8 T cells are decreased. SBRT markedly alters the immune environment within prostate cancers.

UCLA Department of Radiation Oncology