A feasibility trial of skin surface motion-gated stereotactic body radiotherapy for treatment of upper abdominal or lower thoracic targets using a novel O-ring gantry

BACKGROUND AND PURPOSE: A novel O-ring gantry can deliver stereotactic body radiation therapy (SBRT) with artificial intelligence-facilitated, CT-guided online plan adaptation. It gates mobile targets by optically monitoring skin surface motion. However, this gating solution has not been clinically validated. We conducted a trial to evaluate the feasibility of optical skin surface-guided gating for patients with mobile upper abdominal or lower thoracic malignancies treated with SBRT on this platform (NCT05030454). MATERIALS AND METHODS: Ten patients who were prescribed SBRT to a thoracic or abdominal target and were capable of breath-hold for at least 17 s enrolled. They received SBRT in five fractions with breath-hold technique and optical skin surface motion monitored-gating with a ± 2 mm tolerance. Online plan adaptation was left to the discretion of the daily treating physician. The primary endpoint was defined as successful completion of \u3e 75 % of attempted fractions. Exploratory endpoints included local control and acute grade ≥ 3 toxicity rates after three months. For adapted fractions the contouring, planning, quality assurance, and treatment delivery times were recorded. RESULTS: Forty-seven of 51 SBRT fractions (92 %) were successfully gated at breath-hold by optical skin surface motion monitoring. The tumor centroid position during breath-hold varied by a mean of approximately 2 mm. Sixty-three percent of fractions were adapted online with a median total treatment time of 78.5 min. After three months no local recurrences or acute grade ≥ 3 toxicities were observed. CONCLUSIONS: SBRT treatment to mobile targets with surface-monitored gating on a novel O-ring gantry was prospectively validated

A pilot study of same-day MRI-only simulation and treatment with MR-guided adaptive palliative radiotherapy (MAP-RT)

We conducted a prospective pilot study evaluating the feasibility of same day MRI-only simulation and treatment with MRI-guided adaptive palliative radiotherapy (MAP-RT) for urgent palliative indications (NCT#03824366). All (16/16) patients were able to complete 99% of their first on-table attempted fractions, and no grades 3-5 toxicities occurred

Prospective in silico evaluation of cone-beam computed tomography-guided stereotactic adaptive radiation therapy (CT-STAR) for the ablative treatment of ultracentral thoracic disease

PURPOSE: We conducted a prospective, in silico study to evaluate the feasibility of cone-beam computed tomography (CBCT)-guided stereotactic adaptive radiation therapy (CT-STAR) for the treatment of ultracentral thoracic cancers (NCT04008537). We hypothesized that CT-STAR would reduce dose to organs at risk (OARs) compared with nonadaptive stereotactic body radiation therapy (SBRT) while maintaining adequate tumor coverage. METHODS AND MATERIALS: Patients who were already receiving radiation therapy for ultracentral thoracic malignancies underwent 5 additional daily CBCTs on the ETHOS system as part of a prospective imaging study. These were used to simulate CT-STAR, in silico RESULTS: Seven patients were accrued, 6 with intraparenchymal tumors and 1 with a subcarinal lymph node. CT-STAR was feasible in 34 of 35 simulated fractions. In total, 32 dose constraint violations occurred when the P CONCLUSIONS: CT-STAR widened the dosimetric therapeutic index of ultracentral thorax SBRT compared with nonadaptive SBRT. A phase 1 protocol is underway to evaluate the safety of this paradigm for patients with ultracentral early-stage NSCLC

Urine cell-free DNA multi-omics to detect MRD and predict survival in bladder cancer patients

Circulating tumor DNA (ctDNA) sensitivity remains subpar for molecular residual disease (MRD) detection in bladder cancer patients. To remedy this problem, we focused on the biofluid most proximal to the disease, urine, and analyzed urine tumor DNA in 74 localized bladder cancer patients. We integrated ultra-low-pass whole genome sequencing (ULP-WGS) with urine cancer personalized profiling by deep sequencing (uCAPP-Seq) to achieve sensitive MRD detection and predict overall survival. Variant allele frequency, inferred tumor mutational burden, and copy number-derived tumor fraction levels in urine cell-free DNA (cfDNA) significantly predicted pathologic complete response status, far better than plasma ctDNA was able to. A random forest model incorporating these urine cfDNA-derived factors with leave-one-out cross-validation was 87% sensitive for predicting residual disease in reference to gold-standard surgical pathology. Both progression-free survival (HR = 3.00, p = 0.01) and overall survival (HR = 4.81, p = 0.009) were dramatically worse by Kaplan-Meier analysis for patients predicted by the model to have MRD, which was corroborated by Cox regression analysis. Additional survival analyses performed on muscle-invasive, neoadjuvant chemotherapy, and held-out validation subgroups corroborated these findings. In summary, we profiled urine samples from 74 patients with localized bladder cancer and used urine cfDNA multi-omics to detect MRD sensitively and predict survival accurately

Urine cell-free DNA multi-omics to detect MRD and predict survival in bladder cancer patients

Abstract Circulating tumor DNA (ctDNA) sensitivity remains subpar for molecular residual disease (MRD) detection in bladder cancer patients. To remedy this problem, we focused on the biofluid most proximal to the disease, urine, and analyzed urine tumor DNA in 74 localized bladder cancer patients. We integrated ultra-low-pass whole genome sequencing (ULP-WGS) with urine cancer personalized profiling by deep sequencing (uCAPP-Seq) to achieve sensitive MRD detection and predict overall survival. Variant allele frequency, inferred tumor mutational burden, and copy number-derived tumor fraction levels in urine cell-free DNA (cfDNA) significantly predicted pathologic complete response status, far better than plasma ctDNA was able to. A random forest model incorporating these urine cfDNA-derived factors with leave-one-out cross-validation was 87% sensitive for predicting residual disease in reference to gold-standard surgical pathology. Both progression-free survival (HR = 3.00, p = 0.01) and overall survival (HR = 4.81, p = 0.009) were dramatically worse by Kaplan–Meier analysis for patients predicted by the model to have MRD, which was corroborated by Cox regression analysis. Additional survival analyses performed on muscle-invasive, neoadjuvant chemotherapy, and held-out validation subgroups corroborated these findings. In summary, we profiled urine samples from 74 patients with localized bladder cancer and used urine cfDNA multi-omics to detect MRD sensitively and predict survival accurately