radiation-planning-assistant-web-based-tool-to-support-high-quality

Radiation Planning Assistant - A Web-based Tool to Support High-quality Radiotherapy in Clinics with Limited Resources

Access to radiotherapy worldwide is limited. The Radiation Planning Assistant (RPA) is a fully automated, web-based tool that is being developed to offer ...

The University of Texas MD Anderson Cancer Center

To explore the potential of tumor-specific DNA as a biomarker for head and neck squamous cell carcinomas (HNSCC), we queried DNA from saliva or plasma of 93 HNSCC patients. We searched for somatic mutations or human papillomavirus genes, collectively referred to as tumor DNA. When both plasma and saliva were tested, tumor DNA was detected in 96% of 47 patients. The fractions of patients with detectable tumor DNA in early- and late-stage disease were 100% (n = 10) and 95% (n = 37), respectively. When segregated by site, tumor DNA was detected in 100% (n = 15), 91% (n = 22), 100% (n = 7), and 100% (n = 3) of patients with tumors of the oral cavity, oropharynx, larynx, and hypopharynx, respectively. In saliva, tumor DNA was found in 100% of patients with oral cavity cancers and in 47 to 70% of patients with cancers of the other sites. In plasma, tumor DNA was found in 80% of patients with oral cavity cancers, and in 86 to 100% of patients with cancers of the other sites. Thus, saliva is preferentially enriched for tumor DNA from the oral cavity, whereas plasma is preferentially enriched for tumor DNA from the other sites. Tumor DNA in saliva was found postsurgically in three patients before clinical diagnosis of recurrence, but in none of the five patients without recurrence. Tumor DNA in the saliva and plasma appears to be a potentially valuable biomarker for detection of HNSCC.

Detection of somatic mutations and HPV in the saliva and plasma of patients with head and neck squamous cell carcinomas.

There is a significant need to find biomarkers of response to radiotherapy and cetuximab in locally advanced head and neck squamous cell carcinoma (HNSCC) and biomarkers that predict altered immunity, thereby enabling personalized treatment.

The KRAS-Variant and Cetuximab Response in Head and Neck Squamous Cell Cancer: A Secondary Analysis of a Randomized Clinical Trial.

Over the past decade, several strides have been made to improve the management of breast cancer in developing countries; however, there are still obstacles present. In the area of radiation therapy, these hurdles include limited access to radiotherapy treatment and scarcity of oncology specialists. In an effort to reduce inequities in cancer care while improving patient outcomes, our research is focused on developing automated postmastectomy radiation therapy (PMRT) plans for breast cancer patients in these underserved communities that can be further improved upon through treatment planning system (TPS) specific optimization guidelines. The automated planning tool utilized algorithms integrated with Varian's Eclipse TPS. The tool created PMRT plans that used monoisocentric tangents and supraclavicular (SCV) fields with a mix of high and low energy photon beams along with field-in-field (FIF) segments. The completed autogenerated PMRT plans were imported into Phillip's Pinnacle 9.10 and Varian's Eclipse 13.6 TPSs to be further improved through manual optimization; the time required to complete this step was measured and assessed. A senior dosimetrist, physicist, and physician evaluated the optimized plans for clinical acceptability. Guidelines were developed for the planning systems that can be implemented by personnel with either limited experience in radiation treatment planning or those with limited time to produce treatment plans. The autogenerated plans in conjunction with our guidelines have shown to significantly reduce the time required to produce a clinically acceptable PMRT plan from approximately 120 ± 60 minutes to just 13 ± 11 (Pinnacle) and 12 ± 7 (Eclipse) minutes, reducing the total uninterrupted treatment planning time by an average of 108 ± 51 minutes. The results from this research indicate that the autogenerated PMRT plans along with the optimization guidelines are a viable option to provide quality and clinically acceptable PMRT plans that are more efficient and consistent for postmastectomy breast cancer patients in severely underserved communities.

Optimization of autogenerated chest-wall radiation treatment plans developed for postmastectomy breast cancer patients in underserved clinics.

Delta-like protein 3 (DLL3) is highly expressed in solid tumors, including neuroendocrine carcinomas/neuroendocrine tumors (NEC/NET). Rovalpituzumab tesirine (Rova-T) is a DLL3-targeting antibody-drug conjugate. Patients with NECs and other advanced DLL3-expressing tumors were enrolled in this phase I/II study (NCT02709889). The primary endpoint was safety. Two hundred patients were enrolled: 101 with NEC/NET (large-cell NEC, gastroenteropancreatic NEC, neuroendocrine prostate cancer, and other NEC/NET) and 99 with other solid tumors (melanoma, medullary thyroid cancer [MTC], glioblastoma, and other). The recommended phase II dose (RP2D) was 0.3 mg/kg every 6 weeks (q6w) for two cycles. At the RP2D, grade 3/4 adverse events included anemia (17%), thrombocytopenia (15%), and elevated aspartate aminotransferase (8%). Responses were confirmed in 15/145 patients (10%) treated at 0.3 mg/kg, including 9/69 patients (13%) with NEC/NET. Rova-T at 0.3 mg/kg q6w had manageable toxicity, with antitumor activity observed in patients with NEC/NET, melanoma, MTC, and glioblastoma.

A phase I/II study of rovalpituzumab tesirine in delta-like 3-expressing advanced solid tumors.

TP53 mutation is the most frequent genetic event in head and neck squamous cell carcinoma (HNSCC), found in more than 80% of patients with human papillomavirus-negative disease. As mutations in the TP53 gene are associated with worse outcomes in HNSCC, novel therapeutic approaches are needed for patients with TP53-mutated tumors. The National Cancer Institute sponsored a Clinical Trials Planning Meeting to address the issues of identifying and developing clinical trials for patients with TP53 mutations. Subcommittees, or breakout groups, were tasked with developing clinical studies in both the locally advanced and recurrent and/or metastatic (R/M) disease settings as well as considering signal-seeking trial designs. A fourth breakout group was focused on identifying and standardizing biomarker integration into trial design; this information was provided to the other breakout groups prior to the meeting to aid in study development. A total of 4 concepts were prioritized to move forward for further development and implementation. This article summarizes the proceedings of the Clinical Trials Planning Meeting with the goal of developing clinical trials for patients with TP53-mutant HNSCC that can be conducted within the National Clinical Trials Network.

Clinical Trial Development in TP53-Mutated Locally Advanced and Recurrent and/or Metastatic Head and Neck Squamous Cell Carcinoma.

Anaplastic thyroid cancer is a rare and aggressive cancer with no standard radiotherapy-based local treatment. Based on data suggesting synergy between pazopanib and paclitaxel in anaplastic thyroid cancer, NRG Oncology did a double-blind, placebo-controlled, randomised phase 2 clinical trial comparing concurrent paclitaxel and intensity-modulated radiotherapy (IMRT) with the addition of pazopanib or placebo with the aim of improving overall survival in this patient population.

Radiotherapy and paclitaxel plus pazopanib or placebo in anaplastic thyroid cancer (NRG/RTOG 0912): a randomised, double-blind, placebo-controlled, multicentre, phase 2 trial.

This study aimed to use deep learning-based dose prediction to assess head and neck (HN) plan quality and identify suboptimal plans.

Deep Learning-Based Dose Prediction for Automated, Individualized Quality Assurance of Head and Neck Radiation Therapy Plans.

There remains an unmet need to improve clinical outcomes in patients with recurrent or metastatic squamous cell carcinoma of the head and neck (R/M SCCHN).

Efficacy and Safety of Nivolumab Plus Ipilimumab vs Nivolumab Alone for Treatment of Recurrent or Metastatic Squamous Cell Carcinoma of the Head and Neck: The Phase 2 CheckMate 714 Randomized Clinical Trial.

Automation, including the use of artificial intelligence, has been identified as a possible opportunity to help reduce the gap in access and quality for radiotherapy and other aspects of cancer care. The Radiation Planning Assistant (RPA) project was conceived in 2015 (and funded in 2016) to use automated contouring and treatment planning algorithms to support the efforts of oncologists in low- and middle-income countries, allowing them to scale their efforts and treat more patients safely and efficiently (to increase access).

Addressing the Global Expertise Gap in Radiation Oncology: The Radiation Planning Assistant.

In recent years, deep-learning models have been used to predict entire three-dimensional dose distributions. However, the usability of dose predictions to improve plan quality should be further investigated.

Article	Year
Detection of somatic mutations and HPV in the saliva and plasma of patients with head and neck squamous cell carcinomas. Science translational medicine\| PubMed ID: 26109104	2015
The KRAS-Variant and Cetuximab Response in Head and Neck Squamous Cell Cancer: A Secondary Analysis of a Randomized Clinical Trial. JAMA oncology\| PubMed ID: 28006059	2016
Optimization of autogenerated chest-wall radiation treatment plans developed for postmastectomy breast cancer patients in underserved clinics. Medical dosimetry : official journal of the American Association of Medical Dosimetrists\| PubMed ID: 31956001	2020
A phase I/II study of rovalpituzumab tesirine in delta-like 3-expressing advanced solid tumors. NPJ precision oncology\| PubMed ID: 34354225	2021
Clinical Trial Development in TP53-Mutated Locally Advanced and Recurrent and/or Metastatic Head and Neck Squamous Cell Carcinoma. Journal of the National Cancer Institute\| PubMed ID: 36053203	2022
Radiotherapy and paclitaxel plus pazopanib or placebo in anaplastic thyroid cancer (NRG/RTOG 0912): a randomised, double-blind, placebo-controlled, multicentre, phase 2 trial. The Lancet. Oncology\| PubMed ID: 36681089	2023
Deep Learning-Based Dose Prediction for Automated, Individualized Quality Assurance of Head and Neck Radiation Therapy Plans. Practical radiation oncology\| PubMed ID: 36697347	2023
Efficacy and Safety of Nivolumab Plus Ipilimumab vs Nivolumab Alone for Treatment of Recurrent or Metastatic Squamous Cell Carcinoma of the Head and Neck: The Phase 2 CheckMate 714 Randomize... JAMA oncology\| PubMed ID: 37022706	2023
Addressing the Global Expertise Gap in Radiation Oncology: The Radiation Planning Assistant. JCO global oncology\| PubMed ID: 37471671	2023
Deep learning-based dose prediction to improve the plan quality of volumetric modulated arc therapy for gynecologic cancers. Medical physics\| PubMed ID: 37706560	2023

Christine Chung

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