{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T18:13:50Z","timestamp":1788372830056,"version":"build-2803163510"},"reference-count":30,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T00:00:00Z","timestamp":1763078400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Cancers"],"abstract":"<jats:p>Background\/Objectives: Treatment planning for stage III non\u2013small cell lung cancer (NSCLC) presents dosimetric challenges due to the proximity of critical structures. RapidPlan (RP), a knowledge-based planning (KBP) system, offers the potential for improved plan consistency and organ-at-risk (OAR) sparing. The objective of this study was to compare dosimetric and clinical outcomes of RP-generated plans versus manually optimized plans in patients with stage III NSCLC undergoing IMRT or VMAT. Methods: In this retrospective analysis, 50 patients treated with concurrent chemoradiation for stage III NSCLC at Hadassah Medical Center (2015\u20132021) were analyzed. RP plans were generated using a lung-specific model in the Eclipse treatment planning system and compared with the original clinical manual plans. Dosimetric parameters for target volumes and OARs were evaluated, and subgroup analyses were performed by technique (IMRT vs. VMAT). Toxicity and survival outcomes were analyzed, and Normal Tissue Complication Probability (NTCP) modeling was conducted. Results: RP significantly reduced mean heart dose (\u0394 = \u22122.54 Gy, p &lt; 0.001), spinal cord maximum dose (\u0394 = \u22124.08 Gy, p &lt; 0.001), and esophageal mean dose (\u0394 = \u22123.89 Gy, p &lt; 0.001) compared with manual plans. Lung doses were slightly higher in RP plans (V20 \u0394 = +2.12%, p &lt; 0.001). VMAT-RP plans demonstrated greater cardiac and esophageal sparing than VMAT-manual plans. RP yielded significant NTCP reductions for the heart (0.34% \u2192 0.20%) and esophagus (16.6% \u2192 11.5%), but no improvement for lung or spinal cord. Lung toxicity \u2265 grade 2 was associated with reduced overall survival (16.2 vs. 51.8 months, p &lt; 0.001). Conclusions: RapidPlan-based knowledge-based planning enhances OAR sparing while maintaining target coverage in locally advanced NSCLC. Slight increases in lung dose highlight the need for ongoing model refinement. An association between lung toxicity and reduced survival was observed, underscoring the impact of treatment-related morbidity on outcomes.<\/jats:p>","DOI":"10.3390\/cancers17223654","type":"journal-article","created":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T10:07:03Z","timestamp":1763114823000},"page":"3654","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["RapidPlan Knowledge-Based Radiotherapy Planning Compared to Manual Planning in Locally Advanced Non-Small-Cell Lung Cancer"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7733-9438","authenticated-orcid":false,"given":"Tal","family":"Falick Michaeli","sequence":"first","affiliation":[{"name":"Department of Radiation Oncology, Sharett Institute of Oncology Hadassah Medical Center, Jerusalem 91120, Israel"},{"name":"Department of Developmental Biology and Cancer Research, Institute for Medical Research Israel-Canada, Hebrew University Medical School, Jerusalem 91120, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tamar","family":"Abu Said","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology, Sharett Institute of Oncology Hadassah Medical Center, Jerusalem 91120, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stanislav","family":"Raskin","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology, Sharett Institute of Oncology Hadassah Medical Center, Jerusalem 91120, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-8581-3142","authenticated-orcid":false,"given":"Antoni","family":"Skripai","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology, Sharett Institute of Oncology Hadassah Medical Center, Jerusalem 91120, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yakir","family":"Rottenberg","sequence":"additional","affiliation":[{"name":"Department of Medical Oncology, Sharett Institute of Oncology Hadassah Medical Center, Jerusalem 91120, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5688-5712","authenticated-orcid":false,"given":"Johnathan","family":"Arnon","sequence":"additional","affiliation":[{"name":"Department of Medical Oncology, Sharett Institute of Oncology Hadassah Medical Center, Jerusalem 91120, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4672-6862","authenticated-orcid":false,"given":"Philip","family":"Blumenfeld","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology, Sharett Institute of Oncology Hadassah Medical Center, Jerusalem 91120, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,11,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1430","DOI":"10.1016\/j.jtho.2019.04.005","article-title":"Real-World Treatment of Stage III NSCLC: The Role of Trimodality Treatment in the Era of Immunotherapy","volume":"14","author":"Moore","year":"2019","journal-title":"J. Thorac. Oncol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1623","DOI":"10.1016\/j.mayocp.2019.01.013","article-title":"Non-Small Cell Lung Cancer: Epidemiology, Screening, Diagnosis, and Treatment","volume":"94","author":"Duma","year":"2019","journal-title":"Mayo Clin. Proc."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1038\/s41416-020-01069-z","article-title":"The current treatment landscape in the UK for stage III NSCLC","volume":"123","author":"Evison","year":"2020","journal-title":"Br. J. Cancer"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Wass, R., Hochmair, M., Kaiser, B., Grambozov, B., Feurstein, P., Wei\u00df, G., Moosbrugger, R., Sedlmayer, F., Lamprecht, B., and Studnicka, M. (2022). Durvalumab after Sequential High Dose Chemoradiotherapy versus Standard of Care (SoC) for Stage III NSCLC: A Bi-Centric Trospective Comparison Focusing on Pulmonary Toxicity. Cancers, 14.","DOI":"10.3390\/cancers14133226"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"2342","DOI":"10.1056\/NEJMoa1809697","article-title":"Overall Survival with Durvalumab after Chemoradiotherapy in Stage III NSCLC","volume":"379","author":"Antonia","year":"2018","journal-title":"N. Engl. J. Med."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1016\/S1470-2045(14)71207-0","article-title":"Standard-dose versus high-dose conformal radiotherapy with concurrent and consolidation carboplatin plus paclitaxel with or without cetuximab for patients with stage IIIA or IIIB non-small-cell lung cancer (RTOG 0617): A randomised, two-by-two factorial phase 3 study","volume":"16","author":"Bradley","year":"2015","journal-title":"Lancet Oncol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1387","DOI":"10.1200\/JCO.2016.70.0229","article-title":"Cardiac Toxicity After Radiotherapy for Stage III Non-Small-Cell Lung Cancer: Pooled Analysis of Dose-Escalation Trials Delivering 70 to 90 Gy","volume":"35","author":"Wang","year":"2017","journal-title":"J. Clin. Oncol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1016\/j.radonc.2017.10.001","article-title":"Heart dosimetric analysis of three types of cardiac toxicity in patients treated on dose-escalation trials for Stage III non-small-cell lung cancer","volume":"125","author":"Wang","year":"2017","journal-title":"Radiother. Oncol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"310","DOI":"10.1002\/jmrs.420","article-title":"Rolling out RapidPlan: What we\u2019ve learnt","volume":"67","author":"Le","year":"2020","journal-title":"J. Med. Radiat. Sci."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1021","DOI":"10.1016\/j.ijrobp.2017.07.012","article-title":"Performance of Knowledge-Based Radiation Therapy Planning for the Glioblastoma Disease Site","volume":"99","author":"Chatterjee","year":"2017","journal-title":"Int. J. Radiat. Oncol. Biol. Phys."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"250","DOI":"10.4103\/jmp.jmp_138_21","article-title":"Validation of RapidPlan Knowledge-Based Model for Volumetric-Modulated Arc Therapy in Prostate Cancer","volume":"47","author":"Ayuthaya","year":"2022","journal-title":"J. Med. Phys."},{"key":"ref_12","first-page":"e219","article-title":"RapidPlan for Knowledge-Based Planning of Malignant Pleural Mesothelioma","volume":"11","author":"Dumane","year":"2021","journal-title":"Radiat. Oncol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1194","DOI":"10.1080\/0284186X.2023.2238882","article-title":"Improving knowledge-based treatment planning for lung cancer radiotherapy with automatic multi-criteria optimized training plans","volume":"62","author":"Fjellanger","year":"2023","journal-title":"Acta Oncol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1016\/j.meddos.2024.10.003","article-title":"Dosimetric comparison between laterality-specific and general knowledge-based planning models for nonsmall cell lung cancer","volume":"50","author":"Seng","year":"2025","journal-title":"Med. Dosim."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"967","DOI":"10.1007\/s00066-023-02126-1","article-title":"Novel in-house knowledge-based automated planning system for lung cancer treated with intensity-modulated radiotherapy","volume":"200","author":"Shao","year":"2023","journal-title":"Strahlenther. Und Onkol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"e14152","DOI":"10.1002\/acm2.14152","article-title":"Automated evaluation for rapid implementation of knowledge-based radiotherapy planning models","volume":"24","author":"Harms","year":"2023","journal-title":"J. Appl. Clin. Med. Phys."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"2606","DOI":"10.1200\/JCO.1995.13.10.2606","article-title":"Radiation pneumonitis following combined modality therapy for lung cancer: Analysis of prognostic factors","volume":"13","author":"Roach","year":"1995","journal-title":"J. Clin. Oncol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"100745","DOI":"10.1016\/j.adro.2021.100745","article-title":"Implementation of a Knowledge-Based Treatment Planning Model for Cardiac-Sparing Lung Radiation Therapy","volume":"6","author":"Harms","year":"2021","journal-title":"Adv. Radiat. Oncol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1016\/j.ijrobp.2016.10.005","article-title":"Highly Efficient Training, Refinement, and Validation of a Knowledge-based Planning Quality-Control System for Radiation Therapy Clinical Trials","volume":"97","author":"Li","year":"2017","journal-title":"Int. J. Radiat. Oncol. Biol. Phys."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1533033820973283","DOI":"10.1177\/1533033820973283","article-title":"Comprehensive Comparison of Progressive Optimization Algorithm Based Automatic Plan and Manually Planned Treatment Technique for Cervical-Thoracic Esophageal Cancers","volume":"19","author":"Zhou","year":"2020","journal-title":"Technol. Cancer Res. Treat."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1002\/acm2.13114","article-title":"An Automated knowledge-based planning routine for stereotactic body radiotherapy of peripheral lung tumors via DCA-based volumetric modulated arc therapy","volume":"22","author":"Visak","year":"2020","journal-title":"J. Appl. Clin. Med. Phys."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"974","DOI":"10.1111\/1754-9485.13737","article-title":"Moving beyond mean heart dose: The importance of cardiac substructures in radiation therapy toxicity","volume":"68","author":"Jones","year":"2024","journal-title":"J. Med. Imaging Radiat. Oncol."},{"key":"ref_23","first-page":"tzae006","article-title":"Assessment of heart-substructures auto-contouring accuracy for application in heart-sparing radiotherapy for lung cancer","volume":"6","author":"Marchant","year":"2024","journal-title":"BJR Open"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"110654","DOI":"10.1016\/j.radonc.2024.110654","article-title":"Dosimetric impact of sparing base of heart on organ at risk doses during lung radiotherapy","volume":"202","author":"Marchant","year":"2025","journal-title":"Radiother. Oncol."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"20180270","DOI":"10.1259\/bjr.20180270","article-title":"Automation in intensity modulated radiotherapy treatment planning-a review of recent innovations","volume":"91","author":"Hussein","year":"2018","journal-title":"Br. J. Radiol."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1287","DOI":"10.1016\/j.ijrobp.2023.06.019","article-title":"Explainable Artificial Intelligence to Identify Dosimetric Predictors of Toxicity in Patients with Locally Advanced Non-Small Cell Lung Cancer: A Secondary Analysis of RTOG 0617","volume":"117","author":"Ladbury","year":"2023","journal-title":"Int. J. Radiat. Oncol. Biol. Phys."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1307","DOI":"10.2967\/jnumed.124.267434","article-title":"RadShap: An Explanation Tool for Highlighting the Contributions of Multiple Regions of Interest to the Prediction of Radiomic Models","volume":"65","author":"Captier","year":"2024","journal-title":"J. Nucl. Med."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Severn, C., Suresh, K., G\u00f6rg, C., Choi, Y.S., Jain, R., and Ghosh, D. (2022). A Pipeline for the Implementation and Visualization of Explainable Machine Learning for Medical Imaging Using Radiomics Features. Sensors, 22.","DOI":"10.3390\/s22145205"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"252","DOI":"10.1016\/j.semradonc.2023.03.003","article-title":"The Promise and Future of Radiomics for Personalized Radiotherapy Dosing and Adaptation","volume":"33","author":"Ger","year":"2023","journal-title":"Semin. Radiat. Oncol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"e269","DOI":"10.1016\/j.clon.2024.03.003","article-title":"Radiomics for clinical decision support in radiation oncology","volume":"36","author":"Russo","year":"2024","journal-title":"Clin. Oncol."}],"container-title":["Cancers"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-6694\/17\/22\/3654\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,16]],"date-time":"2025-12-16T09:02:23Z","timestamp":1765875743000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-6694\/17\/22\/3654"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,14]]},"references-count":30,"journal-issue":{"issue":"22","published-online":{"date-parts":[[2025,11]]}},"alternative-id":["cancers17223654"],"URL":"https:\/\/doi.org\/10.3390\/cancers17223654","relation":{},"ISSN":["2072-6694"],"issn-type":[{"value":"2072-6694","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,11,14]]}}}