{"doi":"10.1016/j.tipsro.2025.100353","title":"PrecisionPro Fusion: Clinical validation of an automated, rigid, Prostate-Specific MRI-CT Fusion system for prostate radiotherapy planning","abstract":"Background: Accurate image registration between magnetic resonance imaging (MRI) and computed tomography (CT) is required for precise radiation therapy of prostate cancer. Manual registration methods have been identified as a significant barrier to the implementation of advanced treatment techniques such as focal boost therapy. Purpose: To evaluate the accuracy of PrecisionPro Fusion-an automated, rigid, prostate-specific MRI-CT registration pipeline- compared to manual registration by experienced radiation oncologists. Materials and Methods: We conducted a prospective, multi-institutional validation study involving six genitourinary radiation oncologists from three institutions who performed registrations on 20 patient cases. The study used a two-round design with a one-month washout period, where physicians conducted MRI-CT registrations with and without PrecisionPro Fusion. We compared PrecisionPro Fusion to practical accuracy limits of manual registration, defined by intra-physician variability (distance between a physician's two MRI-CT registrations of the same patient case) and inter-physician variability (maximum distance between a physician's registration and the physician consensus- average of all physicians' registrations of that patient case). Physician participants reported on the PrecisionPro Fusion user experience using a System Usability Scale questionnaire. Results: Intra-physician variability for manual subspecialist registrations was median 2.9 mm (IQR: 1.9, 5.4); inter-physician variability was median: 4.7 mm (4.3, 5.7). PrecisionPro Fusion registrations had median distance from the physician consensus of 1.3 mm (IQR: 0.9, 2.7). The system received high usability scores (median 81; IQR: 74, 88). Conclusion: PrecisionPro Fusion provides prostate MRI-CT registration accuracy comparable to manual physician registration. Automated, rigid, prostate-specific MRI-CT registration could enable faster delineation of structures visible on MRI, including the urethra and intraprostatic tumors.","journal":"Technical Innovations & Patient Support in Radiation Oncology","year":2025,"id":580509,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9569,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":360587,"name":"Christopher C. Conlin","orcid":"0000-0003-4509-8702","position":1,"is_corresponding":false},{"id":1319696,"name":"Madison Baxter","orcid":null,"position":2,"is_corresponding":false},{"id":654779,"name":"John P. Christodouleas","orcid":"0000-0001-5061-2038","position":3,"is_corresponding":false},{"id":393051,"name":"Robert T. Dess","orcid":"0000-0003-2331-3758","position":4,"is_corresponding":false},{"id":1491303,"name":"I. Dragojević","orcid":"0000-0003-0748-4776","position":5,"is_corresponding":false},{"id":262585,"name":"Mukesh G. Harisinghani","orcid":"0000-0003-0993-1947","position":6,"is_corresponding":false},{"id":584404,"name":"Sophia C. Kamran","orcid":"0000-0001-9283-6515","position":7,"is_corresponding":false},{"id":391671,"name":"Vitali Moiseenko","orcid":null,"position":8,"is_corresponding":false},{"id":727631,"name":"Himanshu Nagar","orcid":"0000-0003-2381-6910","position":9,"is_corresponding":false},{"id":1491304,"name":"Nabih Nakrour","orcid":"0009-0000-6402-7585","position":10,"is_corresponding":false},{"id":1407944,"name":"Lily Nguyen","orcid":"0009-0004-0076-1640","position":11,"is_corresponding":false},{"id":1491730,"name":"Rhea Rupareliya","orcid":null,"position":12,"is_corresponding":false},{"id":456307,"name":"Steven N. Seyedin","orcid":"0000-0002-6841-968X","position":13,"is_corresponding":false},{"id":1381053,"name":"Yuze Song","orcid":"0000-0001-5803-1254","position":14,"is_corresponding":false},{"id":19608,"name":"Anders M. Dale","orcid":"0000-0002-6126-2966","position":15,"is_corresponding":false},{"id":360589,"name":"Tyler M. Seibert","orcid":"0000-0002-4089-7399","position":16,"is_corresponding":false},{"id":1491302,"name":"Deondre Do","orcid":"0009-0007-5943-3379","position":0,"is_corresponding":true}],"reference_count":20,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T02:58:38.868285Z","pmid":"41322076","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}