Physics and Imaging in Radiation Oncology最新文献

{"title":"Linear approximation of variable relative biological effectiveness models for proton therapy","authors":"Dirk Wagenaar,&nbsp;Johannes A. Langendijk,&nbsp;Stefan Both","doi":"10.1016/j.phro.2024.100691","DOIUrl":"10.1016/j.phro.2024.100691","url":null,"abstract":"<div><div>The McNamara (MCN) and Wedenberg (WED) RBE weighted dose (D_RBE), dose and dose-weighted average LET (LET_d) were calculated in twenty brain cancer patients. A linear approximation was made for each RBE model to give best agreement to clinically relevant dosimetric parameters. Additional evaluations were done on twenty head and neck and twenty breast cancer patients.The R² of the fits was ≥0.94 and ≥0.91 for MCN and WED respectively for α/β values ≥1.0 Gy. The graphs derived in this work can be used to convert RBE-LET slopes derived from clinical data to α/β values in the MCN or WED models.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"33 ","pages":"Article 100691"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11780161/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143068554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Repeatability of rectal cancer apparent diffusion coefficient measurements on a 1.5 T MR-linac","authors":"Hidde Eijkelenkamp ,&nbsp;Guus Grimbergen ,&nbsp;Brigid McDonald ,&nbsp;Reijer Rutgers ,&nbsp;Tim Schakel ,&nbsp;Casper Beijst ,&nbsp;Marielle Philippens ,&nbsp;Gert Meijer ,&nbsp;Martijn Intven","doi":"10.1016/j.phro.2025.100720","DOIUrl":"10.1016/j.phro.2025.100720","url":null,"abstract":"<div><div>The repeatability of the apparent diffusion coefficient (ADC) during radiotherapy for rectal cancer on a 1.5 T MR-linac was investigated by acquiring two sequential diffusion-weighted imaging (DWI) sequences at each fraction. In 109 treatment sessions involving 22 patients, tumors were separately delineated on the b500 images. ADC maps were generated with all b-values (0, 30, 150, and 500 s/mm²) on the MR-linac, and the median ADC values were used in Bland-Altman analyses. A relative repeatability coefficient of 17.0 % was determined, providing a threshold to differentiate between measurement variability and true treatment response. This threshold can be used for potential response monitoring and personalized treatment adjustments.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"33 ","pages":"Article 100720"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143511833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neurovascular bundle sparing in hypofractionated radiotherapy maintained with realistic treatment uncertainties","authors":"Roel C. Kwakernaak,&nbsp;Victor J. Brand,&nbsp;Jesús Rojo-Santiago,&nbsp;Femke E. Froklage,&nbsp;Mischa S. Hoogeman,&nbsp;Steven J.M. Habraken,&nbsp;Maaike T.W. Milder","doi":"10.1016/j.phro.2025.100714","DOIUrl":"10.1016/j.phro.2025.100714","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Erectile dysfunction is a common side effect of radiotherapy for prostate cancer. To mitigate this toxicity, it has been suggested to limit the dose to critical nerves and vessels. We investigated the feasibility of sparing the neuro-vascular bundles (NVBs) in stereotactic body radiotherapy under the impact of realistic treatment uncertainties.</div></div><div><h3>Materials and methods</h3><div>Non-sparing and sparing NVB treatment plans, delivered in 5 × 7.25 Gy, were automatically generated for 20 patients. Polynomial Chaos Expansion (PCE) was used to fast and accurately model the dose against treatment errors. PCE enabled a robustness evaluation of 100.000 treatment scenarios per plan, allowing to derive scenario distributions of clinically relevant dose volume histogram parameters and population dose histograms.</div></div><div><h3>Results</h3><div>An average decrease of 3.7 Gy and 4.4 Gy in the median <span><math><mrow><msub><mi>D</mi><mrow><mn>0.1</mn><mi>c</mi><msup><mrow><mi>m</mi></mrow><mn>3</mn></msup></mrow></msub></mrow></math></span> of the NVB was achieved in the patient population in the presence of realistic treatment uncertainties for non-coplanar (NC) and coplanar (C) plans respectively. Sparing NVBs decreased planning target volume coverage by 2.1 % in <span><math><mrow><msub><mi>V</mi><mrow><mn>36.25</mn><mi>G</mi><mi>y</mi></mrow></msub></mrow></math></span> on average, however clinical target volume (CTV) dose remained adequate. Population dose histograms showed that, while sparing does impact dose volume histogram parameters of organs at risk (OARs), the probability of a scenario exceeding planning constraints was limited.</div></div><div><h3>Conclusion</h3><div>NVB sparing was maintained in the presence of treatment uncertainties without compromising CTV coverage or OAR dose. There was no significant difference in the achieved NVB dose between NC and C plans. The clinical impact of the achieved sparing is subject of ongoing clinical trials.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"33 ","pages":"Article 100714"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143130343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"New rectum dose surface mapping methodology to identify rectal subregions associated with toxicities following prostate cancer radiotherapy","authors":"Artemis Bouzaki ,&nbsp;Dylan Green ,&nbsp;Marcel van Herk ,&nbsp;Jane Shortall ,&nbsp;Tanuj Puri ,&nbsp;Sarah Kerns ,&nbsp;David Azria ,&nbsp;Marrie-Pierre Farcy-Jacquet ,&nbsp;Jenny Chang-Claude ,&nbsp;Ananya Choudhury ,&nbsp;Alison Dunning ,&nbsp;Maarten Lambrecht ,&nbsp;Barbara Avuzzi ,&nbsp;Dirk De Ruysscher ,&nbsp;Petra Seibold ,&nbsp;Elena Sperk ,&nbsp;Christopher Talbot ,&nbsp;Ana Vega ,&nbsp;Liv Veldeman ,&nbsp;Adam Webb ,&nbsp;Alan McWilliam","doi":"10.1016/j.phro.2025.100701","DOIUrl":"10.1016/j.phro.2025.100701","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Growing evidence suggests that spatial dose variations across the rectal surface influence toxicity risk after radiotherapy. Existing methodologies employ a fixed, arbitrary physical extent for rectal dose mapping, limiting their analysis. We developed a method to standardise rectum contours, unfold them into 2D cylindrical surface maps, and identify subregions where higher doses increase rectal toxicities.</div></div><div><h3>Materials and methods</h3><div>Data of 1,048 patients with prostate cancer from the REQUITE study were used. Deep learning based automatic segmentations were generated to ensure consistency. Rectum length was standardised using linear transformations superior and inferior to the prostate. The automatic contours were validated against the manual contours through contour variation assessment with cylindrical mapping. Voxel-based analysis of the dose surface maps for the manual and automatic contours against individual rectal toxicities was performed using Student’s t permutation test and Cox Proportional Hazards Model (CPHM). Significance was defined by permutation testing.</div></div><div><h3>Results</h3><div>Our method enabled the analysis of 1,048 patients using automatic segmentation. Student’s <em>t</em>-test showed significance (p &lt; 0.05) in the lower posterior for clinical-reported proctitis and patient-reported bowel urgency. Univariable CPHM identified a 3 % increased risk per Gy for clinician-reported proctitis and a 2 % increased risk per Gy for patient-reported bowel urgency in the lower posterior. No other endpoints were significant.</div></div><div><h3>Conclusion</h3><div>We developed a methodology that unfolds the rectum to a 2D surface map. The lower posterior was significant for clinician-reported proctitis and patient-reported bowel urgency, suggesting that reducing the dose in the region could decrease toxicity risk.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"33 ","pages":"Article 100701"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143130345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adaptive treatment workflow and dosimetric evaluation of intracranial fractionated stereotactic radiosurgery on a low-field magnetic resonance-linear accelerator","authors":"Karen Chin Snyder,&nbsp;Salim M. Siddiqui,&nbsp;Parag Parikh,&nbsp;Kundan Thind","doi":"10.1016/j.phro.2025.100702","DOIUrl":"10.1016/j.phro.2025.100702","url":null,"abstract":"<div><h3>Background and Purpose</h3><div>Online adaptive radiotherapy for fractionated intracranial stereotactic radiosurgery (FSRS) on a magnetic resonance linear accelerator (MR-L) has the potential to allow for real-time adjustments of anatomical changes during radiotherapy treatment. This study investigates the dosimetric improvements of an online-adaptive MR-L workflow and validates the dosimetry utilizing an MR-visible phantom.</div></div><div><h3>Methods and materials</h3><div>Twenty-six cases previously treated with a conventional C-arm linear accelerator (CA-L) were replanned to determine optimal optimization constraints and objectives for achieving comparable MR-L plans. The optimization methodology was subsequently applied to simulate an online adaptive workflow on an MR phantom, incorporating target volumes from five previously treated patients that required offline adaptation. Plan quality and normal brain dose statistics were evaluated and compared to the offline adapted CA-L plans.</div></div><div><h3>Results</h3><div>No significant difference was observed between the CA-L and MR-L target coverage. The normal brain dose for MR-L plans increased with target volume more rapidly than for CA-L plans. However, some outliers achieved equivalent normal brain doses, indicating potential benefits of MRIgRT for specific superficial volumes located in the frontal, occipital lobes, and cerebellum. End-to-end validation with simulated adaptive workflow on a MR phantom utilizing target volumes that previously required adaption showed acceptable difference of &lt;2.5 % between measured and planned target dose.</div></div><div><h3>Conclusion</h3><div>The study shows promising results for an online adaptive workflow for the treatment of intracranial FSRS on a low-field MR-L.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"33 ","pages":"Article 100702"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143130572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling dose uncertainty in cone-beam computed tomography: Predictive approach for deep learning-based synthetic computed tomography generation","authors":"Cédric Hémon,&nbsp;Lucía Cubero,&nbsp;Valentin Boussot,&nbsp;Romane-Alize Martin,&nbsp;Blanche Texier,&nbsp;Joël Castelli,&nbsp;Renaud de Crevoisier,&nbsp;Anaïs Barateau,&nbsp;Caroline Lafond,&nbsp;Jean-Claude Nunes","doi":"10.1016/j.phro.2025.100704","DOIUrl":"10.1016/j.phro.2025.100704","url":null,"abstract":"<div><h3>Background and purpose:</h3><div>Cone-beam computed tomography (CBCT) is essential in image-guided radiotherapy (RT) for patient positioning and daily dose calculation. However, CT numbers in CBCT fluctuate and differ from those in computed tomography (CT), requiring synthetic CT (sCT) generation to improve dose calculation accuracy. CBCT-to-sCT synthesis remains a challenging and uncertain task in clinical practice. This study aims to introduce a voxel-wise uncertainty estimator correlated with the error between sCT and CT.</div></div><div><h3>Material and Methods:</h3><div>Eighty-five head and neck (H&amp;N) patients treated with photon RT from a single center were selected for developing and validating our uncertainty estimation method. To test the method’s robustness on out-of-distribution images, three additional patients from different centers were included. Our proposed uncertainty estimation method builds on established conventional techniques. Additionally, to explore potential error scenarios, we generated several ‘plausible’ sCTs representing variations in sCT generation caused by CBCT quality differences. This allowed us to quantify dose uncertainties.</div></div><div><h3>Results:</h3><div>The effectiveness of uncertainty maps was evaluated by correlating them with the absolute error map between sCT and CT, yielding a Pearson correlation coefficient between 0.65 and 0.72. Dose uncertainty was determined on the dose-volume histogram (DVH). For all patients except one, the reference CT DVH was included in the uncertainty interval defined by the sCT-derived DVH.</div></div><div><h3>Conclusions:</h3><div>Our proposed methods effectively predict uncertainty maps that aid in evaluating sCT quality. This approach also provides a novel method for estimating dose uncertainty by defining a confidence interval around the CT DVH using the estimated sCT uncertainty.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"33 ","pages":"Article 100704"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143130581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Translation of dynamic contrast-enhanced imaging onto a magnetic resonance-guided linear accelerator in patients with head and neck cancer","authors":"Michael J. Dubec ,&nbsp;Michael Berks ,&nbsp;James Price ,&nbsp;Lisa McDaid ,&nbsp;John Gaffney ,&nbsp;Ross A. Little ,&nbsp;Susan Cheung ,&nbsp;Marcel van Herk ,&nbsp;Ananya Choudhury ,&nbsp;Julian C. Matthews ,&nbsp;Andrew McPartlin ,&nbsp;Geoff J.M. Parker ,&nbsp;David L. Buckley ,&nbsp;James P.B. O’Connor","doi":"10.1016/j.phro.2024.100689","DOIUrl":"10.1016/j.phro.2024.100689","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Magnetic resonance imaging – linear accelerator (MRI-linac) systems permit imaging of tumours to guide treatment. Dynamic contrast enhanced (DCE)-MRI allows investigation of tumour perfusion. We assessed the feasibility of performing DCE-MRI on a 1.5 T MRI-linac in patients with head and neck cancer (HNC) and measured biomarker repeatability and sensitivity to radiotherapy effects.</div></div><div><h3>Materials and methods</h3><div>Patients were imaged on a 1.5 T MRI-linac or a 1.5 T diagnostic MR system twice before treatment. DCE-MRI parameters including K^trans were calculated, with the optimum pharmacokinetic model identified using corrected Akaike information criterion. Repeatability was assessed by within-subject coefficient of variation (wCV). Treatment effects were assessed as change measured at week 2 of radiotherapy.</div></div><div><h3>Results</h3><div>14 patients were recruited (6 scanned on diagnostic MR and 8 on MRI-linac), with a total of 24 lesions. Baseline K^trans estimates were comparable on both MR systems; 0.13 [95 %CI: 0.10 to 0.16] min⁻¹ (diagnostic MR) and 0.15 [0.12 to 0.18] min⁻¹ (MRI-linac). wCV values were 22.6 % [95 % CI: 16.2 to 37.3 %] (diagnostic MR) and 11.7 % [8.4 to 19.3 %] (MRI-linac). Combined cohort increase in K^trans was significant (p &lt; 0.01). Similar results were seen for other DCE-MRI parameters.</div></div><div><h3>Conclusions</h3><div>DCE-MRI is feasible on a 1.5 T MRI-linac system in patients with HNC. Parameter estimates, repeatability, and sensitivity to treatment were similar to those measured on a conventional diagnostic MR system. These data support performing DCE-MRI in studies on the MRI-linac to assess treatment response and adaptive guidance based on tumour perfusion.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"33 ","pages":"Article 100689"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11721217/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142972457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corrigendum to “Explicitly encoding the cyclic nature of breathing signal allows for accurate breathing motion prediction in radiotherapy with minimal training data” [Phys. Imaging Radiat. Oncol. 30 (2024) 100594]","authors":"Andreas Renner ,&nbsp;Ingo Gulyas ,&nbsp;Martin Buschmann ,&nbsp;Gerd Heilemann ,&nbsp;Barbara Knäusl ,&nbsp;Martin Heilmann ,&nbsp;Joachim Widder ,&nbsp;Dietmar Georg ,&nbsp;Petra Trnková","doi":"10.1016/j.phro.2025.100718","DOIUrl":"10.1016/j.phro.2025.100718","url":null,"abstract":"","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"33 ","pages":"Article 100718"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143130583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Accuracy-dependent dose-constraints and dose-based safety margins for organs-at-risk in radiotherapy","authors":"Joep C. Stroom ,&nbsp;Sandra C. Vieira ,&nbsp;Carlo Greco ,&nbsp;Sebastiaan M.J.J.G. Nijsten","doi":"10.1016/j.phro.2025.100713","DOIUrl":"10.1016/j.phro.2025.100713","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Geometrical uncertainties in radiotherapy are generally accounted for by margins for tumors, but their effect on organs-at-risk (OARs) is often ignored. We developed a model that incorporates dose- and geometry-based uncertainties in OAR planning using dose constraints.</div></div><div><h3>Materials and methods</h3><div>Radiotherapy uncertainties cause real dose-volume histograms (DVHs) to spread around the planned DVH. With a <em>published</em> OAR dose constraint D(V_crit) &lt; D_crit such that complication probability &lt; Y%, real differences from planned D_crit can be described by mean- (MD_Dcrit) and standard deviations (SD_Dcrit). Assuming complications are associated with the worst DVHs, <em>New</em> dose constraints that maintain complication probability can be derived for new treatments:<span><span><span>D_crit,New = D_crit,publ + Φ⁻¹(1 - Y%) * (SD_Dcrit,publ - SD_Dcrit,New) + (MD_Dcrit,publ - MD_Dcrit,New),</span></span></span>with Φ⁻¹(x) the inverse cumulative normal distribution function. Setting SD_Dcrit,New = MD_Dcrit,New = 0 in the recipe yields the “True” critical dose, and D_crit,True - D_crit,publ can be considered a dose-based safety margin (DSM).</div><div>As hypothetical example, we estimated MD_Dcrit and SD_Dcrit values by simulating geometric errors in our clinical treatment plans and adding dose-based uncertainty. Over 1000 OARs with 108 different regular- and hypo-fractionation constraints were simulated. We assumed accuracy SDs to change from 2.5mm/3% to 1.5mm/2%.</div></div><div><h3>Results</h3><div>Results varied per OAR, fractionation, and constraint-type. If our 2.5mm/3% MD_Dcrit and SD_Dcrit values approximated dose-constraint studies, on average the DSM would be 4.5 Gy (18%) and our dose constraints would increase with 1.2 Gy (5%).</div></div><div><h3>Conclusions</h3><div>We introduced a first model relating dose constraints and complication probabilities with treatment uncertainties and safety margins for OARs. Among other things, it quantified how higher constraints can be applied with increasing radiotherapy accuracy.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"33 ","pages":"Article 100713"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143130342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel multimodality anthropomorphic phantom enhances compliance with quality assurance guidelines for magnetic resonance imaging in radiotherapy","authors":"Meshal Alzahrani ,&nbsp;David A Broadbent ,&nbsp;Irvin Teh ,&nbsp;Bashar Al-Qaisieh ,&nbsp;Emily Johnstone ,&nbsp;Richard Speight","doi":"10.1016/j.phro.2025.100707","DOIUrl":"10.1016/j.phro.2025.100707","url":null,"abstract":"<div><h3>Background and purpose</h3><div>The use of magnetic resonance imaging (MRI) for radiotherapy (RT) simulation has grown, prompting quality assurance (QA) guidelines by the Institute of Physics and Engineering in Medicine (IPEM) and the American Association of Physicists in Medicine (AAPM). This study compares a novel multimodality anthropomorphic phantom to an American College of Radiology (ACR) phantom for a subset of these MRI-specific QA tests in RT.</div></div><div><h3>Materials and methods</h3><div>A novel 3D-printed multimodality head-and-neck anthropomorphic phantom was compared to an ACR large MRI phantom. IPEM and AAPM-recommended QA tests were conducted, including informatics/connectivity/data transfer, MRI-CT registration, end-to-end QA, and signal-to-noise ratio (SNR)/percentage integral uniformity (PIU) assessments using RT accessories.</div></div><div><h3>Results</h3><div>Both phantoms were suitable for informatics/connectivity/data transfer. In MRI-CT registration, no errors were found; the ACR phantom offered more quantitative landmarks, while the anthropomorphic phantom provided limited structures. Both phantoms achieved target registration errors (TREs) below 0.97 mm and dice similarity coefficient (DSC) values above 0.9, meeting guidelines. For end-to-end QA, the anthropomorphic phantom facilitated dose measurements of 1.994 Gy versus a calculated 2.01 Gy (−0.8 %). SNR and PIU assessments showed higher values in radiology setups compared to RT setups for both phantoms.</div></div><div><h3>Conclusions</h3><div>Multimodality anthropomorphic phantoms compatible with dosimetric equipment allow realistic end-to-end QA, unlike the ACR phantom. While the ACR phantom is suitable for informatics and MRI-CT registration, anthropomorphic phantoms better represent clinical scenarios. For comprehensive QA, both ACR and anthropomorphic phantoms are required. Additionally, large field-of-view (FOV) phantoms are crucial for evaluating large FOV MRI distortions.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"33 ","pages":"Article 100707"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143130585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}