Physics and Imaging in Radiation Oncology最新文献

{"title":"Multi-modality imaging parameters that predict rapid tumor regression in head and neck radiotherapy","authors":"Eric Aliotta ,&nbsp;Ramesh Paudyal ,&nbsp;Bill Diplas ,&nbsp;James Han ,&nbsp;Yu-Chi Hu ,&nbsp;Jung Hun Oh ,&nbsp;Vaios Hatzoglou ,&nbsp;Naomi Jensen ,&nbsp;Peng Zhang ,&nbsp;Michalis Aristophanous ,&nbsp;Nadeem Riaz ,&nbsp;Joseph O. Deasy ,&nbsp;Nancy Y. Lee ,&nbsp;Amita Shukla-Dave","doi":"10.1016/j.phro.2024.100603","DOIUrl":"https://doi.org/10.1016/j.phro.2024.100603","url":null,"abstract":"<div><h3>Background and purpose</h3><p>Volume regression during radiotherapy can indicate patient-specific treatment response. We aimed to identify pre-treatment multimodality imaging (MMI) metrics from positron emission tomography (PET), magnetic resonance imaging (MRI), and computed tomography (CT) that predict rapid tumor regression during radiotherapy in human papilloma virus (HPV) associated oropharyngeal carcinoma.</p></div><div><h3>Materials and methods</h3><p>Pre-treatment FDG PET-CT, diffusion-weighted MRI (DW-MRI), and intra-treatment (at 1, 2, and 3 weeks) MRI were acquired in 72 patients undergoing chemoradiation therapy for HPV+ oropharyngeal carcinoma. Nodal gross tumor volumes were delineated on longitudinal images to measure intra-treatment volume changes. Pre-treatment PET standardized uptake value (SUV), CT Hounsfield Unit (HU), and non-gaussian intravoxel incoherent motion DW-MRI metrics were computed and correlated with volume changes. Intercorrelations between MMI metrics were also assessed using network analysis. Validation was carried out on a separate cohort (N = 64) for FDG PET-CT.</p></div><div><h3>Results</h3><p>Significant correlations with volume loss were observed for baseline FDG SUV_mean (Spearman ρ = 0.46, p &lt; 0.001), CT HU_mean (ρ = 0.38, p = 0.001), and DW-MRI diffusion coefficient, D_mean (ρ = -0.39, p &lt; 0.001). Network analysis revealed 41 intercorrelations between MMI and volume loss metrics, but SUV_mean remained a statistically significant predictor of volume loss in multivariate linear regression (p = 0.01). Significant correlations were also observed for SUV_mean in the validation cohort in both primary (ρ = 0.30, p = 0.02) and nodal (ρ = 0.31, p = 0.02) tumors.</p></div><div><h3>Conclusions</h3><p>Multiple pre-treatment imaging metrics were correlated with rapid nodal gross tumor volume loss during radiotherapy. FDG-PET SUV in particular exhibited significant correlations with volume regression across the two cohorts and in multivariate analysis.</p></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2405631624000733/pdfft?md5=9045d5a812efecba363adf39f4aa588f&pid=1-s2.0-S2405631624000733-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141481359","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":"Feasibility of simulation free abdominal stereotactic adaptive radiotherapy using an expedited pre-plan workflow","authors":"Alex T. Price ,&nbsp;Joshua P. Schiff ,&nbsp;Alice Silberstein ,&nbsp;Robbie Beckert ,&nbsp;Tianyu Zhao ,&nbsp;Geoffrey D. Hugo ,&nbsp;Pamela P. Samson ,&nbsp;Eric Laugeman ,&nbsp;Lauren E. Henke","doi":"10.1016/j.phro.2024.100611","DOIUrl":"10.1016/j.phro.2024.100611","url":null,"abstract":"<div><h3>Background and Purpose</h3><p>Improved hounsfield-unit accuracy of on-board imaging may lead to direct-to-unit treatment approaches We aimed to demonstrate the feasibility of using only a diagnostic (dx) computed tomography (CT)-defined target pre-plan in an <em>in silico</em> study of simulation-free abdominal stereotactic adaptive radiotherapy (ART).</p></div><div><h3>Materials and Methods</h3><p>Eight patients with abdominal treatment sites (five pancreatic cancer, three oligometastases) were treated using an integrated adaptive O-Ring gantry system. Each patient’s target was delineated on a dxCT. The target only pre-plan served primarily to seed the ART process. During the ART session, all structures were delineated. All simulated cases were treated to 50 Gy in 5 fractions to a planning target optimization structure (PTV_OPT) to allow for dose escalation within the planning target volume. Timing of steps during this workflow was recorded. Plan quality was compared between ART treatment plans and a plan created on a CT simulation scan using the traditional planning workflow.</p></div><div><h3>Results</h3><p>The workflow was feasible in all attempts, with organ-at-risk (OAR) constraints met in all fractions despite lack of initial OAR contours. Median absolute difference between the adapted plan and simulation CT plan for the PTV_Opt V95% was 2.0 %. Median absolute difference in the D0.5 cm³ between the adapted plan and simulation CT plan was −0.9 Gy for stomach, 1.2 Gy for duodenum, −5.3 Gy for small bowel, and 0.3 Gy for large bowel. Median end-to-end workflow time was 63 min.</p></div><div><h3>Conclusion</h3><p>The workflow was feasible for a dxCT-defined target-only pre-plan approach to stereotactic abdominal ART.</p></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2405631624000812/pdfft?md5=fb856b62ebccaf8ffa345fd98e38c826&pid=1-s2.0-S2405631624000812-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141705970","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":"Evaluation of magnetic resonance imaging derived synthetic computed tomography for proton therapy planning in prostate cancer","authors":"Kajsa M.L. Fridström ,&nbsp;René M. Winter ,&nbsp;Natalie Hornik ,&nbsp;Sigrun S. Almberg ,&nbsp;Signe Danielsen ,&nbsp;Kathrine R. Redalen","doi":"10.1016/j.phro.2024.100625","DOIUrl":"10.1016/j.phro.2024.100625","url":null,"abstract":"<div><h3>Background and purpose</h3><p>Magnetic resonance imaging (MRI)-only workflow is used in photon radiotherapy (RT) today, but not yet for protons. To bring MRI-only proton RT into clinical use, proton dose calculation on MRI-derived synthetic CT (sCT) must be validated. We evaluated proton dose calculation accuracy of prostate cancer proton plans using a commercially available sCT generator already validated for photon planning.</p></div><div><h3>Materials and methods</h3><p>The retrospective planning study included 10 prostate cancer patients who underwent MRI and planning CT (pCT) before RT. sCT were generated from the MRI with MRI Planner v2.3, and compared to pCT using structural mean absolute error (MAE). The pCT was used to create one-arc volumetric modulated arc therapy (VMAT) photon plan and two-field intensity modulated proton therapy (IMPT) proton plan. Each plan was recalculated on the sCT and compared to pCT doses. Dose volume histogram parameters, gamma analyses and range differences were evaluated.</p></div><div><h3>Results</h3><p>Median MAE for the body contour was 71 HU. Dose differences between pCT and sCT were small and similar for VMAT and IMPT plans. Median (range) gamma pass rates were lower for IMPT plans with 95.8 (89.3–98.7) % compared to VMAT plans with 99.4 (91.2–99.6) %. The proton range difference was 1.0 (interquartile range –0.1 – 0.2) mm deeper for sCT compared to the reference.</p></div><div><h3>Conclusion</h3><p>MRI-only IMPT planning for prostate cancer seems feasible in a clinical setting for the evaluated beam arrangement and sCT generator. More patients and evaluation of other beam arrangements are needed for a more general conclusion.</p></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2405631624000952/pdfft?md5=bdff56b24bab3515231eb6ae2a486b75&pid=1-s2.0-S2405631624000952-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141993841","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":"Comparison of image registration methods in patients with non-melanoma skin cancer treated with superficial brachytherapy","authors":"Marta Szlag,&nbsp;Magdalena Stankiewicz,&nbsp;Sylwia Kellas-Ślęczka,&nbsp;Małgorzata Stąpór-Fudzińska,&nbsp;Agnieszka Cholewka,&nbsp;Agnieszka Pruefer,&nbsp;Piotr Wojcieszek","doi":"10.1016/j.phro.2024.100631","DOIUrl":"10.1016/j.phro.2024.100631","url":null,"abstract":"<div><p>The accumulated dose from sequential treatments of metachronous non-melanoma skin cancer can be assessed using image registration, although guidelines for selecting the appropriate algorithm are lacking. This study shows the impact of rigid (RIR), deformable (DIR) and deformable structure-based (SDIR) algorithms on the skin dose. DIR increased: the maximum dose (39.2 Gy vs 9.4 Gy), the dose to 0.1 cm³ (16.4 Gy vs 7.8 Gy) and the dose to 2 cm³ (7.6 Gy vs 5.7 Gy). RIR only affected the maximum dose, which increased to 17.0 Gy. SDIR correctly translated the dose maps, as none of the parameters changed significantly.</p></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2405631624001015/pdfft?md5=f9df898248b65fa6251a71bb25161eb4&pid=1-s2.0-S2405631624001015-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142039670","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":"Histopathology-validated gross tumor volume delineations of intraprostatic lesions using PSMA-positron emission tomography/multiparametric magnetic resonance imaging","authors":"Josefine Grefve ,&nbsp;Karin Söderkvist ,&nbsp;Adalsteinn Gunnlaugsson ,&nbsp;Kristina Sandgren ,&nbsp;Joakim Jonsson ,&nbsp;Angsana Keeratijarut Lindberg ,&nbsp;Erik Nilsson ,&nbsp;Jan Axelsson ,&nbsp;Anders Bergh ,&nbsp;Björn Zackrisson ,&nbsp;Mathieu Moreau ,&nbsp;Camilla Thellenberg Karlsson ,&nbsp;Lars.E. Olsson ,&nbsp;Anders Widmark ,&nbsp;Katrine Riklund ,&nbsp;Lennart Blomqvist ,&nbsp;Vibeke Berg Loegager ,&nbsp;Sara N. Strandberg ,&nbsp;Tufve Nyholm","doi":"10.1016/j.phro.2024.100633","DOIUrl":"10.1016/j.phro.2024.100633","url":null,"abstract":"<div><h3>Background and purpose</h3><p>Dose escalation in external radiotherapy of prostate cancer shows promising results in terms of biochemical disease-free survival. Boost volume delineation guidelines are sparse which may cause high interobserver variability. The aim of this research was to characterize gross tumor volume (GTV) delineations based on multiparametric magnetic resonance imaging (mpMRI) and prostate specific membrane antigen-positron emission tomography (PSMA-PET) in relation to histopathology-validated Gleason grade 4 and 5 regions.</p></div><div><h3>Material and methods</h3><p>The study participants were examined with [⁶⁸Ga]PSMA-PET/mpMRI prior to radical prostatectomy. Four radiation oncologists delineated GTVs in 15 study participants, on four different image types; T2-weighted (T2w), diffusion weighted imaging (DWI), dynamic contrast enhanced (DCE) and PSMA-PET scans separately. The simultaneous truth and performance level estimation (STAPLE) algorithm was used to generate combined GTVs. GTVs were subsequently compared to histopathology. We analysed how Dice similarity coefficient (DSC) and lesion coverage are affected by using single versus multiple image types as well as by adding a clinical target volume (CTV) margin.</p></div><div><h3>Results</h3><p>Median DSC (STAPLE) for different GTVs varied between 0.33 and 0.52. GTV_{PSMA-PET/mpMRI} generated the highest median lesion coverage at 0.66. Combining different image types achieved similar lesion coverage as adding a CTV margin to contours from a single image type, while reducing non-malignant tissue inclusion within the target volume.</p></div><div><h3>Conclusion</h3><p>The combined use of mpMRI or PSMA-PET/mpMRI shows promise, achieving higher DSC and lesion coverage while minimizing non-malignant tissue inclusion, in comparison to the use of a single image type with an added CTV margin.</p></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2405631624001039/pdfft?md5=b71b9bd1ff863c1b10a65329734f1ed1&pid=1-s2.0-S2405631624001039-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142099479","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":"Data-driven gated positron emission tomography/computed tomography for radiotherapy","authors":"Tinsu Pan ,&nbsp;Dershan Luo","doi":"10.1016/j.phro.2024.100601","DOIUrl":"https://doi.org/10.1016/j.phro.2024.100601","url":null,"abstract":"<div><h3>Purpose</h3><p>Software-based data-driven gated (DDG) positron emission tomography/computed tomography (PET/CT) has replaced hardware-based 4D PET/CT. The purpose of this article was to review DDG PET/CT, which could improve the accuracy of treatment response assessment, tumor motion evaluation, and target tumor contouring with whole-body (WB) PET/CT for radiotherapy (RT).</p></div><div><h3>Material and methods</h3><p>This review covered the topics of 4D PET/CT with hardware gating, advancements in PET instrumentation, DDG PET, DDG CT, and DDG PET/CT based on a systematic literature review. It included a discussion of the large axial field-of-view (AFOV) PET detector and a review of the clinical results of DDG PET and DDG PET/CT.</p></div><div><h3>Results</h3><p>DDG PET matched or outperformed 4D PET with hardware gating. DDG CT was more compatible with DDG PET than 4D CT, which required hardware gating. DDG CT could replace 4D CT for RT. DDG PET and DDG CT for DDG PET/CT can be incorporated in a WB PET/CT of less than 15 min scan time on a PET/CT scanner of at least 25 cm AFOV PET detector.</p></div><div><h3>Conclusions</h3><p>DDG PET/CT could correct the misregistration and tumor motion artifacts in a WB PET/CT and provide the quantitative PET and tumor motion information of a registered PET/CT for RT.</p></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S240563162400071X/pdfft?md5=6ec4d7c81437ba1f40c849fbbb9ed997&pid=1-s2.0-S240563162400071X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141481356","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":"Target coverage and organs at risk dose in hypofractionated salvage radiotherapy after prostatectomy","authors":"Floor H.E. Staal,&nbsp;Jorinde Janssen,&nbsp;Sajee Krishnapillai,&nbsp;Johannes A. Langendijk,&nbsp;Stefan Both,&nbsp;Charlotte L. Brouwer,&nbsp;Shafak Aluwini","doi":"10.1016/j.phro.2024.100600","DOIUrl":"https://doi.org/10.1016/j.phro.2024.100600","url":null,"abstract":"<div><h3>Background and purpose</h3><p>Introducing moderately hypofractionated salvage radiotherapy (SRT) following prostatectomy obligates investigation of its effects on clinical target volume (CTV) coverage and organ-at-risk (OAR) doses. This study assessed interfractional volume and dose changes in OARs and CTV in moderately hypofractionated SRT and evaluated the 8-mm planning target volume (PTV) margin.</p></div><div><h3>Materials and methods</h3><p>Twenty patients from the PERYTON-trial were included; 10 received conventional SRT (35 × 2 Gy) and 10 hypofractionated SRT (20 × 3 Gy). OARs were delineated on 539 pre-treatment Cone Beam CT (CBCT) scans to compare interfractional OAR volume changes. CTVs for the hypofractionated group were delineated on 199 CBCTs. Dose distributions with 4 and 6 mm PTV margins were generated using voxel-wise minimum robustness evaluation of the original 8-mm PTV plan, and dose changes were assessed.</p></div><div><h3>Results</h3><p>Median volume changes for bladder and rectum were −26 % and −10 %, respectively. OAR volume changes were not significantly different between the two treatment schedules. The 8-mm PTV margin ensured optimal coverage for prostate bed and vesicle bed CTV (V95 = 100 % in &gt;97 % fractions). However, bladder V60 &lt;25 % was not achieved in 5 % of fractions, and rectum V60 &lt;5 % was unmet in 33 % of fractions. A 6-mm PTV margin resulted in CTV V95 = 100 % in 92 % of fractions for prostate bed, and in 86 % for vesicle bed CTV.</p></div><div><h3>Conclusions</h3><p>Moderately hypofractionated SRT yielded comparable OAR volume changes to conventionally fractionated SRT. Interfractional changes remained acceptable with a PTV margin of 6 mm for prostate bed and 8 mm for vesicle bed.</p></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2405631624000708/pdfft?md5=132a0a691b8570ae9bf8ccaf6ecd72ea&pid=1-s2.0-S2405631624000708-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141479446","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 comparative analysis of preclinical computed tomography radiomics using cone-beam and micro-computed tomography scanners","authors":"Kathryn H. Brown ,&nbsp;Brianna N. Kerr ,&nbsp;Mihaela Pettigrew ,&nbsp;Kate Connor ,&nbsp;Ian S. Miller ,&nbsp;Liam Shiels ,&nbsp;Colum Connolly ,&nbsp;Conor K. McGarry ,&nbsp;Annette T. Byrne ,&nbsp;Karl T. Butterworth","doi":"10.1016/j.phro.2024.100615","DOIUrl":"10.1016/j.phro.2024.100615","url":null,"abstract":"<div><h3>Background and purpose</h3><p>Radiomics analysis extracts quantitative data (features) from medical images. These features could potentially reflect biological characteristics and act as imaging biomarkers within precision medicine. However, there is a lack of cross-comparison and validation of radiomics outputs which is paramount for clinical implementation. In this study, we compared radiomics outputs across two computed tomography (CT)-based preclinical scanners.</p></div><div><h3>Materials and methods</h3><p>Cone beam CT (CBCT) and µCT scans were acquired using different preclinical CT imaging platforms. The reproducibility of radiomics features on each scanner was assessed using a phantom across imaging energies (40 &amp; 60 kVp) and segmentation volumes (44–238 mm³). Retrospective mouse scans were used to compare feature reliability across varying tissue densities (lung, heart, bone), scanners and after voxel size harmonisation. Reliable features had an intraclass correlation coefficient (ICC) &gt; 0.8.</p></div><div><h3>Results</h3><p>First order and GLCM features were the most reliable on both scanners across different volumes. There was an inverse relationship between tissue density and feature reliability, with the highest number of features in lung (CBCT=580, µCT=734) and lowest in bone (CBCT=110, µCT=560). Comparable features for lung and heart tissues increased when voxel sizes were harmonised. We have identified tissue-specific preclinical radiomics signatures in mice for the lung (133), heart (35), and bone (15).</p></div><div><h3>Conclusions</h3><p>Preclinical CBCT and µCT scans can be used for radiomics analysis to support the development of meaningful radiomics signatures. This study demonstrates the importance of standardisation and emphasises the need for multi-centre studies.</p></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S240563162400085X/pdfft?md5=b221bc4589295353c2252f604eaea120&pid=1-s2.0-S240563162400085X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141853630","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 planning study of proton therapy dose escalation for non-small cell lung cancer","authors":"Arno C. Hessels,&nbsp;Sabine Visser,&nbsp;Stefan Both,&nbsp;Erik W. Korevaar,&nbsp;Johannes A. Langendijk,&nbsp;Robin Wijsman","doi":"10.1016/j.phro.2024.100616","DOIUrl":"10.1016/j.phro.2024.100616","url":null,"abstract":"<div><p>In non-small-cell lung cancer (NSCLC), improving local control through radiotherapy dose escalation might improve survival. However, a photon-based RCT showed increased organ at risk dose exposure and worse overall survival in the dose escalation arm. In this study, intensity-modulated proton therapy plans with dose escalation to the primary tumour were created for 20 NSCLC patients. The mediastinal envelope was delineated to spare structures around the heart. It was possible to increase primary tumour dose up to 74.0 Gy without a significant increase in organ at risk doses and predicted toxicity.</p></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2405631624000861/pdfft?md5=764652d67f19ea096c13b4f9e1994df2&pid=1-s2.0-S2405631624000861-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141840896","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":"Robustness of radiomics features on 0.35 T magnetic resonance imaging for magnetic resonance-guided radiotherapy","authors":"Morgan Michalet ,&nbsp;Gladis Valenzuela ,&nbsp;Pierre Debuire ,&nbsp;Olivier Riou ,&nbsp;David Azria ,&nbsp;Stéphanie Nougaret ,&nbsp;Marion Tardieu","doi":"10.1016/j.phro.2024.100613","DOIUrl":"10.1016/j.phro.2024.100613","url":null,"abstract":"<div><h3>Background and purpose</h3><p>MR-guided radiotherapy adds the precision of magnetic resonance imaging (MRI) to the therapeutic benefits of a linear accelerator. Prior to each therapeutic session, an MRI generates a significant volume of imaging data ripe for analysis. Radiomics stands at the forefront of medical imaging and oncology research, dedicated to mining quantitative imaging attributes to forge predictive models. However, the robustness of these models is often challenged.</p></div><div><h3>Materials and methods</h3><p>To assess the robustness of feature extraction, we conducted reproducibility studies using a 0.35 T MR-linac system, employing both a specialized phantom and patient-derived images, focusing on cases of pancreatic cancer. We extracted shape-based, first-order and textural features from patient-derived images and only first-order and textural features from phantom-derived images. The impact of the delay between simulation and first fraction images was also assessed with an equivalence test.</p></div><div><h3>Results</h3><p>From 107 features evaluated, 58 (54 %) were considered as non-reproducible: 18 were uniformly inconsistent across both phantom and patient images, 9 were specific to phantom-based analysis, and 31 to patient-derived data.</p></div><div><h3>Conclusion</h3><p>Our findings show that a significant proportion of radiomic features extracted from this dual dataset were unreliable. It is essential to discard these non-reproducible elements to refine and enhance radiomic model development, particularly for MR-guided radiotherapy in pancreatic cancer.</p></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2405631624000836/pdfft?md5=a1d7bc7fab2c42024091aef306d09d95&pid=1-s2.0-S2405631624000836-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141842813","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}