Pub Date : 2025-01-01Epub Date: 2024-12-26DOI: 10.1016/j.ejmp.2024.104861
Christian Petrich, Johanna Winter, Anton Dimroth, Jan J Wilkens, Stefan Bartzsch
Purpose: Microbeam radiation therapy (MRT) has shown superior healthy tissue sparing at equal tumour control probabilities compared to conventional radiation therapy in many preclinical studies. The limitation to preclinical research arises from a lack of suitable radiation sources for clinical application of MRT due to high demands on beam quality. To overcome these limitations, we developed and built the first prototype of a line-focus X-ray tube (LFXT). During commissioning, characterisation of the X-ray focal spot is necessary. For the generation of microbeams, we require a specially designed collimator adapted to the LFXT.
Methods: We present an adapted edge method and a pinhole method for focal spot measurements of the LFXT prototype as well as the design of the microbeam collimator with a slit width of 50μm, spaced by 400μm. Monte Carlo simulations validated the focal spot measurement techniques and the design of the collimator.
Results: We showed that the adapted edge method is more complex but superior to the adapted pinhole method in terms of quantitative validity. Simulations for the microbeam collimator showed a sharp microbeam dose profile with a peak-to-valley dose ratio (PVDR) above 23 throughout 50 mm of water.
Conclusion: During commissioning, the adapted focal spot visualisation methods will be used to determine the focal spot dimensions and to optimise machine parameters. The LFXT prototype will enable preclinical MRT with significantly higher dose rates than any other compact MRT source and will pave the way for the first clinical trials in a hospital setting.
{"title":"The compact line-focus X-ray tube for microbeam radiation therapy - Focal spot characterisation and collimator design.","authors":"Christian Petrich, Johanna Winter, Anton Dimroth, Jan J Wilkens, Stefan Bartzsch","doi":"10.1016/j.ejmp.2024.104861","DOIUrl":"10.1016/j.ejmp.2024.104861","url":null,"abstract":"<p><strong>Purpose: </strong>Microbeam radiation therapy (MRT) has shown superior healthy tissue sparing at equal tumour control probabilities compared to conventional radiation therapy in many preclinical studies. The limitation to preclinical research arises from a lack of suitable radiation sources for clinical application of MRT due to high demands on beam quality. To overcome these limitations, we developed and built the first prototype of a line-focus X-ray tube (LFXT). During commissioning, characterisation of the X-ray focal spot is necessary. For the generation of microbeams, we require a specially designed collimator adapted to the LFXT.</p><p><strong>Methods: </strong>We present an adapted edge method and a pinhole method for focal spot measurements of the LFXT prototype as well as the design of the microbeam collimator with a slit width of 50μm, spaced by 400μm. Monte Carlo simulations validated the focal spot measurement techniques and the design of the collimator.</p><p><strong>Results: </strong>We showed that the adapted edge method is more complex but superior to the adapted pinhole method in terms of quantitative validity. Simulations for the microbeam collimator showed a sharp microbeam dose profile with a peak-to-valley dose ratio (PVDR) above 23 throughout 50 mm of water.</p><p><strong>Conclusion: </strong>During commissioning, the adapted focal spot visualisation methods will be used to determine the focal spot dimensions and to optimise machine parameters. The LFXT prototype will enable preclinical MRT with significantly higher dose rates than any other compact MRT source and will pave the way for the first clinical trials in a hospital setting.</p>","PeriodicalId":56092,"journal":{"name":"Physica Medica-European Journal of Medical Physics","volume":"129 ","pages":"104861"},"PeriodicalIF":3.3,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142900585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Background and purpose: Free-breathing computed tomography (FBCT) used in treatment planning for lower thoracic (Th8-Th12) spine stereotactic body radiotherapy (SBRT) can cause deviations between planned and irradiated doses due to diaphragm movement (DM). This study analyzed the dosimetric impact of DM on lower thoracic spine SBRT.
Materials and methods: Data were collected from 19 patients who underwent FBCT and four-dimensional CT (4DCT) during the same session. The 4DCT data were divided into ten respiratory phases (0-90%), and an average CT (AveCT) was reconstructed from them. Using FBCT, target and normal tissues near the diaphragm were contoured and spine SBRT plans with 24-Gy doses in two fractions were created. These plans were applied to each phase of CT and AveCT, with doses recalculated using the same parameters. Actual treatment doses (Deformed AveCT) were estimated by accumulating doses across each 4DCT phase using deformable image registration on the AveCT. Dose-volume histogram (DVH) indices were compared between the FBCT, AveCT, 0% phase, 50% phase, and Deformed AveCT plans.
Results: The mean differences in DVH indices for target and normal tissues were within 2.4 and 2.1%, respectively, when the diaphragm displacement was between -1.6 cm and 2.0 cm, as compared with FBCT. DM displacement showed moderate to strong correlations with DVH differences.
Conclusion: Our results indicate that DM has a minor impact on DVH indices if the diaphragm remains within 1.5 cm of the FBCT position.
{"title":"Impact of diaphragm motion on dosimetry in lower thoracic spine stereotactic body radiotherapy.","authors":"Kohei Kawata, Hideaki Hirashima, Manabu Nakata, Takahiro Fujimoto, Rihito Aizawa, Takashi Mizowaki","doi":"10.1016/j.ejmp.2024.104886","DOIUrl":"10.1016/j.ejmp.2024.104886","url":null,"abstract":"<p><strong>Background and purpose: </strong>Free-breathing computed tomography (FBCT) used in treatment planning for lower thoracic (Th8-Th12) spine stereotactic body radiotherapy (SBRT) can cause deviations between planned and irradiated doses due to diaphragm movement (DM). This study analyzed the dosimetric impact of DM on lower thoracic spine SBRT.</p><p><strong>Materials and methods: </strong>Data were collected from 19 patients who underwent FBCT and four-dimensional CT (4DCT) during the same session. The 4DCT data were divided into ten respiratory phases (0-90%), and an average CT (AveCT) was reconstructed from them. Using FBCT, target and normal tissues near the diaphragm were contoured and spine SBRT plans with 24-Gy doses in two fractions were created. These plans were applied to each phase of CT and AveCT, with doses recalculated using the same parameters. Actual treatment doses (Deformed AveCT) were estimated by accumulating doses across each 4DCT phase using deformable image registration on the AveCT. Dose-volume histogram (DVH) indices were compared between the FBCT, AveCT, 0% phase, 50% phase, and Deformed AveCT plans.</p><p><strong>Results: </strong>The mean differences in DVH indices for target and normal tissues were within 2.4 and 2.1%, respectively, when the diaphragm displacement was between -1.6 cm and 2.0 cm, as compared with FBCT. DM displacement showed moderate to strong correlations with DVH differences.</p><p><strong>Conclusion: </strong>Our results indicate that DM has a minor impact on DVH indices if the diaphragm remains within 1.5 cm of the FBCT position.</p>","PeriodicalId":56092,"journal":{"name":"Physica Medica-European Journal of Medical Physics","volume":"129 ","pages":"104886"},"PeriodicalIF":3.3,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142928653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01Epub Date: 2024-12-31DOI: 10.1016/j.ejmp.2024.104887
Valeria Landoni, Sara Broggi, Marcello Serra, Raffaella Doro, Anna Stefania Martinotti, Irene Redaelli, Maria Cristina Frassanito, Carmelo Siragusa, Elena De Martin, Antonella Soriani, Alessia Tudda, Roberta Castriconi, Antonella Del Vecchio, Laura Masi, Claudio Fiorino
Purpose: This study analyzed inter-institute conformity and dose gradient variability of CyberKnife (CK) brain SRS/SRT plans. The feasibility of multi-center predictive models was investigated, aiming at guided/automated planning optimization.
Methods: Data from 335 clinical plans, delivered for single lesions in 1-5 fractions, were collected by 8 CK centers. Conformity index (CI), Dose Gradient Index (DGI) and the effective radii defined by different isodose volumes (Reff) were computed. Predictability of dose fall-off from PTV dimensions was analyzed. DGI average, 80th and 10thpercentile values were evaluated stratifying plans by PTV size into six groups. Linear regression models were created for Reff as a function of PTV equivalent radius.
Results: CI values (range 0.96---2.23) exceeded 1.20 in 88/335 plans, mostly (65 %) collected in 2 of the participating centers. DGI showed an acceptable inter-institute variability and a strong significant correlation (p < 0.0001) with PTV. Ideal and Minimal DGI for each of the six groups were respectively 95 (86), 82 (73), 77 (68), 71 (60), 59 (43) and 50 (29). The rate of DGI values passing the multicenter minimal criteria, considering each center separately, varied from 43 % to 100 %. R2values for the regression between Reff and PTV radius were ≥ 0.958, showing an increasing inter-center variability for decreasing isodose values.
Conclusion: Observed inter-center differences enhanced the advantages of a multi-institute approach. Multicenter predictive models for dose fall-off in CK brain SR/SRT planning are feasible and easy to use. Reff models and DGI analysis may permit to partially automate planning optimization avoiding creation of suboptimal plans.
{"title":"Multicenter approach to predict plan quality of robotic intracranial SRS/SRT.","authors":"Valeria Landoni, Sara Broggi, Marcello Serra, Raffaella Doro, Anna Stefania Martinotti, Irene Redaelli, Maria Cristina Frassanito, Carmelo Siragusa, Elena De Martin, Antonella Soriani, Alessia Tudda, Roberta Castriconi, Antonella Del Vecchio, Laura Masi, Claudio Fiorino","doi":"10.1016/j.ejmp.2024.104887","DOIUrl":"10.1016/j.ejmp.2024.104887","url":null,"abstract":"<p><strong>Purpose: </strong>This study analyzed inter-institute conformity and dose gradient variability of CyberKnife (CK) brain SRS/SRT plans. The feasibility of multi-center predictive models was investigated, aiming at guided/automated planning optimization.</p><p><strong>Methods: </strong>Data from 335 clinical plans, delivered for single lesions in 1-5 fractions, were collected by 8 CK centers. Conformity index (CI), Dose Gradient Index (DGI) and the effective radii defined by different isodose volumes (Reff) were computed. Predictability of dose fall-off from PTV dimensions was analyzed. DGI average, 80th and 10<sup>th</sup>percentile values were evaluated stratifying plans by PTV size into six groups. Linear regression models were created for Reff as a function of PTV equivalent radius.</p><p><strong>Results: </strong>CI values (range 0.96---2.23) exceeded 1.20 in 88/335 plans, mostly (65 %) collected in 2 of the participating centers. DGI showed an acceptable inter-institute variability and a strong significant correlation (p < 0.0001) with PTV. Ideal and Minimal DGI for each of the six groups were respectively 95 (86), 82 (73), 77 (68), 71 (60), 59 (43) and 50 (29). The rate of DGI values passing the multicenter minimal criteria, considering each center separately, varied from 43 % to 100 %. R<sup>2</sup>values for the regression between Reff and PTV radius were ≥ 0.958, showing an increasing inter-center variability for decreasing isodose values.</p><p><strong>Conclusion: </strong>Observed inter-center differences enhanced the advantages of a multi-institute approach. Multicenter predictive models for dose fall-off in CK brain SR/SRT planning are feasible and easy to use. Reff models and DGI analysis may permit to partially automate planning optimization avoiding creation of suboptimal plans.</p>","PeriodicalId":56092,"journal":{"name":"Physica Medica-European Journal of Medical Physics","volume":"129 ","pages":"104887"},"PeriodicalIF":3.3,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142916393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Objectives: The purpose of this study was to investigate the fundamental properties of spot-scanning proton beams and compare them to Monte Carlo (MC) simulations, both with and without CT calibration, using spatially diverse combinations of materials.
Methods: A heterogeneous phantom was created by spatially distributing titanium, wax, and thermocol to generate six scenarios of heterogeneous combinations. Proton pencil beams ranging in energy from 100 to 226.2 MeV were directed perpendicular to each heterogeneous combination, and the exit proton was measured using a Lynx scintillation detector and a Zebra Multi-Layer-Ionization-Chamber for depth dose and spot profile measurements, respectively. The identical measurement configuration was duplicated in the RayStation-TPS. The measured and simulated RayStation-MC beam characteristics were compared.
Results: The results showed that at 100 MeV, the mean standard deviation of spot size was 5.66 ± 0.27 mm, while at 226.2 MeV, it rapidly decreased to 3.37 ± 0.07 mm. The physical phantom showed a larger perturbation difference between measurement and MC simulation than the virtual phantom. MC overestimates ranges up to 1.5 % in virtual phantoms, but underestimates ranges up to 5 % in physical phantoms. Range perturbations over 1 mm occurred in 35.7 % of virtual phantom measurements and in 85.7 % of physical phantom measurements.
Conclusions: Despite using a CT artefact reduction approach and an accurate Monte-Carlo dose calculation algorithm, perturbations in proton characteristics were still observed. It is essential to be aware of the limits of the TPS in managing such heterogeneous combinations. It is recommended to perform more validation checks on heterogeneous combinations than on individual materials.
{"title":"Influence of spatial redistribution of heterogeneities in proton beam characteristics.","authors":"Manikandan Arjunan, Dayananda Sharma Shamurailatpam, Kartikeswar Ch Patro, Suryakant Kaushik, Ganapathy Krishnan","doi":"10.1016/j.ejmp.2024.104882","DOIUrl":"10.1016/j.ejmp.2024.104882","url":null,"abstract":"<p><strong>Objectives: </strong>The purpose of this study was to investigate the fundamental properties of spot-scanning proton beams and compare them to Monte Carlo (MC) simulations, both with and without CT calibration, using spatially diverse combinations of materials.</p><p><strong>Methods: </strong>A heterogeneous phantom was created by spatially distributing titanium, wax, and thermocol to generate six scenarios of heterogeneous combinations. Proton pencil beams ranging in energy from 100 to 226.2 MeV were directed perpendicular to each heterogeneous combination, and the exit proton was measured using a Lynx scintillation detector and a Zebra Multi-Layer-Ionization-Chamber for depth dose and spot profile measurements, respectively. The identical measurement configuration was duplicated in the RayStation-TPS. The measured and simulated RayStation-MC beam characteristics were compared.</p><p><strong>Results: </strong>The results showed that at 100 MeV, the mean standard deviation of spot size was 5.66 ± 0.27 mm, while at 226.2 MeV, it rapidly decreased to 3.37 ± 0.07 mm. The physical phantom showed a larger perturbation difference between measurement and MC simulation than the virtual phantom. MC overestimates ranges up to 1.5 % in virtual phantoms, but underestimates ranges up to 5 % in physical phantoms. Range perturbations over 1 mm occurred in 35.7 % of virtual phantom measurements and in 85.7 % of physical phantom measurements.</p><p><strong>Conclusions: </strong>Despite using a CT artefact reduction approach and an accurate Monte-Carlo dose calculation algorithm, perturbations in proton characteristics were still observed. It is essential to be aware of the limits of the TPS in managing such heterogeneous combinations. It is recommended to perform more validation checks on heterogeneous combinations than on individual materials.</p>","PeriodicalId":56092,"journal":{"name":"Physica Medica-European Journal of Medical Physics","volume":"129 ","pages":"104882"},"PeriodicalIF":3.3,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142928656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-21DOI: 10.1016/j.ejmp.2024.104880
J Garcia Perez-Schofield, C Gutierrez Mendiguchia, A Gomez Casal, A Fernandez Diaz, S Lorenzo Martinez, M Pequeño Gonzalez
{"title":"Corrigendum to \"PS10.16 ACTIVITY IN THE SALIVA OF rhTSH AND THW THYROID CANCER PATIENTS TREATED WITH IODINE-131\" [Phys. Med. 125(Supplement 1) (2024) 104229].","authors":"J Garcia Perez-Schofield, C Gutierrez Mendiguchia, A Gomez Casal, A Fernandez Diaz, S Lorenzo Martinez, M Pequeño Gonzalez","doi":"10.1016/j.ejmp.2024.104880","DOIUrl":"https://doi.org/10.1016/j.ejmp.2024.104880","url":null,"abstract":"","PeriodicalId":56092,"journal":{"name":"Physica Medica-European Journal of Medical Physics","volume":" ","pages":"104880"},"PeriodicalIF":3.3,"publicationDate":"2024-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142873584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-01DOI: 10.1016/j.ejmp.2024.104838
F. Nicolanti , B. Caccia , A. Cartoni , D. Emfietzoglou , R. Faccini , S. Incerti , I. Kyriakou , M. Satta , H.N. Tran , C. Mancini-Terracciano
Background and aim:
Cosmic rays have the potential to induce significant changes in atmospheric chemical reactions by generating ions, thereby influencing the atmosphere’s chemical composition. The use of particle–molecule interaction models that account for the molecular structure of the atmospheric medium can advance our understanding on the role of ions, and enables a quantitative analysis of the impact of ion-molecule reactions on atmospheric modifications. This study marks the initial effort to expand the Geant-DNA toolkit for atmospheric applications.
Methods:
Building on our previous work, we extended the validation of new electron impact interaction models with the nitrogen and oxygen molecules up to 10 MeV. Additionally, we introduce electron cross sections for the carbon dioxide molecule, due to its crucial role as a major greenhouse gas. We present the implementation of the cross section models in Geant4-DNA, along with their validation through simulations of stopping power and range.
Results:
The differential cross sections have been verified against analytical calculations, demonstrating good agreement with existing literature data for all three molecules. The implementation has been validated through simulations of stopping power and range in N, O, CO, and . Results demonstrate agreement within 6% compared to reference data from the ESTAR database.
Conclusions:
The cross section models for the N, O, and CO atmospheric molecules have been implemented in the Geant4-DNA toolkit. This evolution is crucial for studying ionic reactive chemical networks in a quantitative manner, assessing the impact of ionization on chemical reactions occurring in the atmosphere and their implications for climate.
{"title":"Geant4-DNA development for atmospheric applications: N2, O2 and CO2 models implementation","authors":"F. Nicolanti , B. Caccia , A. Cartoni , D. Emfietzoglou , R. Faccini , S. Incerti , I. Kyriakou , M. Satta , H.N. Tran , C. Mancini-Terracciano","doi":"10.1016/j.ejmp.2024.104838","DOIUrl":"10.1016/j.ejmp.2024.104838","url":null,"abstract":"<div><h3>Background and aim:</h3><div>Cosmic rays have the potential to induce significant changes in atmospheric chemical reactions by generating ions, thereby influencing the atmosphere’s chemical composition. The use of particle–molecule interaction models that account for the molecular structure of the atmospheric medium can advance our understanding on the role of ions, and enables a quantitative analysis of the impact of ion-molecule reactions on atmospheric modifications. This study marks the initial effort to expand the Geant-DNA toolkit for atmospheric applications.</div></div><div><h3>Methods:</h3><div>Building on our previous work, we extended the validation of new electron impact interaction models with the nitrogen and oxygen molecules up to 10 MeV. Additionally, we introduce electron cross sections for the carbon dioxide molecule, due to its crucial role as a major greenhouse gas. We present the implementation of the cross section models in Geant4-DNA, along with their validation through simulations of stopping power and range.</div></div><div><h3>Results:</h3><div>The differential cross sections have been verified against analytical calculations, demonstrating good agreement with existing literature data for all three molecules. The implementation has been validated through simulations of stopping power and range in N<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span>, O<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span>, CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span>, and <span><math><mrow><mi>a</mi><mi>i</mi><mi>r</mi></mrow></math></span>. Results demonstrate agreement within 6% compared to reference data from the ESTAR database.</div></div><div><h3>Conclusions:</h3><div>The cross section models for the N<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span>, O<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span>, and CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> atmospheric molecules have been implemented in the Geant4-DNA toolkit. This evolution is crucial for studying ionic reactive chemical networks in a quantitative manner, assessing the impact of ionization on chemical reactions occurring in the atmosphere and their implications for climate.</div></div>","PeriodicalId":56092,"journal":{"name":"Physica Medica-European Journal of Medical Physics","volume":"128 ","pages":"Article 104838"},"PeriodicalIF":3.3,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142745766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-01DOI: 10.1016/j.ejmp.2024.104863
Suresh Rana, Noufal Manthala Padannayil, Youssef Zeidan, Shyam Pokharel, Samuel Richter, Michael Kasper, Hina Saeed
Purpose
This study aims to compare the dosimetric impact of incorporating systematic and random setup uncertainties in the robust optimization of head and neck cancer (HNC) Intensity Modulated Proton Therapy (IMPT) plans.
Methods
Bilateral HNC patients (n = 10) previously treated with conventional photon therapy at our institution were included. Both systematic and random setup uncertainties were incorporated into the robust optimization process of IMPT planning. Dosimetric comparisons were made between plans optimized with systematic (IMPT-S) versus random (IMPT-R) setup uncertainties, assessing both the clinical target volume (CTVs) and organs at risk (OARs) across various dosimetric metrics. Both plans applied a fixed range uncertainty of ± 3 % and a maximum setup uncertainty of ± 3 mm.
Results
Both IMPT-S and IMPT-R plans achieved similar target coverage, meeting robustness criteria for CTVs. On average, the D95% voxel-wise min to the high-risk CTV (CTV_HR) was slightly higher in IMPT-S plans by 1.78 ± 0.72 % compared to IMPT-R plans. However, IMPT-R plans provided better OAR sparing, which was evident in both nominal and voxel-wise maximum values. While random setup errors in robust optimization improved OAR sparing, the clinical impact may be minimal where OAR doses are already well below tolerance levels.
Conclusion
Both IMPT-S and IMPT-R techniques met the robustness criteria for CTVs in HNC IMPT planning. Incorporating random setup uncertainties in robust optimization improves OAR sparing compared to systematic setup uncertainties. Further research is needed to explore the broader applicability of random setup errors and to integrate random uncertainties in robustness evaluations for a more comprehensive assessment of treatment plans.
{"title":"Exploring the dosimetric impact of systematic and random setup uncertainties in robust optimization of head and neck IMPT plans","authors":"Suresh Rana, Noufal Manthala Padannayil, Youssef Zeidan, Shyam Pokharel, Samuel Richter, Michael Kasper, Hina Saeed","doi":"10.1016/j.ejmp.2024.104863","DOIUrl":"10.1016/j.ejmp.2024.104863","url":null,"abstract":"<div><h3>Purpose</h3><div>This study aims to compare the dosimetric impact of incorporating systematic and random setup uncertainties in the robust optimization of head and neck cancer (HNC) Intensity Modulated Proton Therapy (IMPT) plans.</div></div><div><h3>Methods</h3><div>Bilateral HNC patients (n = 10) previously treated with conventional photon therapy at our institution were included. Both systematic and random setup uncertainties were incorporated into the robust optimization process of IMPT planning. Dosimetric comparisons were made between plans optimized with systematic (IMPT-S) versus random (IMPT-R) setup uncertainties, assessing both the clinical target volume (CTVs) and organs at risk (OARs) across various dosimetric metrics. Both plans applied a fixed range uncertainty of ± 3 % and a maximum setup uncertainty of ± 3 mm.</div></div><div><h3>Results</h3><div>Both IMPT-S and IMPT-R plans achieved similar target coverage, meeting robustness criteria for CTVs. On average, the D<sub>95%</sub> voxel-wise min to the high-risk CTV (CTV_HR) was slightly higher in IMPT-S plans by 1.78 ± 0.72 % compared to IMPT-R plans. However, IMPT-R plans provided better OAR sparing, which was evident in both nominal and voxel-wise maximum values. While random setup errors in robust optimization improved OAR sparing, the clinical impact may be minimal where OAR doses are already well below tolerance levels.</div></div><div><h3>Conclusion</h3><div>Both IMPT-S and IMPT-R techniques met the robustness criteria for CTVs in HNC IMPT planning. Incorporating random setup uncertainties in robust optimization improves OAR sparing compared to systematic setup uncertainties. Further research is needed to explore the broader applicability of random setup errors and to integrate random uncertainties in robustness evaluations for a more comprehensive assessment of treatment plans.</div></div>","PeriodicalId":56092,"journal":{"name":"Physica Medica-European Journal of Medical Physics","volume":"128 ","pages":"Article 104863"},"PeriodicalIF":3.3,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142745767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-01DOI: 10.1016/j.ejmp.2024.104850
Yoshi-hide Sato , Dousatsu Sakata , David Bolst , Edward C. Simpson , Andrew Chacon , Mitra Safavi-Naeini , Susanna Guatelli , Akihiro Haga
Purpose:
This study aims to validate the Light-Ion Quantum Molecular Dynamics (LIQMD) model, an advanced version of the QMD model for more accurate simulations in hadron therapy, incorporated into Geant4 (release 11.2).
Methods:
Two sets of experiments are employed. The first includes positron-emitter distributions along the beam path for 350 MeV/u 12C ions incident on a PMMA target, obtained from in–vivo Positron Emission Tomography (PET) experiments at QST (Chiba, Japan). The second comprises cross-sections for 95 MeV/u 12C ions incident on thin targets (H, C, O, Al, and Ti), obtained from experiments at GANIL (Caen, France). The LIQMD model’s performance is compared with the experimental data and the default QMD model results.
Results:
The LIQMD model can predict the profile shape of positron-emitting radionuclide yields with better accuracy than the default QMD model, although some discrepancies remains. The consistency observed in the production of positron-emitting radionuclides aligns with the thin target cross-section analysis. The LIQMD model significantly improves the differential and double-differential cross-sections of fragments produced in thin targets, especially in the forward direction. The overestimation of 10C production in the in–vivo PET benchmark is consistent with the 95 MeV/u 12C cross-section test. Overall, the LIQMD model demonstrates better agreement with experimental measurements for nearly all fragment species compared to the QMD model.
Conclusions:
The LIQMD model offers an improved description of the fragmentation process in hadron therapy. Future work should involve further validation against additional experimental measurements to confirm these findings.
{"title":"Validation of Light–Ion Quantum Molecular Dynamics (LIQMD) model for hadron therapy","authors":"Yoshi-hide Sato , Dousatsu Sakata , David Bolst , Edward C. Simpson , Andrew Chacon , Mitra Safavi-Naeini , Susanna Guatelli , Akihiro Haga","doi":"10.1016/j.ejmp.2024.104850","DOIUrl":"10.1016/j.ejmp.2024.104850","url":null,"abstract":"<div><h3>Purpose:</h3><div>This study aims to validate the Light-Ion Quantum Molecular Dynamics (LIQMD) model, an advanced version of the QMD model for more accurate simulations in hadron therapy, incorporated into Geant4 (release 11.2).</div></div><div><h3>Methods:</h3><div>Two sets of experiments are employed. The first includes positron-emitter distributions along the beam path for 350 MeV/u <sup>12</sup>C ions incident on a PMMA target, obtained from in–vivo Positron Emission Tomography (PET) experiments at QST (Chiba, Japan). The second comprises cross-sections for 95 MeV/u <sup>12</sup>C ions incident on thin targets (H, C, O, Al, and Ti), obtained from experiments at GANIL (Caen, France). The LIQMD model’s performance is compared with the experimental data and the default QMD model results.</div></div><div><h3>Results:</h3><div>The LIQMD model can predict the profile shape of positron-emitting radionuclide yields with better accuracy than the default QMD model, although some discrepancies remains. The consistency observed in the production of positron-emitting radionuclides aligns with the thin target cross-section analysis. The LIQMD model significantly improves the differential and double-differential cross-sections of fragments produced in thin targets, especially in the forward direction. The overestimation of <sup>10</sup>C production in the in–vivo PET benchmark is consistent with the 95 MeV/u <sup>12</sup>C cross-section test. Overall, the LIQMD model demonstrates better agreement with experimental measurements for nearly all fragment species compared to the QMD model.</div></div><div><h3>Conclusions:</h3><div>The LIQMD model offers an improved description of the fragmentation process in hadron therapy. Future work should involve further validation against additional experimental measurements to confirm these findings.</div></div>","PeriodicalId":56092,"journal":{"name":"Physica Medica-European Journal of Medical Physics","volume":"128 ","pages":"Article 104850"},"PeriodicalIF":3.3,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142745765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-25DOI: 10.1016/j.ejmp.2024.104859
Richárd Elek , Levente Herényi , Marcell Gyánó , Balázs Nemes , Szabolcs Osváth
Objective
By modelling patient exposures of interventional procedures, this study compares the reduction of radiation detriment between Digital Variance Angiography (DVA) and Digital Subtraction Angiography (DSA).
Methods
The paper presents a retrospective risk assessment using an in-house developed tool on 107 patient exposures from a clinical trial of DVA used to diagnose peripheral arterial disease (PAD). DICOM exposure parameters were used to initiate the PENELOPE (PENetration and Energy LOss of Positrons and Electrons) Monte Carlo simulation, radiation quality and quantity, and irradiation geometry. The effective dose and the lifetime attributable risk (LAR) for cancer incidence and mortality are calculated based on the International Commission on Radiation Protection’s (ICRP) 103 recommendations and the Committee on the Biological Effects of Ionising Radiations’ latest (BEIR VII) report, respectively.
Results
The study found that procedures conducted using DVA significantly reduce the radiation exposure of patients, compared to DSA. The collective effective dose for the DVA group was 58% lower than that for the DSA group. Correspondingly, the LAR of different organs showed a substantial decrease for cancer incidence (25–75%) and mortality (51–84%).
Conclusion
DVA demonstrates a considerable reduction in physical dosimetric quantities and consequently effective dose and cancer risk, suggesting its potential as a safer alternative to DSA in interventional radiology. The use of DVA supports the optimisation of patient radiation protection and aligns with the principles of ALARA (as low as reasonably achievable).
本研究通过对介入手术的患者暴露进行建模，比较了数字变异血管造影术（DVA）和数字减影血管造影术（DSA）之间辐射危害的减少情况。本文介绍了使用内部开发的工具对用于诊断外周动脉疾病（PAD）的 DVA 临床试验中 107 例患者暴露进行的回顾性风险评估。DICOM 暴露参数用于启动 PENELOPE（正电子和电子的穿透和能量分布）蒙特卡罗模拟、辐射质量和数量以及照射几何形状。癌症发病率和死亡率的有效剂量和终生可归因风险（LAR）分别根据国际辐射防护委员会（ICRP）第 103 号建议和电离辐射生物效应委员会（BEIR VII）的最新报告计算得出。DVA 组的集体有效剂量比 DSA 组低 58%。相应地，不同器官的 LAR 癌症发病率（25%-75%）和死亡率（51%-84%）也大幅降低。DVA 的使用有助于优化对患者的辐射防护，并符合 ALARA（尽可能低）原则。
{"title":"Comparative effectiveness of digital variance and subtraction angiography in lower limb angiography: A Monte Carlo modelling approach","authors":"Richárd Elek , Levente Herényi , Marcell Gyánó , Balázs Nemes , Szabolcs Osváth","doi":"10.1016/j.ejmp.2024.104859","DOIUrl":"10.1016/j.ejmp.2024.104859","url":null,"abstract":"<div><h3>Objective</h3><div>By modelling patient exposures of interventional procedures, this study compares the reduction of radiation detriment between Digital Variance Angiography (DVA) and Digital Subtraction Angiography (DSA).</div></div><div><h3>Methods</h3><div>The paper presents a retrospective risk assessment using an in-house developed tool on 107 patient exposures from a clinical trial of DVA used to diagnose peripheral arterial disease (PAD). DICOM exposure parameters were used to initiate the PENELOPE (PENetration and Energy LOss of Positrons and Electrons) Monte Carlo simulation, radiation quality and quantity, and irradiation geometry. The effective dose and the lifetime attributable risk (LAR) for cancer incidence and mortality are calculated based on the International Commission on Radiation Protection’s (ICRP) 103 recommendations and the Committee on the Biological Effects of Ionising Radiations’ latest (BEIR VII) report, respectively.</div></div><div><h3>Results</h3><div>The study found that procedures conducted using DVA significantly reduce the radiation exposure of patients, compared to DSA. The collective effective dose for the DVA group was 58% lower than that for the DSA group. Correspondingly, the LAR of different organs showed a substantial decrease for cancer incidence (25–75%) and mortality (51–84%).</div></div><div><h3>Conclusion</h3><div>DVA demonstrates a considerable reduction in physical dosimetric quantities and consequently effective dose and cancer risk, suggesting its potential as a safer alternative to DSA in interventional radiology. The use of DVA supports the optimisation of patient radiation protection and aligns with the principles of ALARA (as low as reasonably achievable).</div></div>","PeriodicalId":56092,"journal":{"name":"Physica Medica-European Journal of Medical Physics","volume":"128 ","pages":"Article 104859"},"PeriodicalIF":3.3,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142699168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-09DOI: 10.1016/j.ejmp.2024.104842
Juuso H.J. Ketola , Satu I. Inkinen , Teemu Mäkelä , Suvi Syväranta , Juha Peltonen , Touko Kaasalainen , Mika Kortesniemi
Artificial intelligence (AI) applications are becoming increasingly common in radiology. However, ensuring reliable operation and expected clinical benefits remains a challenge. A systematic testing process aims to facilitate clinical deployment by confirming software applicability to local patient populations, practises, adherence to regulatory and safety requirements, and compatibility with existing systems. In this work, we present our testing process developed based on practical experience. First, a survey and pre-evaluation is conducted, where information requests are sent for potential products, and the specifications are evaluated against predetermined requirements. In the second phase, data collection, testing, and analysis are conducted. In the retrospective stage, the application undergoes testing with a pre selected dataset and is evaluated against specified key performance indicators (KPIs). In the prospective stage, the application is integrated into the clinical workflow and evaluated with additional process-specific KPIs. In the final phase, the results are evaluated in terms of safety, effectiveness, productivity, and integration. The final report summarises the results and includes a procurement/deployment or rejection recommendation. The process allows termination at any phase if the application fails to meet essential criteria. In addition, we present practical remarks from our experiences in AI testing and provide forms to guide and document the testing process. The established AI testing process facilitates a systematic evaluation and documentation of new technologies ensuring that each application undergoes equal and sufficient validation. Testing with local data is crucial for identifying biases and pitfalls of AI algorithms to improve the quality and safety, ultimately benefiting patient care.
{"title":"Testing process for artificial intelligence applications in radiology practice","authors":"Juuso H.J. Ketola , Satu I. Inkinen , Teemu Mäkelä , Suvi Syväranta , Juha Peltonen , Touko Kaasalainen , Mika Kortesniemi","doi":"10.1016/j.ejmp.2024.104842","DOIUrl":"10.1016/j.ejmp.2024.104842","url":null,"abstract":"<div><div>Artificial intelligence (AI) applications are becoming increasingly common in radiology. However, ensuring reliable operation and expected clinical benefits remains a challenge. A systematic testing process aims to facilitate clinical deployment by confirming software applicability to local patient populations, practises, adherence to regulatory and safety requirements, and compatibility with existing systems. In this work, we present our testing process developed based on practical experience. First, a survey and pre-evaluation is conducted, where information requests are sent for potential products, and the specifications are evaluated against predetermined requirements. In the second phase, data collection, testing, and analysis are conducted. In the retrospective stage, the application undergoes testing with a pre selected dataset and is evaluated against specified key performance indicators (KPIs). In the prospective stage, the application is integrated into the clinical workflow and evaluated with additional process-specific KPIs. In the final phase, the results are evaluated in terms of safety, effectiveness, productivity, and integration. The final report summarises the results and includes a procurement/deployment or rejection recommendation. The process allows termination at any phase if the application fails to meet essential criteria. In addition, we present practical remarks from our experiences in AI testing and provide forms to guide and document the testing process. The established AI testing process facilitates a systematic evaluation and documentation of new technologies ensuring that each application undergoes equal and sufficient validation. Testing with local data is crucial for identifying biases and pitfalls of AI algorithms to improve the quality and safety, ultimately benefiting patient care.</div></div>","PeriodicalId":56092,"journal":{"name":"Physica Medica-European Journal of Medical Physics","volume":"128 ","pages":"Article 104842"},"PeriodicalIF":3.3,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142633306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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