Journal of Applied Clinical Medical Physics最新文献

{"title":"AI-coded radiation therapy software requires unique quality assurance","authors":"Alon Witztum, Yi Wang, Dongxu Wang","doi":"10.1002/acm2.70848","DOIUrl":"10.1002/acm2.70848","url":null,"abstract":"<p>Software is an inseparable part of modern radiation therapy (RT), running everything from treatment planning and record-and-verify systems to the small scripts that physicists write to bridge gaps between clinical systems. Increasingly, software codes are crafted with the help of artificial intelligence (AI): large language models (LLMs) can now generate, modify, test, and document the software on which patient care depends. This prompts a question for our profession, known for its focus on quality assurance (QA) and safety: does software written with AI assistance demand a QA strategy of its own, distinct from the checks we already apply to any clinical software? This question spans the full range of software encountered in the clinic, from FDA-cleared commercial products where development QA rests with the manufacturer, to in-house scripts and tools where the physicist is often both the developer and the end user. The question is not whether such software must be verified and validated (it must), but whether AI's involvement in writing the code changes what that verification should look like, and by whom it should be performed, if it is beyond what we already require for any clinical software. To examine this emerging question, we invited two medical physicists to argue the opposing sides of the proposition: “<i>AI-coded radiation therapy software requires unique</i> <i>QA</i>.” Arguing for the proposition is Alon Witztum, DPhil, DABR; arguing against the proposition is Yi Wang, PhD, DABR.</p><p>Dr. Alon Witztum is a medical physicist and Associate Professor in the Department of Radiation Oncology at the University of California, San Francisco (UCSF). He earned his DPhil in Oncology from the University of Oxford, completed his clinical residency in medical physics at UCSF, and is board-certified by the American Board of Radiology. His work centers on data-driven innovation, clinical automation, and toxicity and outcome modeling. In his position as Director of Radiation Oncology Reporting & Analytics at UCSF he develops informatics pipelines and tools for the clinic, research, quality improvement, and operations. He has contributed to textbooks and given invited talks on the use of AI in radiotherapy QA. As part of the AAPM he serves on the Big Data Subcommittee and the working group on MPPG 20: patient-specific QA for dynamic and intensity modulated RT.</p><p>Dr. Yi Wang is a medical physicist from the Department of Radiation Oncology at Massachusetts General Hospital (MGH) and an Assistant Professor of Radiation Oncology at Harvard Medical School (HMS) in Boston, MA. He is certified in Therapeutic Radiologic Physics by the American Board of Radiology (ABR). He earned his Ph.D. in Biomedical Engineering from the University of Michigan in 2009 and completed the Harvard Medical Physics Residency Program in 2012. Since then, he has been working as a faculty physicist in the Department of Radiation Oncology at MGH. Locally, he leads an AI La","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"27 10","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13662527/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149181740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Longitudinal trends in Gamma Knife radiosurgery utilization across multiple technological generations: A Single-Institution Observational Study","authors":"Daniel El Basha, Eric Filiput, Austen Curcuru, Sven Ferguson, Sreekrishna Murty Goddu, Nels Knutson, Hugh Lee, Timothy Mitchell, Seungjong Oh, Joshua L. Dowling, Jiayi Huang, Taeho Kim","doi":"10.1002/acm2.70808","DOIUrl":"10.1002/acm2.70808","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Gamma Knife radiosurgery (GKRS) has been a foundational modality for the treatment of intracranial diseases for several decades, with successive platform generations introducing substantial technological advancements. Improvements in source configuration, patient positioning systems, imaging guidance, and immobilization techniques have expanded clinical capabilities. Despite these ongoing innovations, few long-term institutional analyses have evaluated whether GKRS utilization has remained stable, increased, or shifted with changes in disease patterns and retreatment needs over time.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>Gamma Knife radiosurgery (GKRS) has undergone multiple technological evolutions over the past two decades. This study provides a retrospective analysis of longitudinal utilization at a single institution, examining trends in case volume, disease indications, retreatment frequency, and platform era.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A retrospective analysis of Gamma Knife treatments delivered at one institution between 1998 and 2025 was performed. Annual counts of first, repeat, and total GKRS treatments were analyzed using negative binomial regression with a log link and Newey–West standard errors; platform-adjusted models accounted for the sequential relationship between calendar time and platform era. Segmented negative binomial regression of monthly counts evaluated slope changes at platform transitions.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Across the study period, 6,201 unique patients received 7,267 delivered treatment courses. Median annual treatment volume was 276 procedures (range, 71–362); median age at first treatment was 60 years (IQR, 50–69), and brain metastasis was the primary indication in 2,991 patients (48.2%). Total volume increased in unadjusted modeling (count ratio [CR], 1.03; <i>p <</i> 0.001), and repeat treatments showed the strongest platform-adjusted growth (CR 1.14; <i>p <</i> 0.001). Metastatic disease was the dominant adjusted disease-specific trend (CR 1.08; <i>p =</i> 0.01). Repeat metastatic treatments increased more than overall repeat treatments (CR 1.15; <i>p <</i> 0.001). Segmented regression showed significant growth during the baseline Model B era (annualized CR 1.16; <i>p <</i> 0.001) followed by significant attenuation at the Model C transition (annualized CR 0.90; <i>p =</i> 0.01). The primary segmented model showed no significant incremental slope change at Perfexion or Icon; sensitivity analyses indicated that","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"27 10","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13662532/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149182010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In Regards to Hayashi et al. JACMP 27(8), e70741","authors":"Jicheng Zhang, Tao You","doi":"10.1002/acm2.70827","DOIUrl":"10.1002/acm2.70827","url":null,"abstract":"<p>In Regard to Hayashi et al.</p><p>We read the study by Hayashi et al.<span><sup>1</sup></span> with interest. The authors evaluated how MRI slice thickness and gold fiducial marker (GFM) orientation affect measurement accuracy in three-dimensional multi-echo gradient recalled echo imaging. They found lower measurement error with 1.0-mm slices and concluded that this protocol can maintain “consistent sub-millimeter localization accuracy” across marker orientations. The study provides useful data on marker visualization, but the reported endpoint does not directly measure localization error.</p><p>The primary outcome was the difference between the GFM length calculated on the treatment planning system and its physical length of 10.0 mm.<span><sup>1</sup></span> Observers identified the three-dimensional coordinates of both marker tips, but these coordinates were then used to calculate the Euclidean distance between the tips. Thus, the reported error is an error in measured marker length, not the displacement of either tip or of the marker relative to an independent spatial reference. If both identified tips are shifted by the same vector, the measured length can remain unchanged despite a localization error. Conversely, the apparent signal void could extend at both marker ends, increasing the measured length while leaving the marker center unchanged. The authors themselves note in the Discussion that stability in length measurement does not imply true three-dimensional localization accuracy because their metric does not measure coordinate deviation relative to a reference.<span><sup>1</sup></span> This distinction is not carried into the Conclusion.</p><p>The data also do not show submillimeter marker-length error at every orientation. With 1.0-mm slices, the overall mean measurement error was 0.96 mm (95% CI, 0.70-1.22 mm).<span><sup>1</sup></span> In Table 3, the orientation-specific means range from 0.32 to 1.42 mm, and 7 of the 12 orientations exceed 1 mm.<span><sup>1</sup></span> These results support lower overall marker-length error with 1.0-mm slices, but not the statement that submillimeter accuracy was maintained across all orientations.</p><p>This also affects the margin illustration. The authors use the maximum 3.10-mm measurement error as a hypothetical constant systematic shift in the Van Herk margin formula.<span><sup>1, 2</sup></span> A 3.10-mm overestimation of marker length, however, is not a demonstrated 3.10-mm translational displacement. For example, extension of the signal void at both marker ends could increase the measured length while leaving the marker center unchanged. The authors appropriately describe this calculation as theoretical, but treating a length error as an equivalent positional error goes beyond what the experiment measured.</p><p>The advantage of thinner slices remains supported by the study. We suggest describing that advantage in terms of reduced marker-length measurement error unless localization is as","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"27 10","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70827","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149136638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In Response to Zhang & You","authors":"Aika Hayashi, Yasukata Takahashi, Naoko Sanuki, Yasufumi Yamashita, Yoshitaka Suzuki, Kanae Matsuura, Hiroe Muto","doi":"10.1002/acm2.70821","DOIUrl":"https://doi.org/10.1002/acm2.70821","url":null,"abstract":"<p>We read with great interest and appreciate the thoughtful, constructive comments on our recently published article, “Impact of MRI slice thickness and fiducial marker orientation on geometric accuracy in multi-echo GRE imaging for prostate radiotherapy planning”.<span><sup>1</sup></span> We thank the correspondents for their detailed analysis and for supporting our primary finding that a thinner (1.0 mm) MRI slice protocol significantly reduces marker-length measurement error.</p><p>The correspondents raise several crucial points about the distinction between “marker-length measurement error” and “true three-dimensional localization/displacement error.” We fully agree with their scientific reasoning and appreciate this opportunity to clarify and refine our interpretations.</p><p>First, we acknowledge the limitation that our primary metric (the difference between the physically verified 10.0-mm GFM length and the Euclidean distance calculated from coordinates identified on the treatment planning system) measures marker-length distortion rather than translational displacement of the marker's centroid or individual tips relative to an independent spatial reference.<span><sup>1</sup></span> As the correspondents rightly point out, symmetric shifts in identified coordinates or isotropic extension of the signal void could affect length measurements without changing the true marker center, and vice versa. Although we acknowledged this intrinsic limitation in the Discussion section of our article, we admit that our use of the term “localization accuracy” in the Abstract and Conclusion was overgeneralized. We agree that it is more accurate to describe this advantage as “reduced marker-length measurement error” until localization is validated against an independent spatial coordinate system.</p><p>Second, regarding the 1.0-mm slice protocol, we agree that while the overall mean measurement error was sub-millimeter (0.96 mm; 95% CI, 0.70–1.22 mm), the specific mean errors in 7 of the 12 orientations did slightly exceed 1.0 mm (ranging from 1.04–1.42 mm). The statement that sub-millimeter accuracy was “maintained across all orientations” was indeed an oversimplification of our tabular data. We appreciate this clarification and agree that the thinner slice protocol minimizes overall measurement error but does not guarantee sub-millimeter precision at every individual orientation angle.</p><p>Third, we concur with the feedback regarding the Van Herk margin simulation.<span><sup>2</sup></span> Our simulation, which utilized the peak measurement error of 3.10 mm as a hypothetical constant systematic shift (Σ), was a worst-case theoretical exploration rather than a demonstrated clinical mandate. We agree that treating a 3.10-mm overestimation of length as an equivalent positional displacement goes beyond our experimental measurements, as signal void extension at both ends may leave the marker center unchanged. We appreciate the recommendation to evaluate CT-MR","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"27 10","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70821","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149146340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Verifying calculated dose to the breast in stereotactic radiotherapy: A practical phantom-based method","authors":"Stewart J. Becker, Ryan E. Smith, Wesley S. Culberson, Kurt E. Stump, Baoshe Zhang, Jie Ding, Sina Mossahebi, Dennis Herschbach, Elizabeth M. Nichols","doi":"10.1002/acm2.70841","DOIUrl":"https://doi.org/10.1002/acm2.70841","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Reference dosimetry for the GammaPod breast radiosurgery device is determined in a polymethyl methacrylate (PMMA) phantom, while the clinical dose calculations assume the patient's breast has the atomic composition of water with a density (∼0.935 g/cm<sup>3</sup>). Direct measurement within this clinical breast-tissue equivalent material is desirable to validate the treatment planning system (TPS) with end-to-end testing and patient-specific quality assurance (PSQA).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>This study aimed to validate the GammaPod TPS dose calculations by 3D printing a breast-equivalent phantom and to develop a practical and reproducible method for end-to-end testing and PSQA.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Multiple breast-shaped phantoms matching the L02 GammaPod cup geometry were fabricated; three using 3D printing and one using clear ice. The 3D-printed phantoms were constructed from polylactic acid (PLA) and premium PLA (PLApro) using optimized infill densities to achieve a physical density near 0.935 g/cm<sup>3</sup>, matching the TPS's breast-tissue model. These infills were determined by creating series of CT phantom plugs and choosing the ones with the closest Hounsfield units (HUs) and stopping power ratios (SPRs) to the TPS breast tissue model. A rotating insert design allowed multi-position measurements with an Exradin A1SL ionization chamber and thermoluminescent dosimeters (TLDs). CT imaging and dosimetry were performed following the clinical GammaPod workflow. An ice phantom, with a density of approximately 0.918 g/cm<sup>3</sup>, served as an independent validation reference. Measured doses were compared with TPS-calculated doses.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The breast-tissue mimicking phantoms yielded mean Hounsfield (HU) and Stopping Power Ratios (SPR) numbers of −81 HU ± 5 and 0.99 SPR for blue PLApro (92.5%), −69 HU ± 11 and 0.99 SPR for natural PLA (86.0%), −82 HU ± 5 and 1.00 SPR for the ice phantom corresponding to densities of 0.916 g/cm<sup>3</sup>, 0.928 g/cm<sup>3</sup>, and 0.915 g/cm<sup>3</sup> respectively, comparable to the modeled breast tissue. Measured-to-calculated dose differences for the ice phantom were within ± 0.5%, while the 3D printed phantoms had an average difference of 1.2%, consistent with published dosimetric uncertainty limits of the GammaPod. The total estimated measurement uncertainty, including charge-to-dose conversion and material variability, was 1.7%. The 3D-printed phantoms demonstrated excellent re","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"27 10","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70841","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149146339","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Frequency Schrödinger bridge diffusion model for fast MRI reconstruction in abdominal MR-guided online adaptive radiotherapy","authors":"Zhiqun Wang, Shaobin Wang, Nan Liu, Qiu Guan, Qi Chen, Fang Chen, Bei Wang, Yongguang Liang, Xia Liu, Bo Yang, Lang Yu, Hongen Liao, Jie Qiu","doi":"10.1002/acm2.70831","DOIUrl":"https://doi.org/10.1002/acm2.70831","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Online adaptive radiotherapy (ART) employs modalities like CBCT, CT, and MRI. For abdominal malignancies, MRI stands out with superior soft-tissue contrast, no ionizing radiation, and functional imaging capabilities. Yet, MRI-guided ART for such cases is challenged by long treatment time. Thus, boosting efficiency, especially via accelerated MRI scanning, is vital.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>This study presents the first accurate and fast MRI reconstruction method tailored for the Unity MR-Linear system. By slashing MRI acquisition time, it aims to enhance patient compliance, reduce intra-fraction anatomical motion, and optimize clinical resource use.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A frequency Schrödinger bridge diffusion (FSBD) model for MRI reconstruction (converting 22-second MRI to full-duration MRI) was proposed, based on a retrospective analysis of 31 fractional MRI scans from 14 patients. Its reconstruction performance was compared with state-of-the-art methods: paired diffusion-based Refusion, and unpaired CycleGAN and CSGAN. Of the initially acquired 40 fractional scans, 9 examinations were excluded following predefined exclusion criteria, leaving 31 valid cases. Dataset was split strictly at patient level: 23 fractional scans for training and the remaining independent patients for testing. An extra baseline using pairwise full-duration MRI from different fractions of identical patients was supplemented for reliability verification. All metrics were calculated on complete 3D volumetric MRI rather than individual 2D slices.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Quantitative evaluation shows the FSBD model's superiority. It achieved significantly lower error metrics: MAE (86.00) and RMSE (123.42), outperforming Refusion (MAE: 99.95, RMSE: 172.55), CycleGAN (MAE: 112.92, RMSE: 149.16), and CSGAN (MAE: 103.04, RMSE: 162.29). In image quality, FSBD's PSNR (28.44 dB) and SSIM (0.885) surpassed Refusion (26.77 dB / 0.870), CycleGAN (25.82 dB / 0.881), and CSGAN (26.34 dB / 0.878). Moreover, it delivered high-fidelity reconstruction with an efficient 20-s inference time.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>This study is the first to propose a sub-one-minute MRI imaging method for the Unity MR linear accelerator in an MR-guided online adaptive radiotherapy (ART) workflow. Experimental results confirm the method's significantly better reconstruction perfo","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"27 10","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70831","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149146406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Retrospective log-based quality assurance of real-time MLC adaptation on a helical tomotherapy platform","authors":"Scott B. Crowe,&nbsp;Tanya Kairn","doi":"10.1002/acm2.70855","DOIUrl":"10.1002/acm2.70855","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Real-time multileaf collimator (MLC) adaptation is available on some helical tomotherapy treatment units. However, these systems are not supplied with software that facilitates the retrospective review of adapted delivery data.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>This study used in-house software to complete a retrospective review of 1,566 treatment fractions with the aim of verifying the suitability and accuracy of MLC adaptations provided by a real-time target tracking system.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A data extractor tool was used to access files containing planned MLC sinogram, the telemetry treatment MLC sinogram, the telemetry delivery timing data, and the 3-dimensional target offset data from each treatment fraction. These data were used to calculate target offsets in the beam's eye view so that expected adaptations could be evaluated and compared to the adaptations recorded by the MLC telemetry system. Further investigations were undertaken using dosimeter array measurements with a motion platform.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>While MLC telemetry matched expected adaptations for the vast majority of treatment fractions, erroneous MLC leaf motions lasting &gt;1 s were identified in four treatment fractions distributed across one lung and two prostate patients (amounting to 0.3% of the total number of fractions examined), producing dose discrepancies of up to 0.3 Gy which equated to 0.6% of the total prescription dose from the affected lung treatment. Phantom measurements demonstrated that a patch provided by the vendor successfully reduced the dosimetric impact of these errors to a negligible level.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>A retrospective review of 1,566 treatment fractions led to the identification of a rare error which was communicated to and subsequently patched worldwide by the vendor, exemplifying the importance of post-treatment quality assurance of adaptive radiotherapy.</p>\u0000 </section>\u0000 </div>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"27 10","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70855","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149136559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Long-term stability evaluation of user-derived electrometer calibration factors (kelec, user) for radiotherapy dosimetry","authors":"Hayato Tsuno,&nbsp;Koji Sasaki,&nbsp;Ruan Sasaki,&nbsp;Fumiyasu Matsubayashi,&nbsp;Kohei Nishi,&nbsp;Tae Ushikawa,&nbsp;Daisaku Goto,&nbsp;Ririko Kosugi,&nbsp;Yasuhiro Kawashima","doi":"10.1002/acm2.70840","DOIUrl":"10.1002/acm2.70840","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Purpose&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;User-derived electrometer calibration factors (&lt;i&gt;k&lt;/i&gt;&lt;sub&gt;elec, user&lt;/sub&gt;) have been proposed as a practical approach for electrometer quality assurance in radiotherapy dosimetry. However, the contribution of long-term stability to the uncertainty of &lt;i&gt;k&lt;/i&gt;&lt;sub&gt;elec, user&lt;/sub&gt; has not been quantitatively evaluated. This study aimed to assess the long-term stability of &lt;i&gt;k&lt;/i&gt;&lt;sub&gt;elec, user&lt;/sub&gt; over a 28-month period and to validate the method using different signal input techniques.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Methods&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;A RAMTEC Solo electrometer was used as the reference electrometer, and three electrometers (UNIDOS&lt;sup&gt;webline&lt;/sup&gt;, RAMTEC Duo, and Super MAX) were evaluated as electrometers under test. Electrometer sensitivity ratios were measured using three signal input methods: A LINAC-based method, a battery-powered current source (SCG002), and a servo-controlled current source (EMF521R). User-derived calibration factors were calculated from the sensitivity ratios and the calibration coefficient of the reference electrometer. Long-term stability was evaluated from repeated measurements over 28 months using linear regression analysis, and the associated uncertainty component was estimated according to the Guide to the Expression of Uncertainty in Measurement (GUM).&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Results&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;The coefficients of variation for repeated measurements were ≤ 0.071% for all methods. The &lt;i&gt;k&lt;/i&gt;&lt;sub&gt;elec, user&lt;/sub&gt; values obtained using the LINAC method, SCG002, and EMF521R agreed within 0.1%, with a maximum relative difference of 0.06%. Over the 28-month observation period, the largest estimated drift was 1.84 × 10&lt;sup&gt;−&lt;/sup&gt;&lt;sup&gt;4&lt;/sup&gt;, corresponding to a Type B standard uncertainty of 1.06 × 10&lt;sup&gt;−&lt;/sup&gt;&lt;sup&gt;4&lt;/sup&gt; (1.06 × 10&lt;sup&gt;−&lt;/sup&gt;&lt;sup&gt;2&lt;/sup&gt;%). The combined standard uncertainty of &lt;i&gt;k&lt;/i&gt;&lt;sub&gt;elec, user&lt;/sub&gt; remained 0.20%, and the experimentally determined long-term stability component had a negligible effect on the overall uncertainty.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Conclusions&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;The influence of signal input method on &lt;i&gt;k&lt;/i&gt;&lt;sub&gt;elec, user&lt;/sub&gt; was minimal, and consistent results were obtained using LINAC-based and current-source-based measurements. The uncertainty contribution from long-term stability over 28 months was negligible compared with the reported uncertainty of electrometer calibration factors. These findings support the use of periodic in-house sensitivity comparison measurements as a complementary quality assurance tool for monitori","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"27 10","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70840","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149136605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AAPM-HPS medical physics practice guideline 16.a: medical health physics scope of practice","authors":"Kenneth Lewis,&nbsp;John Metyko,&nbsp;Jessica Clements,&nbsp;Marc Felice,&nbsp;Mary Ellen Jafari,&nbsp;Melissa Martin,&nbsp;Thomas Morgan,&nbsp;Glenn Sturchio,&nbsp;Chu Wang,&nbsp;Neil Whiteside","doi":"10.1002/acm2.70734","DOIUrl":"10.1002/acm2.70734","url":null,"abstract":"<p>The field of Medical Health Physics (MHP) lies at the intersection of Health Physics (HP) and Medical Physics (MP). The MHP is one of the five subfields identified by the AAPM that in which a Qualified Medical Physicist (QMP) may operate independently to provide clinical professional services. The pathway to become a QMP employed in the field of MHP varies depending on which community an individual originates from (HP or MP). This document aims to identify the minimum educational requirement, appropriate professional certification(s), work experience, and the minimum areas of responsibility (scope of practice) for a QMP working the MHP subfield.</p>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"27 10","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13641361/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149109416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing photon counting detector CT reconstructions for automatic vessel tracing in prostate artery embolization","authors":"Taylor Froelich,&nbsp;Forrest B. Linch,&nbsp;Scott M. Thompson,&nbsp;Michael C. Jundt,&nbsp;Jeremy D. Collins,&nbsp;Andrea Ferrero,&nbsp;Christopher P. Favazza","doi":"10.1002/acm2.70835","DOIUrl":"10.1002/acm2.70835","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Prostate artery embolization (PAE) requires precise visualization of complex pelvic arterial anatomy and can be aided by advanced vessel navigation tools. Photon counting detector (PCD) CT provides simultaneous ultra-high resolution and material-specific imaging, potentially improving automatic vessel tracing workflow for procedural planning and guidance.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>To identify, within a PCD-CT workflow, the reconstruction that provides the most robust and consistent automatic vessel tracing for pre-procedural PAE planning.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Ten patients underwent PCD-CT angiography of the prostate arteries in ultra-high-resolution mode. Four reconstruction approaches were evaluated: conventional reconstructions with (1) standard of care kernel and (2) sharper kernel (Bv64), along with (3) monoenergetic 50 keV, and (4) iodine map spectral results. Using commercial embolization guidance software, three vessels were manually traced for each patient to establish ground truth segmentation. Subsequently, automatic vessel traces were generated using identical start/end points as the ground truth. Root mean squared error (RMSE) between automatic traces and ground truth was used to quantify tracing accuracy.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Comparing individual traces, iodine maps demonstrated consistency with median RMSE of 0.7 mm (0.4 mm interquartile range (IQR)) versus 0.7 mm (12.5 mm IQR), 1.5 mm (14.7 mm IQR), and 0.8 mm (6.7 mm IQR) for Bv56, Bv64, and 50 keV reconstructions, respectively. Iodine maps produced fewer outliers, with 13.3% of traces and 40.0% of patients having one or more traces exceeding 5 mm RMSE, compared with 26.7%–36.7% of traces and 60.0%–80.0% of patients for the other reconstructions.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Material-specific iodine reconstructions from PCD-CT yield more robust automatic vessel tracing for PAE planning, offering a workflow-compatible solution requiring minimal protocol modifications.</p>\u0000 </section>\u0000 </div>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"27 10","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13643050/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149109835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}