Medical physics最新文献

{"title":"Teaching AI for Radiology Applications: A Multisociety‑Recommended Syllabus from the AAPM, ACR, RSNA, and SIIM","authors":"Felipe Kitamura,&nbsp;Timothy Kline,&nbsp;Daniel Warren,&nbsp;Linda Moy,&nbsp;Roxana Daneshjou,&nbsp;Farhad Maleki,&nbsp;Igor Santos,&nbsp;Judy Gichoya,&nbsp;Walter Wiggins,&nbsp;Brian Bialecki,&nbsp;Kevin O'Donnell,&nbsp;Adam E. Flanders,&nbsp;Matt Morgan,&nbsp;Nabile Safdar,&nbsp;Katherine P. Andriole,&nbsp;Raym Geis,&nbsp;Bibb Allen,&nbsp;Keith Dreyer,&nbsp;Matt Lungren,&nbsp;Monica J. Wood,&nbsp;Marc Kohli,&nbsp;Steve Langer,&nbsp;George Shih,&nbsp;Eduardo Farina,&nbsp;Charles E. Kahn Jr.,&nbsp;Ingrid Reiser,&nbsp;Maryellen Giger,&nbsp;Christoph Wald,&nbsp;John Mongan,&nbsp;Tessa Cook,&nbsp;Neil Tenenholtz","doi":"10.1002/mp.17779","DOIUrl":"10.1002/mp.17779","url":null,"abstract":"<p>Medical imaging is undergoing a transformation driven by the advent of new, highly effective, machine learning techniques paired with increases in computational capabilities (Cheng et al. 2021; Gilson et al. 2023; Almeida et al. 2024; Krishna et al. 2024). These advanced algorithms have the potential to improve disease detection, diagnosis, prognosis, and treatment outcomes. However, the complexity of machine learning models, the large amounts of curated and annotated data required by some methods, and the potential for bias and error make it challenging for individuals to safely and effectively leverage these methods (Lin et al. 2024; Guo et al. 2024; Xu et al. 2024; Linguraru et al. 2024; Wood et al. 2019). To address these challenges, the American Association of Physicists in Medicine (AAPM), American College of Radiology (ACR), Radiological Society of North America (RSNA), and Society for Imaging Informatics in Medicine (SIIM) have worked together to develop a syllabus detailing a recommended set of competencies for medical imaging professionals interacting with these systems. This guide is aimed at four different personas: users of AI systems, purchasers of AI systems, individuals who provide clinical expertise during the development of AI systems (“clinical collaborators”), and developers of AI systems.1 This is a syllabus, not a curriculum, and is intentional in this scope. Recognizing that individuals may benefit from different presentations of the same material, this work enumerates a series of relevant competencies but does not prescribe, nor offer, a method of instruction (Schuur, Rezazade Mehrizi, and Ranschaert 2021; Garin et al. 2023). By addressing the task-specific demands of each role, this guide will enable medical imaging professionals to utilize machine learning systems more safely and effectively, ultimately improving patient care and outcomes.</p>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 10","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12485864/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145202632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Treatment parameters consideration for universal range shifter-based multi-energy proton FLASH-RT","authors":"Yiling Zeng,&nbsp;Hong Quan,&nbsp;Qi Zhang,&nbsp;Wei Wang,&nbsp;Xu Liu,&nbsp;Bin Qin,&nbsp;Bo Pang,&nbsp;Muyu Liu,&nbsp;Shuoyan Chen,&nbsp;Kunyu Yang,&nbsp;Yu Chang,&nbsp;Zhiyong Yang","doi":"10.1002/mp.70039","DOIUrl":"10.1002/mp.70039","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Compared to conventional dose rate irradiation, ultra-high dose rate irradiation provides superior normal tissue sparing. Multi-energy proton beams combined with a universal range shifter (URS) and fast energy-switching gantry enable ultra-high dose rate delivery.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>This study investigates the effects of the URS, planning parameters, and patient selection on multi-energy Bragg peak (MEBP) proton FLASH radiotherapy (FLASH-RT) plans.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Single-field plans were generated for water phantoms and a brain case, comparing beam setups with and without the URS. Planning parameters, including spot spacing, layer spacing, and beam orientation, were varied. The effects of fractional dose and target size were also assessed. Dose and FLASH-related metrics were analyzed.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The use of a URS increased the spot size, which reduced the number of required spots and energy layers but also resulted in a broader penumbra, a prolonged distal falloff, and a higher D_mean in normal tissue. These effects became more pronounced with greater URS thickness. A spot spacing of 1.5 times the spot size (σ) and a layer spacing of 1.0 times the Bragg peak width (Proximal and Distal R80) improved V_40Gy/s, while effectively maintaining plan quality. Beam orientations with smaller field sizes increased V_40Gy/s. As the fractional dose increased, V_40Gy/s also increased, reaching saturation around 25 GyRBE. Additionally, V_40Gy/s improved with smaller target volumes.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The URS has a significant impact on plan quality, requiring a balance between normal tissue sparing and the FLASH effect in MEBP planning. Although MEBP plan is suitable for treating tumors with complex shapes, careful selection of planning parameters is critical for achieving effective FLASH treatment.</p>\u0000 </section>\u0000 </div>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 10","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145202575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diffusing alpha-emitters radiation therapy: In vivo measurements of effective diffusion and clearance rates across multiple tumor types","authors":"Mirta Dumančić,&nbsp;Guy Heger,&nbsp;Ishai Luz,&nbsp;Maayan Vatarescu,&nbsp;Noam Weizman,&nbsp;Lior Epstein,&nbsp;Tomer Cooks,&nbsp;Lior Arazi","doi":"10.1002/mp.70052","DOIUrl":"10.1002/mp.70052","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Background&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Diffusing alpha-emitters radiation therapy (“Alpha-DaRT”) is a new modality that uses alpha particles to treat solid tumors. Alpha-DaRT employs interstitial sources loaded with low activities of &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msup&gt;\u0000 &lt;mrow&gt;&lt;/mrow&gt;\u0000 &lt;mn&gt;224&lt;/mn&gt;\u0000 &lt;/msup&gt;\u0000 &lt;mi&gt;Ra&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$^{224}{rm Ra}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;, designed to release a chain of short-lived alpha-emitters, which diffuse over a few millimeters around each source. Alpha-DaRT dosimetry is described, to first order, by a framework called the “diffusion–leakage” (DL) model.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Purpose&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;The aim of this work is to estimate the tumor-specific parameters of the DL model from in vivo studies on multiple histological cancer types.&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;Autoradiography studies with phosphor imaging were conducted on 113 tumors in mice from 10 cancer cell lines. An observable, referred to as the “effective diffusion length” &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;L&lt;/mi&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;e&lt;/mi&gt;\u0000 &lt;mi&gt;f&lt;/mi&gt;\u0000 &lt;mi&gt;f&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/msub&gt;\u0000 &lt;annotation&gt;$L_{eff}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;, was extracted from images of histological slices obtained using phosphor screens. The tumor and Alpha-DaRT source activities were measured after excision with a gamma counter to estimate the probability of &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msup&gt;\u0000 &lt;mrow&gt;&lt;/mrow&gt;\u0000 &lt;mn&gt;212&lt;/mn&gt;\u0000 &lt;/msup&gt;\u0000 &lt;mi&gt;Pb&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$^{212}{rm Pb}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; clearance from the tumor by the blood, &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;P&lt;/mi&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;l&lt;/mi&gt;\u0000 &lt;mi&gt;e&lt;/mi&gt;\u0000 ","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 10","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12483980/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145202598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AAPM 2025 67th Annual Meeting & Exhibition July 27–30 Washington DC","authors":"","doi":"10.1002/mp.70058","DOIUrl":"10.1002/mp.70058","url":null,"abstract":"","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 10","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145194089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"FLASH irradiation-induced acute lung injury promotes metastatic colonization via neutrophil extracellular trap formation","authors":"Hui Luo,&nbsp;Chengliang Yang,&nbsp;Marie-Catherine Vozenin,&nbsp;Ronghu Mao,&nbsp;Leijie Ma,&nbsp;Hongchang Lei,&nbsp;Hong Ge","doi":"10.1002/mp.70054","DOIUrl":"10.1002/mp.70054","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>FLASH irradiation, a technique that delivers prescribed dose at ultra-high dose rate, has been described to alleviate normal tissue injury in multiple animal models. However, the underlying mechanism was not fully understood.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>We aimed to investigate whether FLASH irradiation-induced acute lung injury could reduce metastatic colonization compared with conventional (CONV) irradiation.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Healthy lungs of C57BL/6J male mice were irradiated with either FLASH or CONV, SV2 lung adenocarcinoma cells were intravenously injected and healthy lung volume was monitored using micro-computed tomography (micro-CT). The irradiated tissues (tumor + normal parenchyma) were analyzed by proteomic to identify key regulators of cancer progression. Key proteins were preliminarily validated using real-time quantitative PCR and western blot. Further validation was carried out by inhibiting or promoting neutrophil extracellular traps (NETs) formation within in vivo models.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>In radiation-induced acute lung injury models, both CONV and FLASH involved in equivalent and enhanced metastatic colonization. Follow-up molecular analysis using proteomic profiling revealed NETs formation involved in cancer progression. Both radiation modalities triggered acute lung injury and inflammatory response with a similar pattern. Inhibiting NETs formation significantly delay tumor metastasis in either FLASH or CONV, whereas stimulating NETs formation markedly accelerate cancer progression.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>These experiments suggest that healthy lung spare does not recapitulate at acute time point after exposure to FLASH. Proteomic analyses suggest a possible role for NETs formation within the tumor microenvironment in deriving cancer cell seeding. NETs formation could be served as a prognostic factor in thoracic cancer.</p>\u0000 </section>\u0000 </div>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 10","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145202648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Equivalent relative biological effectiveness for cell survival and micronuclei formation: insights from a biophysical approach","authors":"Yusuke Matsuya,&nbsp;Ryo Saga,&nbsp;Yidi Wang,&nbsp;Tatsuhiko Sato","doi":"10.1002/mp.70040","DOIUrl":"10.1002/mp.70040","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Micronuclei (MN), which are chromosome fragments, are formed after exposure to ionizing radiation. Radiation-induced MN is currently used as a quantitative indicator of the chromosomal aberrations detectable at a relatively early phase (e.g., within one cell-cycle progression). Meanwhile, the MN formation assay is also used to evaluate radiosensitivity (e.g., cell-killing). As such, the technique to assay the MN formation has been followed with increasing interest. However, the meaning of MN and the corresponding cellular responses remains uncertain.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>This study presents a biophysical model for estimating MN frequency and theoretically explores the cellular responses associated with MN formation, such as the relationship between MN formation and cell survival.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We used an integrated microdosimetric-kinetic (IMK) model that allows the prediction of cell survival after radiation exposure, and we extended the IMK model by introducing a probability of MN formation from lethal lesions by misrepair. To validate the developed model, we estimated the dose, linear energy transfer (LET), and dose-rate dependencies of MN frequency as well as its relative biological effectiveness (RBE_MN) and compared them to the corresponding experimental data reported in the literature and measured in this study. The estimation approach of MN frequency from cell survival data and vice versa was also tested.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Our developed IMK model enables the prediction of the MN formation frequency and the RBE_MN depending on LET and dose rate for both cancer and normal cells. Comparing the experimental data within this work and the literature, the modeling study clearly shows that radiation-induced MN is intrinsically related to cell killing after radiation exposure. Our model analyses confirmed that the RBE values for cell survival and MN frequency are equivalent under the same irradiation conditions.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The present model indicates that the analysis of MN is useful in both radiation therapy and radiation protection to quantitatively evaluate curative effects and histological damage at early stages after exposure.</p>\u0000 </section>\u0000 </div>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 10","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12483971/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145202588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cover","authors":"","doi":"10.1002/mp.70057","DOIUrl":"https://doi.org/10.1002/mp.70057","url":null,"abstract":"","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 9","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://aapm.onlinelibrary.wiley.com/doi/epdf/10.1002/mp.70057","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145224345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Margins to account for cardiac and respiratory motion in cardiac radioablation","authors":"Jakob Marshall,&nbsp;Justin Poon,&nbsp;Alanah Bergman,&nbsp;Tania Karan,&nbsp;Marc W. Deyell,&nbsp;Devin Schellenberg,&nbsp;Richard B. Thompson,&nbsp;Steven Thomas","doi":"10.1002/mp.70041","DOIUrl":"10.1002/mp.70041","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Background&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Cardiac radioablation (CR) is an emerging treatment for ventricular tachycardia, a rapid abnormal heart rhythm. Effectively delivering radiation to CR targets requires understanding and accounting for geometric uncertainties. One important uncertainty is motion induced by the cardiac and respiratory cycles, which can be accounted for by expanding the targeted region by a margin accounting for the motion's effect on dosimetry.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Purpose&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;To investigate margins to account for cardiac and respiratory motions in CR and compare different methods of computing these margins.&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;Eighty four hundred cardiorespiratory motion traces were created by joining 1050 cardiac motions derived from 30 Hz magnetic resonance images with eight respiratory motions from 5 Hz bi-planar kV fluoroscopy. Cardiac motions for each of the 17 segments of the left ventricle were acquired for 50 heart failure patients with a reduced ejection fraction. Respiratory motions were derived from the implantable cardioverter defibrillator lead's tip for eight CR patients. The margins needed to account for random errors were found using the convolution method by blurring a dose penumbra (Gaussian fall-off &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;σ&lt;/mi&gt;\u0000 &lt;mi&gt;p&lt;/mi&gt;\u0000 &lt;/msub&gt;\u0000 &lt;mspace&gt;&lt;/mspace&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;${sigma _p};$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;= 3.2 mm) with the motion. The motion margin was computed as the shift in the 95% dose level after blurring. Since these dosimetric margins do not consider rotations and shape deformation, they are considered a lower limit to account for cardiorespiratory motions. These motion margins were compared to (i) a sum of cardiac and respiratory motion amplitudes, similar to using an internal target volume (ITV); (ii) the van Herk et al. margin formula (MF = &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;β&lt;/mi&gt;\u0000 &lt;mo&gt;(&lt;/mo&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;σ&lt;/mi&gt;\u0000 &lt;mo&gt;−&lt;/mo&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;σ&lt;/mi&gt;\u0000 &lt;mi&gt;p&lt;/mi&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;mo&gt;)&lt;/mo&gt;\u0000 ","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 10","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12480060/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145194143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Retrospective 4D-CT binning based on concurrent non-contact respiratory and cardiac phase tracking using millimeter wave (mmWave) radar","authors":"Jingxuan Zhu,&nbsp;David Zhang,&nbsp;Ziyu Shu,&nbsp;Pamela Samson,&nbsp;Clifford Robinson,&nbsp;Yao Hao,&nbsp;Tiezhi Zhang","doi":"10.1002/mp.18113","DOIUrl":"10.1002/mp.18113","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Concurrent measurement of respiratory and cardiac phases during 4D-CT scans is desired for the treatment of targets in proximity to the heart. Traditional methods require two separate contact-based sensors to monitor breathing and heart beats, which can be inconvenient and intrusive. The mmWave radar can provide non-contact monitoring of patient's motion and has the potential for concurrent monitoring of respiratory and cardiac cycles, offering a promising alternative for phase tracking in 4D-CT.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>The aim of this study is to validate mmWave radars for non-contact phase tracking of respiratory and cardiac waveforms and investigate its application in 4D-CT imaging.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A 60–64 GHz frequency modulated continuous wave (FMCW) radar was used to track the chest wall displacement of healthy volunteers. Respiratory and cardiac signals were extracted from the reflected signals by Fast Fourier Transform (FFT) algorithms and phase unwrapping method. Meanwhile, a respiration bellow and an ECG sensor were used to monitor respiratory and cardiac cycles, respectively, as references. The phase correlations between respiratory and cardiac cycles from the mmWave radar and reference devices were studied, and 4D-CT phase binning was conducted using mmWave signals.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The mmWave radar measurement demonstrated strong correlation with the reference measurements, showing high Pearson correlation coefficients ranging from 0.9437 to 0.9533 for respiratory waveforms and 0.9632–0.9896 for cardiac waveforms. Using mmWave signals, phase binning for 4D respiratory and cardiac CT achieved high accuracy, with relative errors of 0.1% and 2.3%, respectively. The system was able to track both signals accurately, with minimal time offsets, highlighting its capability for simultaneous respiratory and cardiac monitoring and precise phase binning in 4D-CT.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The mmWave FMCW radar presents a convenient and effective solution for non-contact, concurrent respiratory and cardiac phase tracking, enabling precise phase binning in 4D-CT imaging. Its ability to detect subtle chest wall movements associated with breathing and heartbeats eliminates the need for physical contact sensors, offering a potential alternative to traditional contact-based methods in 4D-CT.</p>\u0000 </section>\u0000 </div>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 10","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145194109","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Developing machine learning-driven acute kidney injury predictive models using non-standard EMRs in resource-limited settings","authors":"Shengwen Guo,&nbsp;Yuanhan Chen,&nbsp;Yu Kuang,&nbsp;Qin Zhang,&nbsp;Yanhua Wu,&nbsp;Zhen Xie,&nbsp;Ziqiang Chen,&nbsp;Qiang He,&nbsp;Feng Ding,&nbsp;Guohui Liu,&nbsp;Yuanjiang Liao,&nbsp;Chen Lu,&nbsp;Li Hao,&nbsp;Jing Sun,&nbsp;Lang Zhou,&nbsp;Rui Fang,&nbsp;Qingquan Luo,&nbsp;Haiquan Huang,&nbsp;Qi Cheng,&nbsp;Xinling Liang","doi":"10.1002/mp.70038","DOIUrl":"10.1002/mp.70038","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Acute Kidney Injury (AKI) remains a significant global health challenge, especially in resource-limited settings. Most existing predictive models rely heavily on serum creatinine (SCr) levels and standardized electronic medical records (EMRs). However, in many low-resource environments, SCr testing is infrequent, and EMR systems often lack standardization in data structure, terminology, and recording practices (a.k.a., non-standard EMRs). These limitations hinder the consistent extraction of features needed for accurate AKI prediction and highlight the urgent need for adaptive frameworks tailored to diverse and resource-limited healthcare environments.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>This study aimed to develop and validate a machine learning model using non-standardized EMRs for predicting AKI, even without SCr data.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This multicenter observational study, conducted from 2010 to 2016 across 15 hospitals in China, employed the Light Gradient Boosting Machine (LightGBM) to create predictive models. The model's performance was assessed using area under the curve (AUC), precision, recall, specificity, and accuracy.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>A total of 561 137 hospitalized patients were eligible for the analyses, of whom 45 610 were diagnosed with AKI. The LightGBM model demonstrated high accuracy in predicting AKI, with AUC values ranging from 0.860 to 0.986. The study showed that non-standard EMRs could effectively predict AKI. Importantly, the model maintained strong predictive performance even without SCr data, indicating that AKI can be accurately predicted without this traditional biomarker.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Non-standard EMRs are valuable for predicting AKI, even in the absence of SCr data. This approach is particularly useful in resource-limited settings, where traditional biomarkers are often unavailable, demonstrating the potential of other clinical features to compensate for missing SCr data in AKI prediction.</p>\u0000 </section>\u0000 </div>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 10","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12480061/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145194127","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}