Medical physics最新文献

{"title":"Technique selection and technical developments for 2D dual-energy subtraction angiography on an interventional C-arm.","authors":"Ethan P Nikolau, Joseph F Whitehead, Martin G Wagner, James R Scheuermann, Paul F Laeseke, Michael A Speidel","doi":"10.1002/mp.17661","DOIUrl":"10.1002/mp.17661","url":null,"abstract":"<p><strong>Background: </strong>Dual-energy (DE) x-ray image acquisition has the potential to provide material-specific angiographic images in the interventional suite. This approach can be implemented with novel detector technologies, such as dual-layer and photon-counting detectors. Alternatively, DE imaging can be implemented on existing systems using fast kV-switching. Currently, there are no commercially available DE options for interventional platforms.</p><p><strong>Purpose: </strong>This study reports on the development of a prototype fast kV-switching DE subtraction angiography system. In contrast to alternative approaches to DE imaging in the interventional suite, this prototype uses a clinically available interventional C-arm equipped with special x-ray tube control software. An automatic exposure control algorithm and technical features needed for such a system in the interventional setting are developed and validated in phantom studies.</p><p><strong>Methods: </strong>Fast kV-switching was implemented on an interventional C-arm platform using software that enables frame-by-frame specification of x-ray tube techniques (e.g., tube voltage/kV, pulse width/ms, tube current/mA). A real-time image display was developed on a portable workstation to display DE subtraction images in real-time (nominal 15 frame/s). An empirical CNR-driven automatic exposure control (AEC) algorithm was created to guide DE tube technique selection (kV pair, ms pair, mA). The AEC model contained a look-up table which related DE tube technique parameters and air kerma to iodine CNR, which was measured in acrylic phantom models containing an iodine-equivalent reference object. For a given iodine CNR request, the AEC algorithm estimated patient thickness and then selected the DE tube technique expected to deliver the requested CNR at the minimum air kerma. The AEC algorithm was developed for DE imaging performed without and with the application of anti-correlated noise reduction (ACNR). Validation of the AEC model was performed by comparing the AEC-predicted iodine CNR values with directly measured values in a separate phantom study. Both dose efficiency (CNR<sup>2</sup>/kerma) and maximum achievable iodine CNR (within tube technique constraints) were quantified. Finally, improvements in DE iodine CNR were quantified using a novel variant to the ACNR approach, which used machine-learning image denoising (ACNR-ML).</p><p><strong>Results: </strong>The prototype system provided a continuous display of DE subtraction images. For standard DE imaging, the AEC-predicted iodine CNR values agreed with directly measured values to within 3.5% ± 1.6% (mean ± standard deviation). When ACNR was applied, predicted iodine CNR agreed with measurement to within 2.1% ± 3.3%. AEC-generated DE techniques were typically (low/high energy): 63/125 kV, 10/3.2 ms, with varying mA values. When ACNR was applied, dose efficiency was increased by a factor of 9.37 ± 2.08 and maximum CNR was incre","PeriodicalId":94136,"journal":{"name":"Medical physics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143375073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Will large language model AI (ChatGPT) be a benefit or a risk to quality for submission of medical physics manuscripts?","authors":"Daniel A Low, Per H Halvorsen, Samantha G Hedrick","doi":"10.1002/mp.17657","DOIUrl":"https://doi.org/10.1002/mp.17657","url":null,"abstract":"","PeriodicalId":94136,"journal":{"name":"Medical physics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143256558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Beam collimation and filtration optimization for a novel orthovoltage radiotherapy system.","authors":"Nathan Clements, Olivia Masella, Deae-Eddine Krim, Lane Braun, Magdalena Bazalova-Carter","doi":"10.1002/mp.17662","DOIUrl":"https://doi.org/10.1002/mp.17662","url":null,"abstract":"<p><strong>Background: </strong>The inaccessibility of clinical linear accelerators in low- and middle-income countries creates a need for low-cost alternatives. Kilovoltage (kV) x-ray tubes have shown promise as a source that could meet this need. However, performing radiotherapy with a kV x-ray tube has numerous difficulties, including high skin dose, rapid dose fall-off, and low dose rates. These limitations create a need for highly effective beam collimation and filtration.</p><p><strong>Purpose: </strong>To improve the treatment potential of a novel kV x-ray system by optimizing an iris collimator and beam filtration using Bayesian techniques and Monte Carlo (MC) simulations.</p><p><strong>Methods: </strong>The Kilovoltage Optimized AcceLerated Adaptive therapy system's current beam configuration consists of a 225 kVp x-ray tube, a 12-leaflet tungsten iris collimator, and a 0.1 mm copper filter. A Bayesian optimization was performed for the large and small focal spot sizes of the kV x-ray tube source at 220 kVp using TopasOpt, an open-source library for optimization in TOPAS. Collimator thickness, copper filter thickness, source-to-collimator distance (SCD), and source-to-surface distance (SSD) were the variables considered in the optimization. The objective function was designed to maximize the dose rate and the dose at a depth of 5 cm while minimizing the beam penumbra width and the out-of-field dose (OFD), all evaluated in a water phantom. Post-optimization, the optimal beam configuration was simulated and compared to the existing configuration.</p><p><strong>Results: </strong>The optimal collimation setup consisted of 2.5 mm thick tungsten leaflets for the iris collimator and a 350 mm SSD for both focal spot sizes. The optimal copper filtration was 0.22 mm for the large focal spot and 0.15 mm for the small focal spot, with a SCD of 148.5 mm for the large focal spot and 125.8 mm for the small focal spot. For the large focal spot, the surface dose rate decreased by 9.4%, while the PDD at 5cm depth ( <math> <semantics><msub><mtext>PDD</mtext> <mrow><mn>5</mn> <mi>c</mi> <mi>m</mi></mrow> </msub> <annotation>$text{PDD}_{5textnormal {cm}}$</annotation></semantics> </math> ) increased by 7.7% compared to the existing iris collimator. Additionally, the surface beam penumbra width was reduced by 31.3%, and no significant changes in the OFD were observed. For the small focal spot, the surface dose rate for the new collimator increased by 3.7% and the <math> <semantics><msub><mtext>PDD</mtext> <mrow><mn>5</mn> <mi>c</mi> <mi>m</mi></mrow> </msub> <annotation>$text{PDD}_{5textnormal {cm}}$</annotation></semantics> </math> increased by 5.3%, with no statistically significant changes in the beam penumbra width or OFD.</p><p><strong>Conclusion: </strong>The optimal beam collimation and filtration for both x-ray tube focal spot sizes of a kV radiotherapy system was determined using Bayesian optimization and MC simulations and resulted in improved dose ","PeriodicalId":94136,"journal":{"name":"Medical physics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143257701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing gamma-ray detection: Processing grooved microstructures on LYSO crystal with femtosecond laser.","authors":"Xi Zhang, Xin Yu, Hua Cheng, Yuli Wang, Hamid Sabet, Siwei Xie, Jianfeng Xu, Qiyu Peng","doi":"10.1002/mp.17665","DOIUrl":"https://doi.org/10.1002/mp.17665","url":null,"abstract":"<p><strong>Background: </strong>Gamma-ray detection plays a crucial role in the fields of biomedicine, space exploration, national defense, and security. High-precision gamma photon detection relies on scintillation crystals, which attenuate gamma rays through mechanisms such as photoelectric effect and Compton scattering. These interactions generate light signals within the scintillation crystal, which are subsequently converted into electronic signals using photodetectors, enabling accurate readout, and analysis.</p><p><strong>Purpose: </strong>Improving the readout efficiency of visible photons in crystal detectors can significantly improve the efficiency of gamma-ray detection. Scintillator crystals are usually hard and brittle materials, which are difficult to process. In this paper, we innovatively propose the method of using a femtosecond laser to process grooved microstructures on the light output surface of scintillator crystals to improve the detection efficiency, and thus enhance the comprehensive performance of gamma-ray detection.</p><p><strong>Methods: </strong>Optical simulation software is first used to explore the enhancement of the light output performance by the grooved microstructures. Subsequently, a 5-dimension system for femtosecond laser processing of scintillator crystals was constructed, which can achieve accurate processing of grooved structures. Finally, the feasibility of the study was verified by applying grooved microstructure on crystal bars and crystal arrays.</p><p><strong>Results: </strong>TracePro simulation results showed an average efficiency improvement in light output of 33.56% within the groove parameters: spacing from 20 to 140 µm, depth from 8 to 28 µm, and width from 10 to 30 µm. A custom-designed readout electronic system for gamma detection and a laser processing platform was then constructed to evaluate the feasibility of applying grooved structures to the lutetium-yttrium oxyorthosilicate (LYSO) crystal surface. According to the simulation results, 12 groups of crystal bars were fabricated with spacings from 60 to 140 µm, depths from 7 to 16 µm, and widths from 11 to 14 µm. Experimental results showed an average improvement of 20.4% in light output for the crystal bars, and that of the crystal arrays can be improved by 6.85% on average.</p><p><strong>Conclusions: </strong>This study introduces a method of using femtosecond lasers to fabricate grooved microstructures on LYSO crystal surfaces, which has demonstrated a significant improvement in light output in both simulation and experimentation. This method can be applied to the production of crystal arrays at a low cost and on a large scale, showing promising potential for common gamma detection applications, such as medical imaging, industry, and astrophysics.</p>","PeriodicalId":94136,"journal":{"name":"Medical physics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143257636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatial resolution improvements for photon counting detectors using coincidence counting and frequency weighted reconstruction.","authors":"Scott S Hsieh, Katsuyuki Taguchi, Shuai Leng, Cynthia H McCollough","doi":"10.1002/mp.17664","DOIUrl":"https://doi.org/10.1002/mp.17664","url":null,"abstract":"<p><strong>Background: </strong>Photon counting X-ray detectors (PCDs) provide better spatial resolution than energy integrating X-ray detectors, but even higher resolution is desired in some applications. Certain charge sharing compensation techniques such as coincidence counting preferentially detect photons that arrive at the boundary between pixels, and this could be used for subpixel localization of incident photons and enhanced spatial resolution.</p><p><strong>Purpose: </strong>To estimate improvements to spatial resolution and detective quantum efficiency that are possible when using coincidence counting for high-resolution, non-spectral imaging.</p><p><strong>Methods: </strong>The modulation transfer function (MTF), noise power spectrum (NPS), and detective quantum efficiency (DQE) were estimated using numerical simulations of a two-dimensional parallel-beam CT system. Coincidence counters were modeled either geometrically or with Monte Carlo simulations. The geometric model consisted of narrow coincidence counters that interlaced with wider ordinary pixels, and showed that using standard filtered backprojection decreases low-frequency DQE, but that a frequency weighting technique could be used to restore DQE. The Monte Carlo simulations were used to estimate the possible improvements that could be expected from real systems. The pixel pitch was 0.25 mm and the source apertures considered were 0, 0.125, and 0.5 mm. A numerical stent phantom was also used to illustrate possible improvements.</p><p><strong>Results: </strong>Assuming a 0.125 mm source aperture and the Monte Carlo model, the limiting MTF (at 10%) increased from 20 to 40 lp/cm using coincidence counters. This can be explained by the increased sampling (and higher Nyquist limit) possible from coincidence counters. In the geometric model, coincidence counters are compared to conventional double sampling techniques such as in-plane flying focal spot, and the MTF at 38 lp/cm increased from 5% to 53%. Without the frequency weighting technique, low-frequency DQE was reduced by about 20%, but these losses are recovered with frequency weighting. Improvements are much more modest with the 0.25 mm source aperture because the system becomes source-limited.</p><p><strong>Conclusions: </strong>Coincidence counting could be used to increase spatial resolution in PCDs. The increases in system resolution could be large if a high-resolution X-ray source were available.</p>","PeriodicalId":94136,"journal":{"name":"Medical physics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143256489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Absorbed dose differences between twin fetuses for pregnancy patients in CT examinations.","authors":"Shuiyin Qu, Haoran Jia, Habib Zaidi, Tianwu Xie","doi":"10.1002/mp.17659","DOIUrl":"https://doi.org/10.1002/mp.17659","url":null,"abstract":"<p><strong>Background: </strong>Estimation of the radiation dose to the fetus is essential for the assessment of radiation risks and benefits to pregnant patients undergoing radiological examinations. During the past decade, the global twinning rate has soared resulting from embryo assistance and increased delivery age. However, to the best of our knowledge, radiation dosimetry in multiple pregnancies from radiological imaging has never been reported before.</p><p><strong>Purpose: </strong>The purpose of this study is to develop personalized computational models for twin fetuses based on clinical CT images of real pregnant patients and to estimate personalized radiation doses for twin fetuses from abdominal/pelvic CT examinations.</p><p><strong>Methods: </strong>Personalized computational phantoms representing pregnant females with twins at the second and third trimesters were constructed based on CT images of two pregnant patients. Monte Carlo calculations were performed using the MCNP transport code and three validated CT scanners to estimate the radiation dose of twin fetuses during abdominal and pelvic CT examinations.</p><p><strong>Results: </strong>The absorbed fetal organ dose was calculated and compared between twins. For the same patient, the absolute difference in fetal organ dose between twins varies between 0.63% and 39.64% with an average value of 12.85%. The estimated total-body dose differences for twin fetuses were 11.55% and 7.51%, respectively, for pregnant patients at 22 and 30 weeks gestational age.</p><p><strong>Conclusion: </strong>The variations of body weight and organ mass affect the absorbed dose of twin fetuses. Personalized computational models provide more accurate fetal radiation dosimetry estimates for pregnant patients with twins. This work also contributes to a better understanding of model-induced uncertainties in external radiation dosimetry for the developing fetus.</p>","PeriodicalId":94136,"journal":{"name":"Medical physics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143257696","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of porous lung substitute on linear energy transfer (LET) assessed via Monte Carlo simulation and CR-39 measurement with a carbon-ion beam.","authors":"Jingfang Zhao, Bo Chen, Michael Moyers, Zhiyuan Yang, Shiyan Yang, Weiwei Wang","doi":"10.1002/mp.17671","DOIUrl":"https://doi.org/10.1002/mp.17671","url":null,"abstract":"<p><strong>Background: </strong>Carbon-ion beam radiotherapy offers substantial physical and biological advantages due to its distinct Bragg peak (BP) depth dose distribution and higher linear energy transfer (LET) in the peak region that enhances its efficacy in tumor eradication compared to x-ray beams. Porous structures, such as those found in lung and lung-equivalent tissues, unfortunately, introduce significant uncertainties in both dose and LET distributions, which current treatment planning systems (TPS) inadequately address.</p><p><strong>Purpose: </strong>This study aims to investigate the effects of porous lung-equivalent structures on LET distribution using Monte Carlo (MC) simulations and CR-39 measurements. It seeks to understand how porous structures influence LET spectra and dose-averaged LET (LET_d) in carbon-ion beams.</p><p><strong>Methods: </strong>A Gammex LN300 phantom and a binary voxel virtual phantom composed of water and air were used to represent lung-equivalent tissues for measurements and MC simulations. LET spectra measured with CR-39 at different depths within the LN300 slabs were compared with MC-calculated LET_d distributions. The impact of porous structures on dose and LET_d distributions was evaluated using various beam configurations, including single-beam and multi-beam setups. Additionally, a convolution method with modulation power (P_mod) was proposed to improve LET_d prediction in porous media.</p><p><strong>Results: </strong>The study demonstrated that porous structures broaden both the dose and LET_d distributions, especially around the BP region. Multiple beam angles helped mitigate dose degradation but did not resolve discrepancies in the LET_d distributions. Compared with calculation results based on CT images, intensity-modulated particle therapy (IMPT) using a distal LET_d patching method in porous structure increased the median LET_d in the target from 67.2 to 69.6 keV/µm, and the minimum LET_d from 51.5 to 58.0 keV/µm, respectively. Moreover, to improve the prediction of LET_d in porous structures, analytical convolution-based predictions showed good agreement with the MC simulations, with mean LET_d deviations of -1.9% ± 1.6% in the plateau, -3.1% ± 4.9% in the BP, and -1.1% ± 7.7% in the tail region.</p><p><strong>Conclusions: </strong>Porous lung-equivalent structures significantly affect LET_d distributions in carbon-ion therapy, as confirmed by both CR-39 measurements and MC simulations. IMPT with LET_d optimization may be more impacted by porous structures in terms of median and minimum LET_d values within the target. The Gaussian convolution function shows promise for enhancing LET_d calculation accuracy, but further validation in anatomically complex models is needed to assess its clinical feasibility.</p>","PeriodicalId":94136,"journal":{"name":"Medical physics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143256092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fast and accurate peak skin dose estimation method for interventional fluoroscopy patients.","authors":"Haegin Han, Seth W Streitmatter, Cari M Kitahara, Choonsik Lee","doi":"10.1002/mp.17667","DOIUrl":"https://doi.org/10.1002/mp.17667","url":null,"abstract":"<p><strong>Background: </strong>In fluoroscopy, particularly fluoroscopically guided interventions (FGIs), accurate estimation of peak skin dose (PSD) is crucial for identifying potential radiation-induced skin injuries. Most current methodologies for PSD calculation methods rely on analytical methods, which may introduce uncertainty due to their limited consideration of the complexities of x-ray beam conditions, patient geometry, and positioning. Methods based on full Monte Carlo (MC) simulations can enhance accuracy, but their practical application is limited due to the intensive requirement of computational resources and time.</p><p><strong>Purpose: </strong>We aimed to develop a novel method that combines MC simulation with a noise reduction technique to calculate PSD, as well as skin dose distributions, more efficiently and accurately. The goal was to overcome the limitations of current methods, providing a more practical solution for clinical and academic use.</p><p><strong>Methods: </strong>Our method to calculate the PSD and skin dose distributions consists of two steps of rough MC simulation and iterative noise reduction. The performance of the methodology was demonstrated for six fluoroscopy scenarios, with results compared against those from full MC simulation with high particle history, which is considered a gold standard for radiation dosimetry relative to conventional analytical methods.</p><p><strong>Results: </strong>Our method was demonstrated for various fluoroscopy scenarios, and the result showed that the iterative noise reduction procedure successfully estimates PSD and skin dose distribution for rough MC simulations with a maximum dose statistical error of up to 20%. For successful dose estimations, PSD discrepancies from the values obtained by full MC simulation were within 3%, and voxel-wise dose differences in skin dose distributions were less than 10% of the average skin dose. The computation time of our method was on the order of a few seconds on a personal computer, which is estimated to be at least 10⁴ times faster than full MC simulation when using the same computing resources.</p><p><strong>Conclusion: </strong>Our method rapidly and accurately calculates PSD and skin dose distribution, making it a useful tool for research and clinical applications. The planned integration of our method into the National Cancer Institute Dosimetry System for Radiography and Fluoroscopy (NCIRF) will enhance accessibility. Additionally, future upgrades of NCIRF will include a comprehensive phantom library and pregnant phantoms that will enable our method to account for patient-specific body shapes, further improving the accuracy and personalization in dose assessments.</p>","PeriodicalId":94136,"journal":{"name":"Medical physics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143257658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Chan-Vese aided fuzzy C-means approach for whole breast and fibroglandular tissue segmentation: Preliminary application to real-world breast MRI.","authors":"Syed Furqan Qadri, Chao Rong, Mubashir Ahmad, Jing Li, Salman Qadri, Syeda Shamaila Zareen, Zeyu Zhuang, Salabat Khan, Hongxiang Lin","doi":"10.1002/mp.17660","DOIUrl":"https://doi.org/10.1002/mp.17660","url":null,"abstract":"<p><strong>Background: </strong>Magnetic resonance imaging (MRI) is a highly sensitive modality for diagnosing breast cancer, providing an expanding range of clinical usages that are crucial for the care of women at elevated risk of breast cancer development. Segmentation of the whole breast and fibroglandular tissue (FGT), used to evaluate breast cancer risk, is often manually delineated by radiologists in clinical practice. In this paper, we aim to substitute handcrafted breast density segmentation and categorization. The traditional fuzzy C-means (FCM) enable automatic segmentation but may be susceptible to heterogeneity or sparse FGT distribution in MRI.</p><p><strong>Purpose: </strong>We develop a new automated technique for the segmentation of whole breast and FGT for the coronal-view MRI.</p><p><strong>Methods: </strong>We propose a Chan-Vese (CV) aided FCM segmentation approach for estimating the FGT in the whole breast using fat-suppressed (FS) precontrast T1-weighted breast MRI. We present a methodology pipeline comprising region-of-interest (ROI) extraction, nonparametric non-uniform intensity normalization N4 algorithm-based intensity inhomogeneity correction, skin-layer extraction, and then whole breast and FGT segmentation. Our approach involves the FCM algorithm to assign membership degrees to pixels, distinguishing FGT regions from surrounding adipose tissues by assessing their probability of belonging to specific FGT regions, and subsequently, the region-based active contour CV model leverages these membership degrees to direct contour evolution and enhance segmentation boundaries. The proposed method adeptly tackles common challenges in MRI, including blurred edges, low contrast, and intensity inhomogeneity, with efficiency.</p><p><strong>Results: </strong>We evaluated our approach on the Duke Breast Cancer MRI data (DBCM-data) and achieved good segmentation accuracy in terms of Dice similarity coefficient (DSC), Intersection-over-Union (IoU), and Sensitivity (SEN). Our method demonstrates significant accuracy, achieving a DSC (%) of 93.2 ± 3.3 and 84.1 ± 4.9, IoU (%) of 86.4 ± 3.5 and 73.2 ± 5.1, and SEN 87.3 ± 4.1 and 76.7 ± 4.1 for the segmentations of whole breast and FGT, respectively.</p><p><strong>Conclusion: </strong>Our results demonstrated that the CV-aided FCM approach significantly outperformed the existing methods and resulted in significantly more accurate whole breast and FGT segmentation in MRI data.</p>","PeriodicalId":94136,"journal":{"name":"Medical physics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143257631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Patient- and fraction-specific magnetic resonance volume reconstruction from orthogonal images with generative adversarial networks.","authors":"Hideaki Hirashima, Dejun Zhou, Nobutaka Mukumoto, Haruo Inokuchi, Nobunari Hamaura, Mutsumi Yamagishi, Mai Sakagami, Naoki Mukumoto, Mitsuhiro Nakamura, Keiko Shibuya","doi":"10.1002/mp.17668","DOIUrl":"https://doi.org/10.1002/mp.17668","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Although deep learning (DL) methods for reconstructing 3D magnetic resonance (MR) volumes from 2D MR images yield promising results, they require large amounts of training data to perform effectively. To overcome this challenge, fine-tuning-a transfer learning technique particularly effective for small datasets-presents a robust solution for developing personalized DL models.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Purpose: &lt;/strong&gt;A 2D to 3D conditional generative adversarial network (GAN) model with a patient- and fraction-specific fine-tuning workflow was developed to reconstruct synthetic 3D MR volumes using orthogonal 2D MR images for online dose adaptation.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;A total of 2473 3D MR volumes were collected from 43 patients. The training and test datasets were separated into 34 and 9 patients, respectively. All patients underwent MR-guided adaptive radiotherapy using the same imaging protocol. The population data contained 2047 3D MR volumes from the training dataset. Population data were used to train the population-based GAN model. For each fraction of the remaining patients, the population model was fine-tuned with the 3D MR volumes acquired before beam irradiation of the fraction, named the fine-tuned model. The performance of the fine-tuned model was tested using the 3D MR volume acquired immediately after the beam delivery of the fraction. The model's input was a pair of axial and sagittal MR images at the isocenter level, and the output was a 3D MR volume. Model performance was evaluated using the structural similarity index measure (SSIM), peak signal-to-noise ratio (PSNR), root mean square error (RMSE), and mean absolute error (MAE). Moreover, the prostate, bladder, and rectum in the predicted MR images were manually segmented. To assess geometric accuracy, the 2D Dice Similarity Coefficient (DSC) and 2D Hausdorff Distance (HD) were calculated.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;A total of 84 3D MR volumes were included in the performance testing. The mean ± standard deviation (SD) of SSIM, PSNR, RMSE, and MAE were 0.64 ± 0.10, 93.9 ± 1.5 dB, 0.050 ± 0.009, and 0.036 ± 0.007 for the population model and 0.72 ± 0.09, 96.2 ± 1.8 dB, 0.041 ± 0.007, and 0.028 ± 0.006 for the fine-tuned model, respectively. The image quality of the fine-tuned model was significantly better than that of the population model (p &lt; 0.05). The mean ± SD of DSC and HD of the population model were 0.79 ± 0.08 and 1.70 ± 2.35 mm for prostate, 0.81 ± 0.10 and 2.75 ± 1.53 mm for bladder, and 0.72 ± 0.08 and 1.93 ± 0.59 mm for rectum. Contrarily, the mean ± SD of DSC and HD of the fine-tuned model were 0.83 ± 0.06 and 1.29 ± 0.77 mm for prostate, 0.85 ± 0.07 and 2.16 ± 1.09 mm for bladder, and 0.77 ± 0.08 and 1.57 ± 0.52 mm for rectum. The geometric accuracy of the fine-tuned model was significantly improved than that of the population model (p &lt; 0.05).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt;By employing a patient- and fraction-specific f","PeriodicalId":94136,"journal":{"name":"Medical physics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143191659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}