Medical physics最新文献

{"title":"Feasibility of scan plane tracking using in-bore RGB-D camera(s) for online interventional MRI.","authors":"Fulang Qi, Xiaohan Hao, Penghui Luo, Zheyu Guo, Jianyang Jiang, Jiantai Zhou, Kecheng Yuan, Changliang Wang, Huiyu Du, Yufu Zhou, Bensheng Qiu","doi":"10.1002/mp.17880","DOIUrl":"https://doi.org/10.1002/mp.17880","url":null,"abstract":"<p><strong>Background: </strong>Optical navigation systems have been proven useful for image-guided surgeries in clinical settings. Most of the optical sensors track precise locations of landmarks on surgical instruments and thus are costly, limiting its widespread adoption. Magnetic Resonance Imaging (MRI) is not only excellent in soft tissue contrast but also has the capability of unrestricted multiplanar imaging.</p><p><strong>Purpose: </strong>This study aims to develop an affordable navigation method for MRI-guided interventions by utilizing an in-bore consumer-grade RGB-D camera.</p><p><strong>Methods: </strong>We utilize the camera to track a flat plane pad that is fixed parallel to the surgical tool, typically a needle. This simplifies the navigation process by focusing on locating a scan plane that fully encompasses the needle within the field of view of the MR image, allowing for greater tolerance to tracking deviations. The total cost of the hardware is less than $500.</p><p><strong>Results: </strong>Our proposed method was deployed in a C-shape 0.35T MRI system. The electromagnetic compatibility after integrating the camera was validated by measuring both magnetic field <math> <semantics><msub><mi>B</mi> <mn>0</mn></msub> <annotation>${bf B}_0$</annotation></semantics> </math> homogeneity and image signal-to-noise ratio. In needle-plane tracking experiments, the RGB-D based tracking method demonstrated a maximum distance error of <math> <semantics><mrow><mn>1.32</mn> <mo>±</mo> <mn>0.41</mn></mrow> <annotation>$1.32 pm 0.41$</annotation></semantics> </math>  mm and a maximum angular error of <math> <semantics><mrow><mn>1</mn> <mo>.</mo> <msup><mn>69</mn> <mo>∘</mo></msup> <mo>±</mo> <mn>0</mn> <mo>.</mo> <msup><mn>18</mn> <mo>∘</mo></msup> </mrow> <annotation>$1.69^circ pm 0.18^circ$</annotation></semantics> </math> . Additionally, we simulated ex vivo pig liver biopsy, demonstrating the navigation feasibility of our method in combination with online MRI.</p><p><strong>Conclusions: </strong>Overall, we pioneer a novel RGB-D camera navigation system that makes MRI-guided interventions more accessible in clinical practice at a much lower cost.</p>","PeriodicalId":94136,"journal":{"name":"Medical physics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144082946","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":"Design optimization and simulated performance evaluation of a self-collimated cardiac SPECT with simultaneous high sensitivity and resolution.","authors":"Debin Zhang, Li Cheng, Yifan Hu, Zhenlei Lyu, Lei Wang, Wei Fang, Rutao Yao, Tianyu Ma","doi":"10.1002/mp.17877","DOIUrl":"https://doi.org/10.1002/mp.17877","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Cardiac single photon emission computed tomography (SPECT) is an important noninvasive molecular imaging technology for the diagnosis and risk stratification of heart diseases. However, since its inception, the clinical impact of cardiac SPECT has been constrained by its reliance on mechanical collimation using a metal apertured-plate structure, which causes an inherent inverse interdependency between the system's resolution and sensitivity. Recently, our group introduced self-collimation (SC) detector architecture in single photon emission imaging: in a structure with multiple layers of sparsely distributed active detector elements, certain detectors also function as collimators for others. We have shown that SPECT with SC detector architecture transcends the performance of its counterpart with conventional mechanical collimation.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Purpose: &lt;/strong&gt;This study aims to (1) produce the blueprint of a cardiac SC-SPECT system that achieves high sensitivity and resolution simultaneously, and (2) evaluate the system's performance through Monte Carlo simulation studies.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;Based on our prior SC-SPECT studies and general design considerations for cardiac imaging, we choose a half-hexagon configuration, comprising three identical trapezoid-shaped detector heads, for the detector gantry of the cardiac SC-SPECT. The targeted field of view (FOV) is a spherical volume with a diameter of 190 mm. Each detector head includes a tungsten plate on the side facing the FOV, followed by four stacked detector layers with spacing between each layer. With the distance from the fourth detector layer to the center of FOV, as well as the size of individual detector scintillators fixed, we use an established system resolution and variance evaluation scheme to optimize detector configuration parameters, namely, the placement positions of the first three detector layers, the distribution pattern of the apertures and aperture to metal ratio on the tungsten plate. The SC-SPECT with the set of optimized configuration parameters is then evaluated with a set of simulated phantom studies, and the results are compared against that of a conventional dual-head SPECT system. The phantoms include a hot-rod phantom, a cold-rod phantom, and a XCAT phantom configured for emulating various myocardial ischemia conditions under realistic injection dose and variable acquisition times.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;A cardiac SC-SPECT design with optimized parameters is obtained. The system achieves an average sensitivity of 0.54% within the FOV, and can clearly resolve hot rods with a diameter of 4 mm and cold rods with a diameter of 5 mm. In contrast, the conventional SPECT system exhibits an average sensitivity of 0.02% in the FOV, resolves 6 mm diameter hot rods and none of the cold rods (4-9 mm) with a body-contour orbit, and resolves 5 mm diameter hot rods and 7 mm diameter cold rods with a 150 mm radius circular o","PeriodicalId":94136,"journal":{"name":"Medical physics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144048698","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":"Volumetric soft tissue perfusion assessment on a region basis from x-ray angiography images: Motion compensation.","authors":"Katsuyuki Taguchi, Shalini Subramanian, Andreia V Faria, W Paul Segars","doi":"10.1002/mp.17870","DOIUrl":"https://doi.org/10.1002/mp.17870","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Assessing the soft tissue perfusion quantitatively in interventional suites before, during, and after interventional procedures is desired. The method, if possible, has to assess the perfusion volumetrically and quantitatively, be robust against lesion overlaps and patient motion, require no additional radiation dose, be quick (possibly in real-time), and fit to the clinical workflow well. We have developed a method called IPEN (for Intra-operative PErfusion assessment with No gantry rotation) that has potential to accomplish all of the desired goals except for the patient motion. The innovation with IPEN is not to reconstruct volumetric images, but to estimate enhancement of multiple three-dimensional regions-of-interest directly from x-ray projections acquired at one angle.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Purpose: &lt;/strong&gt;To further develop the IPEN method such that it can compensate for patient motion when the patient moves quickly during the angiography scan but stays still otherwise.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;The proposed motion-compensating IPEN (MCI) consists of the following three steps: (Step 1) The time segment is broken into multiple segments, that is, a set of rapid motion segments and a set of stationary segments; (Step 2) the MCI estimates ROI enhancement within each stationary segment; and (Step 3) MCI connects segments. The performance of the proposed MCI and the original IPEN were assessed using the digital perfusion phantom, simulating 13 ischemic stroke \"patients.\" The head moved within 0.6 s each time, and seven times during 16-s scans; motion magnitude parameter a (for ± a mm and ± a degrees) was 0.0 (no motion), 0.5, 2.0, 5.0, and 25.0 for each scan. The accuracy of time-enhancement curves (TECs) and calculated perfusion-like parameter (\"max-slope\" for the maximum of slope of TEC; similar to Patlak plot analysis) was assessed. In addition, the effect of the motion segments on the accuracy of the estimated TEC has been studied systematically.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Head motion induced very severe inconsistency and artifact in synthesized digital subtraction angiography images. The original IPEN had disjoint TECs, and the correlation coefficients (r) against the true values decreased from 0.475 at a = 0.5 to 0.023 at a = 25.0. The proposed MCI provided smooth and accurate TECs with r = 0.995 at a = 0.5 and r = 0.989 at a = 25.0. The 𝓁&lt;sub&gt;2&lt;/sub&gt;-norm of the error vectors of the max-slope values was 5.6-64.2 (d.l.) for the original IPEN, whereas it was &lt; 0.1 for the MCI for the motion magnitudes investigated. There was an strong linear relationship between the non-linearity of the derivative of TECs and biases in TEC: r was 0.999. MCI would have a significant bias when a lengthy motion occurs when an ROI enhancement changes non-linearly during the time.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt;The proposed MCI can compensate for the patient motion very effectively and accurately when the motion is not ","PeriodicalId":94136,"journal":{"name":"Medical physics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144059180","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":"Characterization of a Commercial Ionization Chamber Array With Scanned Proton Beams for Applications in MRI-Guided Proton Therapy.","authors":"Benjamin Gebauer, Sebastian Gantz, Daniela Kunath, Aswin Hoffmann, Jörg Pawelke, Felix Horst","doi":"10.1002/mp.17875","DOIUrl":"https://doi.org/10.1002/mp.17875","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;The integration of MRI-guidance and proton therapy is a current research topic. Proton therapy with the patient being placed inside an in-beam MR scanner would require the presence of its static magnetic ( &lt;math&gt; &lt;semantics&gt;&lt;msub&gt;&lt;mi&gt;B&lt;/mi&gt; &lt;mn&gt;0&lt;/mn&gt;&lt;/msub&gt; &lt;annotation&gt;$B_0$&lt;/annotation&gt;&lt;/semantics&gt; &lt;/math&gt; ) field to be taken into account in dose calculation and treatment planning. Therefore, dosimetric tools are needed to characterize dose distributions in presence of the &lt;math&gt; &lt;semantics&gt;&lt;msub&gt;&lt;mi&gt;B&lt;/mi&gt; &lt;mn&gt;0&lt;/mn&gt;&lt;/msub&gt; &lt;annotation&gt;$B_0$&lt;/annotation&gt;&lt;/semantics&gt; &lt;/math&gt; field of the MR scanner. Furthermore, patient-specific quality assurance (QA) and treatment plan verification measurements should also be performed within the magnetic field.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Purpose: &lt;/strong&gt;In this work, the PTW Octavius 1500 &lt;math&gt; &lt;semantics&gt;&lt;msup&gt;&lt;mrow&gt;&lt;/mrow&gt; &lt;mrow&gt;&lt;mi&gt;M&lt;/mi&gt; &lt;mi&gt;R&lt;/mi&gt;&lt;/mrow&gt; &lt;/msup&gt; &lt;annotation&gt;$^{MR}$&lt;/annotation&gt;&lt;/semantics&gt; &lt;/math&gt; ionization chamber array was characterized experimentally and tested for its suitability as a dosimetric tool for beam characterization and QA in MRI-guided proton therapy.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;The dose rate response, response homogeneity and effective measurement depth of the detector were determined in experiments with scanned proton beams delivered by a horizontal beamline at OncoRay, Dresden. A patient-specific QA test including gamma analysis was performed for a realistic proton patient treatment plan at two different distances from the beam nozzle. In addition, experiments were performed in a &lt;math&gt; &lt;semantics&gt;&lt;mrow&gt;&lt;mn&gt;0.32&lt;/mn&gt; &lt;mspace&gt;&lt;/mspace&gt; &lt;mi&gt;T&lt;/mi&gt;&lt;/mrow&gt; &lt;annotation&gt;$0.32 mathrm{T}$&lt;/annotation&gt;&lt;/semantics&gt; &lt;/math&gt; in-beam MR scanner. These included measurements of square reference scanning patterns at different proton energies as well as measurements of a two-field patient treatment plan at different water equivalent depths.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;The dose rate response was found to be linear up to &lt;math&gt; &lt;semantics&gt;&lt;mrow&gt;&lt;mn&gt;80&lt;/mn&gt; &lt;mspace&gt;&lt;/mspace&gt; &lt;mtext&gt;Gy/min&lt;/mtext&gt;&lt;/mrow&gt; &lt;annotation&gt;$80 text{Gy/min}$&lt;/annotation&gt;&lt;/semantics&gt; &lt;/math&gt; . The effective measurement depth was determined to be &lt;math&gt; &lt;semantics&gt;&lt;mrow&gt;&lt;mn&gt;8.1&lt;/mn&gt; &lt;mo&gt;±&lt;/mo&gt; &lt;mn&gt;0.2&lt;/mn&gt; &lt;mspace&gt;&lt;/mspace&gt; &lt;mi&gt;mm&lt;/mi&gt;&lt;/mrow&gt; &lt;annotation&gt;$8.1 pm 0.2 mathrm{mm}$&lt;/annotation&gt;&lt;/semantics&gt; &lt;/math&gt; . The response homogeneity was found to be suitable for the verification of proton treatment plans. The patient-specific QA test without magnetic field was satisfactory and also the measurements inside the &lt;math&gt; &lt;semantics&gt;&lt;mrow&gt;&lt;mn&gt;0.32&lt;/mn&gt; &lt;mspace&gt;&lt;/mspace&gt; &lt;mi&gt;T&lt;/mi&gt;&lt;/mrow&gt; &lt;annotation&gt;$0.32 mathrm{T}$&lt;/annotation&gt;&lt;/semantics&gt; &lt;/math&gt; in-beam MR scanner provided reasonable results. Their comparison allowed an assessment of the magnetic field effects on the dose distributions.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Concluding from these tests, the Octavius 1500 &lt;math&gt; &lt;semant","PeriodicalId":94136,"journal":{"name":"Medical physics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144016011","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":"Inference-specific learning for improved medical image segmentation.","authors":"Yizheng Chen, Sheng Liu, Mingjie Li, Bin Han, Lei Xing","doi":"10.1002/mp.17883","DOIUrl":"https://doi.org/10.1002/mp.17883","url":null,"abstract":"<p><strong>Background: </strong>Deep learning networks map input data to output predictions by fitting network parameters using training data. However, applying a trained network to new, unseen inference data resembles an interpolation process, which may lead to inaccurate predictions if the training and inference data distributions differ significantly.</p><p><strong>Purpose: </strong>This study aims to generally improve the prediction accuracy of deep learning networks on the inference case by bridging the gap between training and inference data.</p><p><strong>Methods: </strong>We propose an inference-specific learning strategy to enhance the network learning process without modifying the network structure. By aligning training data to closely match the specific inference data, we generate an inference-specific training dataset, enhancing the network optimization around the inference data point for more accurate predictions. Taking medical image auto-segmentation as an example, we develop an inference-specific auto-segmentation framework consisting of initial segmentation learning, inference-specific training data deformation, and inference-specific segmentation refinement. The framework is evaluated on public abdominal, head-neck, and pancreas CT datasets comprising 30, 42, and 210 cases, respectively, for medical image segmentation.</p><p><strong>Results: </strong>Experimental results show that our method improves the organ-averaged mean Dice by 6.2% (p-value = 0.001), 1.5% (p-value = 0.003), and 3.7% (p-value < 0.001) on the three datasets, respectively, with a more notable increase for difficult-to-segment organs (such as a 21.7% increase for the gallbladder [p-value = 0.004]). By incorporating organ mask-based weak supervision into the training data alignment learning, the inference-specific auto-segmentation accuracy is generally improved compared with the image intensity-based alignment. Besides, a moving-averaged calculation of the inference organ mask during the learning process strengthens both the robustness and accuracy of the final inference segmentation.</p><p><strong>Conclusions: </strong>By leveraging inference data during training, the proposed inference-specific learning strategy consistently improves auto-segmentation accuracy and holds the potential to be broadly applied for enhanced deep learning decision-making.</p>","PeriodicalId":94136,"journal":{"name":"Medical physics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144016013","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":"Field dispersion in uniformly-excited radial parallel plate waveguides for a compact proton accelerator design.","authors":"Morgan J Maher, Christopher M Lund, Julien Bancheri, David G Cooke, Jan Seuntjens","doi":"10.1002/mp.17868","DOIUrl":"https://doi.org/10.1002/mp.17868","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Proton therapy (PT) is a beneficial modality for treating certain cancers but remains under utilized due in part to the high cost of existing PT devices. Dielectric wall accelerators (DWAs) are a proposed class of coreless induction accelerators that may present a suitable option for compact and affordable PT. To realize a compact device, acceleration modules must be designed to achieve field strengths approaching 100 MV/m delivered as pulses on the order of nanoseconds.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Purpose: &lt;/strong&gt;Here, we examine pulse injection into radial parallel plate waveguides as a means of producing high-intensity, pulsed accelerating fields. We present an approach for understanding the impact of waveguide properties on electromagnetic dispersion as well as a means of accounting for this dispersion to produce suitable accelerating fields.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;Geometric and material properties for a set of waveguides were identified based on existing literature and commonly available materials. An analytic model is presented to describe how waveguide geometry and material affect electromagnetic dispersion in a waveguide. Simulations performed in COMSOL Multiphysics are used to calculate a transfer function for the set of waveguides, which provide a means of determining the waveguides output for arbitrary inputs and vice versa. The simulation results are compared to the analytic solution and used to explore alternate matching conditions at the beampipe of the accelerator.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Overall, radial waveguides provide a passive enhancement of the injected pulse, with enhancement of high-frequency components found to be proportional to the square root of the ratio of outer radius to inner radius of the waveguide. Dispersion in the waveguide caused by the radial propagation of the pulse depends on multiple waveguide properties (outer radius, inner radius, material) and leads to reduced enhancement at lower frequencies. The field enhancement in the waveguides reduces the peak voltage required to achieve the desired accelerating field strength. However, dispersion alters the temporal profile of the applied pulse, resulting in a distorted field at the inner radius. Using the transfer function, it is possible to determine the shape of the pulse required to achieve a suitable accelerating field for a given waveguide design.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Passive field enhancement occurred in all waveguides and across all frequencies studied in this work. As such, radial parallel plate waveguides could help to reduce the high voltages required from upstream switching networks. The analytic model can be used to select waveguide parameters that provide a suitable enhancement of the upstream voltage pulse to achieve the high field strengths required for a compact accelerator. However, pulse dispersion must be accounted for. If upstream pulse shaping can be achieved to account for electromagnetic ","PeriodicalId":94136,"journal":{"name":"Medical physics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144052527","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":"Generation of synthetic CT from MRI for MRI-based attenuation correction of brain PET images using radiomics and machine learning.","authors":"Amin Hoseinipourasl, Gholam-Ali Hossein-Zadeh, Peyman Sheikhzadeh, Hossein Arabalibeik, Shaghayegh Karimi Alavijeh, Habib Zaidi, Mohammad Reza Ay","doi":"10.1002/mp.17867","DOIUrl":"https://doi.org/10.1002/mp.17867","url":null,"abstract":"<p><strong>Background: </strong>Accurate quantitative PET imaging in neurological studies requires proper attenuation correction. MRI-guided attenuation correction in PET/MRI remains challenging owing to the lack of direct relationship between MRI intensities and linear attenuation coefficients.</p><p><strong>Purpose: </strong>This study aims at generating accurate patient-specific synthetic CT volumes, attenuation maps, and attenuation correction factor (ACF) sinograms with continuous values utilizing a combination of machine learning algorithms, image processing techniques, and voxel-based radiomics feature extraction approaches.</p><p><strong>Methods: </strong>Brain MR images of ten healthy volunteers were acquired using IR-pointwise encoding time reduction with radial acquisition (IR-PETRA) and VIBE-Dixon techniques. synthetic CT (SCT) images, attenuation maps, and attenuation correction factors (ACFs) were generated using the LightGBM, a fast and accurate machine learning algorithm, from the radiomics-based and image processing-based feature maps of MR images. Additionally, ultra-low-dose CT images of the same volunteers were acquired and served as the standard of reference for evaluation. The SCT images, attenuation maps, and ACF sinograms were assessed using qualitative and quantitative evaluation metrics and compared against their corresponding reference images, attenuation maps, and ACF sinograms.</p><p><strong>Results: </strong>The voxel-wise and volume-wise comparison between synthetic and reference CT images yielded an average mean absolute error of 60.75 ± 8.8 HUs, an average structural similarity index of 0.88 ± 0.02, and an average peak signal-to-noise ratio of 32.83 ± 2.74 dB. Additionally, we compared MRI-based attenuation maps and ACF sinograms with their CT-based counterparts, revealing average normalized mean absolute errors of 1.48% and 1.33%, respectively.</p><p><strong>Conclusion: </strong>Quantitative assessments indicated higher correlations and similarities between LightGBM-synthesized CT and Reference CT images. Moreover, the cross-validation results showed the possibility of producing accurate SCT images, MRI-based attenuation maps, and ACF sinograms. This might spur the implementation of MRI-based attenuation correction on PET/MRI and dedicated brain PET scanners with lower computational time using CPU-based processors.</p>","PeriodicalId":94136,"journal":{"name":"Medical physics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144055965","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":"Medical Physics 3.0 approach to optimizing image quality in a breast screening program.","authors":"Elizabeth Keavey, Paola Baldelli, Gillian Power, Niall Phelan","doi":"10.1002/mp.17878","DOIUrl":"https://doi.org/10.1002/mp.17878","url":null,"abstract":"<p><strong>Background: </strong>Sensitivity and specificity of screening mammography is linked to image quality (IQ) and should be optimized and consistent for all women screened. Optimization, typically based on equipment performance metrics from quality control tests, do not correlate directly with clinical performance.</p><p><strong>Purpose: </strong>The principles of Medical Physics 3.0 have been applied to combine medical physics Quality Control (QC) with screening clinical outcome to optimize the quality in a national breast screening program. Medical Physics 3.0 has been advocated as an initiative to enhance the practice of Medical Physics and leverage the value of medical physics to drive improved patient care.</p><p><strong>Methods: </strong>A retrospective analysis of the cancer detection rate (CDR), of approximately 1.5 million screening examinations, was conducted within a screening program following the introduction of a new mammography system type. Significative differences in CDR (with nonoverlapping 95% confidence intervals [CI]) and performance metrics (lower [IQ] and mean glandular dose [MGD]) were observed between this new system type and the other system types in the screening program. The CDR for individual mammography system types was correlated with medical physics QC metrics of IQ and dosimetry. Preliminary investigations lead to an increase of the operational dose multiplier from 1.2 to 1.6 and the new setting was applied over all the new systems.</p><p><strong>Results: </strong>Following optimization, the medical physics metrics revealed a 19% increase in MGD accompanied by a 12% improvement in IQ for the new system type. Meanwhile, a retrospective analysis of CDR showed overlapping 95% CI, indicating convergence between the two system types.</p><p><strong>Conclusions: </strong>Applying Medical Physics 3.0 principles to aggregated screening and clinical outcome data in support of medical physics quality assurance processes has demonstrated potential to deliver optimization of quality for individual women and for the screened population.</p>","PeriodicalId":94136,"journal":{"name":"Medical physics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144035117","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":"Examination of aperture layout designs for an adaptive-stationary multi-pinhole brain-dedicated SPECT system.","authors":"Kesava S Kalluri, Navid Zeraatkar, Benjamin Auer, Sophia Pells, P Hendrik Pretorius, Garrett R Richards, Micaehla May, Neil Momsen, Kimberly Doty, Maria Ruiz Gonzales, Timothy Fromme, Kevin Truong, Matthew A Kupinski, Phillip H Kuo, Lars R Furenlid, Michael A King","doi":"10.1002/mp.17866","DOIUrl":"https://doi.org/10.1002/mp.17866","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Organ specific multi-pinhole (MPH) SPECT imaging could potentially improve the sensitivity/resolution trade-off and image quality (IQ), while facilitating the use of a variety of imaging-agents, thereby addressing diagnostic, quantitative, and research clinical needs.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Purpose: &lt;/strong&gt;Investigate through simulation six different MPH aperture-layout designs, plus variations in projection multiplexing (MUX) and truncation, for a prototype brain-dedicated MPH SPECT system, named AdaptiSPECT-C, to understand tradeoffs for such choices and guide selection of an optimal design for construction of the actual AdaptiSPECT-C system.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;The prototype AdaptiSPECT-C system investigated herein employs 25 MPH gamma-camera modules arranged in three rings to image a 21 cm diameter spherical volume-of-interest (VOI). With a focal point (FP) to center of detector distances of 38.7 cm, the pinhole aperture diameters were constrained to provide a calculated spatial resolution of 8 mm at the FP. Variations in the number of pinhole (PH) apertures, FP to aperture distance, PH layout, temporal changes in MUX, and extent-of-truncation of the projection images were investigated. Designs of the aperture layouts were used to create inputs for GATE and analytic simulations of a sphere phantom with uniform Tc-99 m activity filling the VOI, to assess MUX, detector utilization, and uniformity in reconstructed slices. We investigated axial and angular sampling using customized-spherical Defrise and Derenzo phantoms. Finally, we assessed reconstructed IQ and activity quantification in reconstructions of analytic simulations of the XCAT digital anthropomorphic phantom with activity and attenuation distributions mimicking clinical-SPECT brain-perfusion imaging. For each phantom, comparison was also made to imaging with a dual-headed SPECT system with low-energy high-resolution (LEHR) parallel-hole (Vertex high resolution [VXHR]) collimators.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Sensitivity at the FP (SENS) for a Tc-99 m source in air calculated relative to a clinical dual-headed SPECT system with VXHR collimators was 2.7x higher for a single aperture with no MUX or truncation, increased to 5.7x for five apertures with limited VOI truncation and MUX, and decreased to 2.5x with 13 apertures with limited MUX. For the spherical tub phantom, limited truncation did not impact uniformity, MUX decreased it, and temporal shuttering of projections helped lessen this impact. Visually, the 6.4 mm rods were generally well differentiated for the single central apertures. For designs with four or more apertures, all the 4.8 mm rods were well differentiated visually. Projection images of the XCAT phantom acquired for an imaging time that would result in the minimum clinically recommended count-level for brain perfusion imaging with parallel-hole collimators, showed low MUX of the brain structures for all of the MPH aperture layo","PeriodicalId":94136,"journal":{"name":"Medical physics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144032870","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 tracer uptake rate on quantification accuracy of myocardial blood flow in PET: A simulation study.","authors":"Xiaotong Hong, Amirhossein Sanaat, Yazdan Salimi, René Nkoulou, Hossein Arabi, Lijun Lu, Habib Zaidi","doi":"10.1002/mp.17871","DOIUrl":"https://doi.org/10.1002/mp.17871","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Cardiac perfusion PET is commonly used to assess ischemia and cardiovascular risk, which enables quantitative measurements of myocardial blood flow (MBF) through kinetic modeling. However, the estimation of kinetic parameters is challenging due to the noisy nature of short dynamic frames and limited sample data points.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Purpose: &lt;/strong&gt;This work aimed to investigate the errors in MBF estimation in PET through a simulation study and to evaluate different parameter estimation approaches, including a deep learning (DL) method.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Materials and methods: &lt;/strong&gt;Simulated studies were generated using digital phantoms based on cardiac segmentations from 55 clinical CT images. We employed the irreversible 2-tissue compartmental model and simulated dynamic &lt;sup&gt;13&lt;/sup&gt;N-ammonia PET scans under both rest and stress conditions (220 cases each). The simulations covered a rest K&lt;sub&gt;1&lt;/sub&gt; range of 0.6 to 1.2 and a stress K&lt;sub&gt;1&lt;/sub&gt; range of 1.2 to 3.6 (unit: mL/min/g) in the myocardium. A transformer-based DL model was trained on the simulated dataset to predict parametric images (PIMs) from noisy PET image frames and was validated using 5-fold cross-validation. We compared the DL method with the voxel-wise nonlinear least squares (NLS) fitting applied to the dynamic images, using either Gaussian filter (GF) smoothing (GF-NLS) or a dynamic nonlocal means (DNLM) algorithm for denoising (DNLM-NLS). Two patients with coronary CT angiography (CTA) and fractional flow reserve (FFR) were enrolled to test the feasibility of applying DL models on clinical PET data.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;The DL method showed clearer image structures with reduced noise compared to the traditional NLS-based methods. In terms of mean absolute relative error (MARE), as the rest K&lt;sub&gt;1&lt;/sub&gt; values increased from 0.6 to 1.2 mL/min/g, the overall bias in myocardium K&lt;sub&gt;1&lt;/sub&gt; estimates decreased from approximately 58% to 45% for the NLS-based methods while the DL method showed a reduction in MARE from 42% to 18%. For stress data, as the stress K&lt;sub&gt;1&lt;/sub&gt; decreased from 3.6 to 1.2 mL/min/g, the MARE increased from 30% to 70% for the GF-NLS method. In contrast, both the DNLM-NLS (average: 42%) and the DL methods (average: 20%) demonstrated significantly smaller MARE changes as stress K&lt;sub&gt;1&lt;/sub&gt; varied. Regarding the regional mean bias (±standard deviation), the GF-NLS method had a bias of 6.30% (±8.35%) of rest K&lt;sub&gt;1&lt;/sub&gt;, compared to 1.10% (±8.21%) for DNLM-NLS and 6.28% (±14.05%) for the DL method. For the stress K&lt;sub&gt;1&lt;/sub&gt;, the GF-NLS showed a mean bias of 10.72% (±9.34%) compared to 1.69% (±8.82%) for DNLM-NLS and -10.55% (±9.81%) for the DL method.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Significance: &lt;/strong&gt;This study showed that an increase in the tracer uptake rate (K&lt;sub&gt;1&lt;/sub&gt;) corresponded to improved accuracy and precision in MBF quantification, whereas lower tracer uptake resulted in higher noise in dynamic PET ","PeriodicalId":94136,"journal":{"name":"Medical physics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144056871","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}