Med Phys [JOURNAL]
Sun
200 papers
A deep-learning-based pipeline for automatic fusion of CT coronary angiogram and stress perfusion CMR.
Jiang W, Ng MY, Sin TH … +1 more , Cao P
Med Phys · 2026 Apr · PMID 41960741 · Full text
BACKGROUND: Accurate evaluation of coronary artery constriction and myocardial ischemia is essential for diagnosing and managing coronary artery disease (CAD). Combining CT coronary angiography (CTCA) and stress cardiova...
BACKGROUND: Accurate evaluation of coronary artery constriction and myocardial ischemia is essential for diagnosing and managing coronary artery disease (CAD). Combining CT coronary angiography (CTCA) and stress cardiovascular magnetic resonance (CMR) imaging allows examination of both coronary artery narrowing and myocardial perfusion. PURPOSE: To develop a deep learning pipeline that integrates CTCA and CMR images, which could help improve accuracy in identifying affected vessels and their associated myocardial territories. METHODS: The proposed pipeline included two deep learning models: one for automatic reorientation of 3D CTCA and another for left ventricle (LV) wall registration between CTCA and CMR images. A 3D spatial co-registration model, the reorientation spatial transformer network (Reorientation STN), predicted reorientation parameters for input CTCA volumes using ResNet18 and STN. A 2D nonrigid spatial deformation network (Nonrigid SDN) was trained for LV wall registration. Cross-modal supervision was employed during training. Evaluation criteria included aspect ratio (AR), Dice similarity coefficient (DSC), and long-axis deviation angles. The process involved quantifying LV wall perfusion on registered CMR images and extracting coronary arteries from reoriented CTCA images to fuse these results. The pipeline was trained and validated on 447 pairs of CTCA and CMR images from 75 patients and tested on 18 subjects. RESULTS: The pipeline achieved an AR of 0.94 ± 0.03, long-axis deviation angles of 1.19 ± 0.83 (axial) and 1.54 ± 0.79 (coronal), a DSC of 0.66 ± 0.04 for LV wall reorientation, and a DSC of 0.92 ± 0.03 for LV wall registration between CTCA and CMR. CONCLUSIONS: This automated framework successfully fuses cardiac CTCA and CMR imaging, demonstrating its potential effectiveness.
Accurate iodine quantification and residual error reduction with principal component analysis multimaterial decomposition using spectral CT.
Khodajou-Chokami H, Ding H, Molloi S
Med Phys · 2026 Apr · PMID 41960726 · Full text
BACKGROUND: Multimaterial decomposition (MMD) in dual-energy CT enables iodine quantification, critical for diagnostic applications. However, residual errors from noniodine materials in iodine maps limit accuracy, especi...
BACKGROUND: Multimaterial decomposition (MMD) in dual-energy CT enables iodine quantification, critical for diagnostic applications. However, residual errors from noniodine materials in iodine maps limit accuracy, especially in complex thoracic regions and low-dose settings. PURPOSE: To evaluate iodine quantification accuracy and residual error using a principal component analysis multimaterial decomposition (PCA-MMD) algorithm on dual-energy CT data across different phantom sizes and radiation dose levels. METHODS: A thorax phantom containing iodine (2-20 mg/mL) and calcium (50-400 mg/mL) inserts was scanned on a clinical photon-counting CT system. Three phantom sizes (small: 20.9 cm, medium: 27.3 cm, large: 33.2-cm water-equivalent diameter) were imaged at dose levels ranging from 3 to 55 mGy. The PCA-MMD algorithm applies a principal component analysis (PCA) transformation followed by direct geometric estimation with barycentric coordinates, thereby avoiding matrix inversion instability. Iodine quantification was evaluated using linear regression, root mean square error (RMSE), and coefficient of variation (CV). Residual error in noniodine regions was expressed as a percentage of the minimum detectable iodine concentration. The algorithm's performance was also evaluated through a clinical proof-of-concept study involving five patients, comparing virtual noncontrast (VNC) images to true noncontrast (TNC) references. RESULTS: PCA-MMD achieved near-unity regression slopes (0.98-0.99, ) across all phantom sizes, reducing RMSE by up to 65% compared to the standard barycentric coordinate-based MMD (0.10-0.39 vs. 0.20-0.72 mg/mL). Residual error was markedly lower with PCA-MMD (0.7-1.6%) than with the standard barycentric coordinate-based MMD (16.1%-54.9%) under identical conditions. At 3 mGy, PCA-MMD achieved an RMSE of 0.60 mg/mL versus 0.95 mg/mL for the standard barycentric coordinate-based MMD. In the clinical cohort, PCA-MMD significantly improved VNC accuracy, achieving a mean RMSE of 15.5 HU compared to 20.9 HU for the vendor-specific algorithm ( ). Reproducibility was excellent, with 85% of the measurements showing a CV . CONCLUSIONS: PCA-MMD significantly improved iodine quantification accuracy and reduced residual error in both phantom and clinical settings. Its robustness across different dose levels supports its potential for clinical translation in quantitative dual-energy CT applications.
Evaluation of extrapolation chamber response for surface and buildup dose assessment in radiotherapy photon beams using Monte Carlo simulations.
Reis CQM, Muir BR, Nicolucci P … +1 more , Rogers DWO
Med Phys · 2026 Apr · PMID 41944461 · Full text
BACKGROUND: Surface dose assessment is essential in radiotherapy, but accurately measuring doses in the buildup region of megavoltage beams presents significant challenges. Extrapolation chambers are frequently regarded...
BACKGROUND: Surface dose assessment is essential in radiotherapy, but accurately measuring doses in the buildup region of megavoltage beams presents significant challenges. Extrapolation chambers are frequently regarded as the most suitable detectors for this purpose. PURPOSE: To establish under what conditions extrapolation chambers can be used to measure surface doses and to use Monte Carlo calculations to prove that measured surface-to-maximum ionization ratios correspond to absorbed-dose ratios. A secondary purpose is to understand why surface measurements with a Markus fixed parallel-plate chamber are inaccurate. METHODS: EGSnrc applications were used for calculating the dose to the air cavity of two extrapolation chambers in a polystyrene phantom as a function of the electrode separation (also called gap), , between 0.1 and 10 mm. Doses to the phantom, , at depths corresponding to the effective point of measurement (EPOM) of the chambers were also calculated. Calculations were performed using clinical photon beams ( , 6, 10, and 25 MV) that were fully modeled using BEAMnrc. Calculated chambers' responses as a function of the gap were compared with experimental data from the literature. Variations of the replacement correction factor ( ) and the wall perturbation factor ( ) as functions of electrode separation and depth in the buildup region were also investigated. RESULTS: Calculated %dose to the air in the chamber's cavity (% ) and measured % ionization from the literature at the polystyrene's surface (i.e., at a depth z = EPOM) agreed to within 2%-3% across all gap sizes and beam qualities. Differences between measured % ionization and calculated % at the phantom surface, were less than 4% (relative to ). For small gaps mm, the calculated chamber response (% ) closely matched the calculated dose to the phantom material (% ), differing by less than 0.9% (relative to ) with deviating from unity by 1%-6% depending on chamber's design and beam energy. At shallow depths (0.01 mm), exhibited the largest variation, increasing by 43% for gaps from 0.1 to 10 mm. In contrast, and stopping-power ratios varied by less than 2.0% and 1.2%, respectively. All correction factors remained approximately constant for small electrode separations ( mm). The Markus chamber exhibited maximum calculated and measured over-responses of 16.2% and 18.2% for and 3.0% and 3.4% for 25 MV, all within the first half of the buildup region. CONCLUSIONS: Surface dose assessment using extrapolation chambers can achieve accuracy within 1% when small electrode separations are used and depth is appropriately defined. The results confirm that the measured % ionization ratios for gaps mm are constant because perturbation effects are minimized. Extrapolation from larger gaps is unreliable due to increasing changes in and extrapolation is only needed to establish where % ionization ratios become constant for small gaps and are hence accurate. Surface measurements with fixed parallel-plate chambers are inaccurate if the gap size is too large.
XACT-guided interventional procedures: A feasibility study.
Yan Y, Pandey PK, Xu Y … +4 more , Sun L, Abi-Jaoudeh N, Wang Z, Xiang SL
Med Phys · 2026 Apr · PMID 41937299 · Full text
BACKGROUND: X-ray Induced Acoustic Computed Tomography (XACT) is an emerging imaging technique that provides 3D volumetric images from a single projection by detecting X-ray-induced acoustic (XA) waves with ultrasound (U...
BACKGROUND: X-ray Induced Acoustic Computed Tomography (XACT) is an emerging imaging technique that provides 3D volumetric images from a single projection by detecting X-ray-induced acoustic (XA) waves with ultrasound (US) transducers. Unlike MRI or CT, XACT enables real-time 3D imaging without long acquisition times, 2D limitations, or motion artifacts from mechanical rotation. Furthermore, when integrated with conventional pulse-echo US through time-sequenced operation, XACT provides complementary soft-tissue contrast, establishing it as a promising platform for dynamic interventional radiology (IR) guidance. PURPOSE: This study aims to evaluate the feasibility of XACT as a novel imaging tool for IR, specifically for guiding needle placement and monitoring contrast agent dynamics. METHODS: We developed a 3D XACT imaging system equipped with a 256-element 2D matrix array and a portable X-ray tube to visualize needle insertion and contrast agent dynamics. To capture both needle position and soft tissue anatomy, we integrated a dual-modality system combining XACT with pulse-echo US using a 128-element linear US array. Experiments were conducted on both tissue-mimic phantoms and soft tissue samples. GPU-accelerated algorithm has been developed for 3D XACT image reconstruction. RESULTS: The results demonstrate the 3D capabilities of XACT imaging for interventional procedures, including monitoring of needle placement and tracking of contrast agent dynamics. The imaging speed reached up to 3∼4 s per frame, constrained by the repetition rate of the X-ray source and signal to noise ratio. The dual-modality approach provided clear visualization of the needle's position and the surrounding soft tissue structures, achieving imaging resolution around 2 mm. CONCLUSIONS: This study demonstrates that XACT imaging is feasible to be used for IR. Its 3D imaging capability with faster imaging speed would be an alternative to cone beam CT and its capability to combine US imaging will provide richer information for soft tissue.
Direct estimation of activity concentration in regional voxels with application to Lu peptide receptor radionuclide therapy.
Gustafsson J, Larsson E, Sjögreen Gleisner K
Med Phys · 2026 Apr · PMID 41937276 · Full text
BACKGROUND: Quantitative SPECT in radionuclide-therapy is limited by partial-volume effects (PVEs). The implementation of regional voxels (r.v.), estimating mean activity concentrations in regions directly from projectio...
BACKGROUND: Quantitative SPECT in radionuclide-therapy is limited by partial-volume effects (PVEs). The implementation of regional voxels (r.v.), estimating mean activity concentrations in regions directly from projections, offers a promising alternative for the geometry-specification to reduce PVEs. PURPOSE: This study aims to demonstrate that activity-concentration estimation with r.v. is superior to reconstruction with cuboid voxels (cu.v.) with post-reconstruction partial-volume correction (PVC) for estimation of activity concentration in Lu peptide receptor radionuclide therapy (Lu-PRRT). METHODS: Data originated from one patient administered [Lu]Lu-DOTA-TOC with SPECT acquired at 1 d, 4 d and 7 d p.i. stored in list-mode format (dataset PA), and eight patients given [Lu]Lu-DOTA-TATE with SPECT acquired 1 d p.i. (dataset PB). Activity concentration was estimated from reconstruction with cu.v. and using r.v. for both datasets, with multiple noise realizations for PA using bootstrapping. Organ delineation was performed based on CT using the AI tool TotalSegmentator, and tumor delineation made in cu.v. SPECT images. The estimated activity concentration for kidneys, spleen, and tumors from r.v. was compared to that obtained with cu.v. with and without post-reconstruction PVC. To study the accuracy of activity-concentration estimates, simulations were performed with the SIMIND Monte Carlo program with patient images used as basis. The sensitivity to misalignments between SPECT and CT was also evaluated. RESULTS: For both patient and simulated data, activity concentrations estimated with r.v. are higher than those from cu.v., with comparable standard deviations. Mean relative errors for simulated images from PA relative to simulation input at 1 d p.i. reconstructions with r.v. are (-4.6 ± 1.4) %, (3.0 ± 0.5) %, (0.1 ± 0.5) %, and (5.6 ± 1.2) % for tumor, left kidney, right kidney, and spleen, respectively. Corresponding results for cu.v. with post-reconstruction PVC are (-12.3 ± 2.2) %, (-4.2 ± 0.6) %, (-7.0 ± 0.5) %, and (-2.1 ± 1.1) %. For simulated images based on PB, the mean relative errors obtained for r.v. are (-3.1 ± 3.5) %, (1.2 ± 1.2) %, (-1.7 ± 1.1) %, and (2.3 ± 0.8) %, while for cu.v. with PVC they are (-7.9 ± 6.7) %, (-5.8 ± 1.9) %, (-9.0 ± 1.0) %, and (-0.7 ± 2.6) %. CONCLUSIONS: Regional voxels are superior to cu.v. for estimation of the activity concentration in organs in Lu-PRRT and demonstrates lower sensitivity to misregistration errors. For tumors, r.v. yields lower systematic errors than cu.v. but demonstrates a higher sensitivity to image segmentation errors for volumes below approximately 10 mL.
Evaluation of a water phantom detector-applicator setup for independent experimental verification of Ru ocular brachytherapy applicators.
Dahlander S, Andrássy M, Frömberg D … +2 more , Persson L, Tedgren ÅC
Med Phys · 2026 Apr · PMID 41937265 · Full text
BACKGROUND: Ru ophthalmic brachytherapy (BT) applicators are used for treating ocular tumors. While manufacturer-provided dosimetry data is commonly used for treatment planning, independent quality assurance (QA) measure...
BACKGROUND: Ru ophthalmic brachytherapy (BT) applicators are used for treating ocular tumors. While manufacturer-provided dosimetry data is commonly used for treatment planning, independent quality assurance (QA) measurements are crucial. However, there is a lack of dedicated equipment and standardized protocols for clinical verification of Ru depth-dose distributions. PURPOSE: The BetaCheck-106™ is a prototype compact water phantom detector-applicator setup enabling high precision alignment of Ru applicators and detectors. We assess the setup's compatibility with three commercially available detectors (microSilicon, microSilicon X and microDiamond) and its performance in determining full 1D depth-current curves with these detectors. In addition, data from clinical QA-tests of 20 Ru applicators was used to estimate inhomogeneities in the applicator's Ru coating. METHODS: Measurements were conducted on two Ru applicators with different activity levels, one had been in clinical service for one year and one was measured before clinical use. Dose rates were recorded at 1 mm intervals from 2 mm to 10 mm in water using the BetaCheck-106™ setup with the three detectors. Measurement precision and detector response were analyzed. Separately, inter-applicator variability was analyzed using the aforementioned measurements of 20 Ru applicators. RESULTS: The BetaCheck-106™ demonstrated exceptional setup reproducibility (0.23%), enabling precise depth-resolved measurements. Both of the silicon diode detectors examined provided stable and reproducible measurements. The diamond detector performed reproducibly for the high-activity applicator but exhibited depth-dependent signal instability for the low-activity source, likely due to the detector's lower sensitivity. Normalized depth-signal curves for the three detectors all had similar shape. Analysis of measured current per activity of 20 Ru applicators revealed a depth dependent inhomogeneity effect decreasing with depth. CONCLUSIONS: The BetaCheck-106™ provides practical high-reproducibility positioning of detector and applicator for Ru applicator measurements in water. The silicon detectors successfully characterized both high and low activity applicators up to 10 mm water depth. The diamond detector proved viable for measurements of the applicator with activity 17.8-18.4 MBq, but it lost stability with depth when measuring the one-year old 8.3 MBq activity applicator.
Direct optimization of the probability of lesion origin in proton treatment planning for low-grade glioma patients.
Ortkamp T, Sallem H, Harrabi S … +4 more , Frank M, Jäkel O, Bauer J, Wahl N
Med Phys · 2026 Apr · PMID 41933418 · Full text
BACKGROUND: In proton therapy of low-grade glioma (LGG) patients, contrast-enhancing brain lesions (CEBLs) on magnetic resonance imaging are considered predictive of late radiation-induced lesions. From the observation t...
BACKGROUND: In proton therapy of low-grade glioma (LGG) patients, contrast-enhancing brain lesions (CEBLs) on magnetic resonance imaging are considered predictive of late radiation-induced lesions. From the observation that CEBLs tend to concentrate in regions of increased dose-averaged linear energy transfer (LET) and proximal to the ventricular system, the probability of lesion origin (POLO) model has been established as a multivariate logistic regression model for the voxel-wise probability prediction of the CEBL origin. PURPOSE: To date, leveraging the predictive power of the POLO model for treatment planning relies on hand tuning the dose and LET distribution to minimize the resulting probability predictions. In this paper, we therefore propose automated POLO model-based treatment planning by directly integrating POLO calculation and optimization into plan optimization for LGG patients. APPROACH: We introduce an extension of the original POLO model including a volumetric correction factor, and a model-based optimization scheme featuring a linear reformulation of the model together with feasible optimization functions based on the predicted POLO values. The developed framework is implemented in the open-source treatment planning toolkit matRad. RESULTS: Our framework can generate clinically acceptable treatment plans while automatically taking into account outcome predictions from the POLO model. It also supports the definition of customized POLO model-based objective and constraint functions. Optimization results from a sample LGG patient show that the POLO model-based outcome predictions can be minimized under expectable shifts in dose, LET, and POLO distributions, while sustaining target coverage ( , ), even when NTCP is strongly downregulated. CONCLUSION: POLO model-based treatment plan optimization for LGG patients can be implemented in a technically feasible way, alleviating the need to hand tune the dose and LET distribution. Future work should address multipatient follow-up studies.
Performance benchmarking of deep learning models for real-time median nerve segmentation and cross-sectional area measurement in ultrasound imaging.
Venkatesh V, Bathala L, Mathew RS … +1 more , Yalavarthy PK
Med Phys · 2026 Apr · PMID 41933401 · Publisher ↗
BACKGROUND: Median nerve, a major peripheral nerve, connects the hand to the central nervous system, facilitating upper limb motor function and sensation by transmitting sensory data from the palm and fingers. Damage to...
BACKGROUND: Median nerve, a major peripheral nerve, connects the hand to the central nervous system, facilitating upper limb motor function and sensation by transmitting sensory data from the palm and fingers. Damage to this nerve can result in motor and sensory deficits, with carpal tunnel syndrome (CTS) causing compression, leading to tingling and numbness in the thumb, index, middle, and lateral ring fingers. PURPOSE: This study aimed to develop an accurate deep-learning-based segmentation method for measuring the cross-sectional area (CSA) of the median nerve to facilitate the diagnosis of nerve entrapment syndromes and aid in surgical planning, with a focus on CTS. METHODS: This study introduces MNSeg-Net, a novel lightweight multiscale feature fusion network with 2.46M parameters for median nerve segmentation in ultrasound (US) frames, specifically designed to enable a fully automated, end-to-end clinical setup supporting real-time segmentation and CSA computation. The dataset comprised 100 subjects and 30 000 ultrasound frames, which were split into training (80%), validation (10%), and testing (10%) subsets with subject-wise separation to avoid data leakage. MNSeg-Net was benchmarked against state-of-the-art segmentation models, including UNet and its variants (UNet++ and U2Net). The performance was assessed using metrics such as the Dice similarity coefficient (DSC) and CSA difference. The statistical significance of performance differences was evaluated using paired t-tests, effect size (Cohen's d), and one-way ANOVA with Tukey's HSD correction for multiple comparisons at a -value threshold of 0.05, while statistical equivalence between models within predefined margins was formally assessed using the two one-sided test (TOST) procedure. Following quantitative validation, the model was deployed in a real-time clinical setup utilizing an Av.io HD Epiphan frame grabber to stream ultrasound images from the ultrasound machine to a GPU-equipped system. A secondary display running parallel to the original ultrasound screen visualized the segmented median nerve and computed the CSA values in real time. RESULTS: MNSeg-Net achieved high segmentation performance, with average DSC scores of 94.7% at the wrist and 83.4% from the wrist to the elbow, and the lowest Hausdorff distance, matching the performance of the best-performing 44-million-parameter heavy U2Net model. Compared to U2Net, MNSeg-Net showed no statistically significant difference in DSC performance ( ; Cohen's ; mean difference = -0.001), with formal equivalence testing confirming equivalence across all tested margins ( ). For CSA estimation, MNSeg-Net also showed no statistically significant difference from clinician-annotated values ( ; Cohen's ; mean difference = -0.081), and equivalence was established at the margin, confirming a strong alignment with expert clinical assessments. MNSeg-Net demonstrated real-time performance by processing up to 43 frames per second on a single GPU, successfully segmenting the median nerve and computing CSA from ultrasound frames. CONCLUSION: The developed MNSeg-Net-based clinical system represents an important step toward real-time median nerve assessment, enabling a fully automated solution for CTS diagnosis. By combining a lightweight architecture, real-time processing capability, and successful clinical deployment, it represents a substantial advancement in the CTS detection and management.
Beam-hardening correction in clinical x-ray dark-field chest radiography using deep-learning-based bone segmentation.
Kaster L, Lochschmidt ME, Bauer AM … +5 more , Dorosti T, Demianova S, Koehler T, Pfeiffer D, Pfeiffer F
Med Phys · 2026 Apr · PMID 41933281 · Full text
BACKGROUND: Dark-field radiography is a novel x-ray imaging modality that provides complementary diagnostic information by visualising microstructural properties of lung tissue. Implemented via a Talbot-Lau interferomete...
BACKGROUND: Dark-field radiography is a novel x-ray imaging modality that provides complementary diagnostic information by visualising microstructural properties of lung tissue. Implemented via a Talbot-Lau interferometer integrated into a conventional x-ray system, it permits simultaneous acquisition of perfectly registered attenuation and dark-field radiographs. Clinical studies have shown that dark-field radiography outperforms conventional radiography in diagnosing and staging pulmonary diseases, yet the polychromatic nature of medical x-ray sources causes beam hardening and introduces structured artifacts, especially from ribs and clavicles. PURPOSE: To address the artificial dark-field signal arising from beam-hardening and thereby improve the reliability of clinical dark-field chest radiography by suppressing bone-induced artifacts. METHODS: A segmentation-based beam-hardening correction (BHC) was developed that employs deep learning to segment ribs and clavicles and uses attenuation-contribution masks derived from dual-layer detector computed-tomography data to refine the material distribution and estimate beam-hardening effects. The rib segmentation network was trained on 196 chest radiographs with 49 validation images (VinDr-RibCXR), and a clavicle network was trained on 56 images with 12 validation and 12 test cases. The trained models were applied to 174 dark-field chest radiographs (51 chronic obstructive pulmonary disease, 86 COVID-19, 37 healthy) and spectral CT scans from two patients; input data consisted of attenuation and dark-field images and outputs were corrected dark-field images and derived lung-signal metrics. RESULTS: The proposed method markedly reduced bone-induced artifacts and improved the homogeneity of the lung dark-field signal. In comparative analyses, the corrected images exhibited diminished structured cross-talk between attenuation and dark-field channels, enhancing both visual interpretation and quantitative consistency across cohorts. CONCLUSIONS: By combining deep-learning-based anatomical segmentation with material-specific attenuation weighting, the proposed BHC suppresses the artificial dark-field signal caused by polychromatic x-ray spectra, leading to more reliable assessment of pulmonary microstructure in clinical dark-field chest radiography.
Comparing deep learning stroke segmentation in NCCT, CTA, and CTP: Accuracy, domain transfer, and temporal sampling effect.
Vorberg L, Ditt H, Maier A … +3 more , Nicolaou S, Murray N, Taubmann O
Med Phys · 2026 Apr · PMID 41933279 · Full text
BACKGROUND: Stroke imaging typically involves multiple CT image types-non-contrast CT (NCCT), CT angiography (CTA), and CT perfusion (CTP). CTP and multiphase CTA (mCTA) are more advanced acquisitions with multiple times...
BACKGROUND: Stroke imaging typically involves multiple CT image types-non-contrast CT (NCCT), CT angiography (CTA), and CT perfusion (CTP). CTP and multiphase CTA (mCTA) are more advanced acquisitions with multiple timesteps and provide insights on the hemodynamics within the brain. Deep Learning models can help facilitate the diagnostic workflow by automatically identifying the extent of core and penumbra, which influences subsequent treatment decisions. For the use in clinical practice, generalizability of these models to new clinical sites is crucial. PURPOSE: We evaluate and compare the usefulness of NCCT, CTA, mCTA, and CTP images for DL-based stroke lesion segmentation, with the aim of guiding modality selection in settings with and without access to advanced imaging, and with an additional focus on model transferability between clinical sites and the impact of time point selection from the CTP scan. METHODS: The experiments involve model training with a dataset of 91 stroke patients from one clinical site. NCCT, CTA, mCTA, and CTP are used separately to train nnU-Net models for segmentation of stroke core and hypoperfused volume using uncertainty-aware labels. To assess site transferability, a model (pre-)trained on 166 cases from a second clinical site is employed to perform as-is inference with data from the first site, then contrast it with a variant of the model fine-tuned using a subset of the data from the first site. Multiple temporal sampling strategies were investigated for the 4D CTP data, choosing different subsets of the time series as the model input. RESULTS: For automatic segmentation of stroke core, advanced imaging techniques yield improved accuracy with the modified Dice coefficient increasing from (NCCT) to (CTA), (mCTA), and (CTP) for infarcts of size 10-70 mL. A similar trend is observed for smaller infarcts of 1-10 mL. In terms of generalizability, the additional fine-tuning stage consistently enhances the segmentation results, regardless of the image type used. To leverage the initially large series of perfusion images, different temporal sampling strategies are applied to predict stroke core. The experiments show no clear trend as the results vary across different timing scenarios and infarct sizes. CONCLUSIONS: The study provides an overview of the quality of automated stroke lesion segmentation with nnU-Net across all relevant CT acquisition types. Hereby, multitimepoint imaging exhibits significantly improved segmentation performance compared to NCCT and CTA.
A simulation study of a novel spiral volumetric modulated arc therapy for enhanced dose delivery efficiency and quality in radiotherapy.
Li K, Zhang W, Ma X … +2 more , Zhou Q, Zhu J
Med Phys · 2026 Apr · PMID 41933273 · Full text
BACKGROUND: Conventional volumetric modulated arc therapy (VMAT) is limited by its longitudinal field size for large targets, often requiring multiple isocenters, while Helical Tomotherapy (HT) offers superior longitudin...
BACKGROUND: Conventional volumetric modulated arc therapy (VMAT) is limited by its longitudinal field size for large targets, often requiring multiple isocenters, while Helical Tomotherapy (HT) offers superior longitudinal conformity but suffers from prolonged treatment times due to its narrow fan beam. PURPOSE: This simulation study proposes a novel spiral volumetric modulated arc therapy (SVMAT) technique designed to bridge this gap by synergizing continuous couch movement with dynamic MLC modulation. METHODS: The SVMAT technique was implemented on a model of ring-gantry linac with dual-layer staggered MLC. Its core is a direct aperture optimization algorithm that discretizes the delivery path into finite projections, concurrently optimizing MLC aperture, monitor unit weight, gantry angle, and couch position. A comprehensive dosimetric and efficiency comparison was conducted against state-of-the-art VMAT and HT plans for three clinically challenging scenarios: hippocampal-sparing whole-brain radiotherapy (HS-WBRT), bilateral breast radiotherapy (BBRT), and craniospinal irradiation (CSI), including a pediatric subgroup. RESULTS: SVMAT demonstrated comparable or superior target coverage and conformity index to VMAT and HT across all cases. Its most significant advantage was in organ-at-risk (OAR) sparing. For HS-WBRT, SVMAT significantly reduced the maximum (D) and mean (D) doses to the hippocampus compared to both VMAT and HT (p < 0.05). For BBRT, SVMAT notably reduced the heart D (4.78 ± 0.86 Gy vs. 9.47 ± 3.44 Gy) for VMAT. In CSI, SVMAT reduced the lens D by over 33% and the heart D by 36.1%. Also, the pediatric CSI analysis confirmed these benefits, with SVMAT significantly reducing doses to developing organs. Regarding efficiency, SVMAT's beam on time was significantly shorter than HT's across all plans (reductions of 33.1% to 55.3%) and was comparable to the multi-isocenter VMAT in CSI. CONCLUSIONS: The SVMAT technique successfully integrates the dynamic delivery of VMAT with the longitudinal integration and single-isocenter capability of HT. By offering enhanced OAR sparing and reduced treatment times, SVMAT represents a significant advancement in radiotherapy, showing immense potential for improving outcomes, especially in vulnerable populations such as pediatric patients.
An efficient method for evaluating the lead equivalence of x-ray radiation protective equipment using an analytical spectrum model.
Surdashi S, Aziz A, Mobini Kesheh S … +2 more , Nilsson JS, Omar A
Med Phys · 2026 Apr · PMID 41933271 · Full text
BACKGROUND: X-ray radiation protective equipment is essential for ensuring the safety of medical staff. It is therefore important to verify its effectiveness, including confirming the specified lead equivalence ( ), as...
BACKGROUND: X-ray radiation protective equipment is essential for ensuring the safety of medical staff. It is therefore important to verify its effectiveness, including confirming the specified lead equivalence ( ), as it is a recognized standard protective value. Current methods require multiple comparative measurements with reference lead sheets, rendering the process laborious, susceptible to errors, and challenging to apply across a large medical facility with diverse protective equipment. PURPOSE: To introduce an efficient method for evaluating lead equivalence based on a computational model involving analytical spectrum modeling. METHODS: The method consists of measuring the transmission of the protective equipment and then translating it into a lead-equivalent thickness using a computational model. In this work, an example implementation is presented utilizing the SpekPy toolkit for spectrum modeling. To validate the method, it was used to estimate the thickness of high-purity lead sheets with known thicknesses (0.1-1.0-mm Pb). Furthermore, its application is demonstrated for two lead-free aprons (0.25- and 0.35-mm ), a lead-vinyl apron (0.5-mm ), a lead-acrylic and a lead-plywood mobile screen (0.5- and 1.0-mm ). Because the approach is based on measuring the transmission utilizing the primary x-ray tube beam (rather than scatter from a phantom), Monte Carlo (MC) simulations were performed to identify x-ray tube settings that reproduce clinically relevant scatter beams. Scatter spectra were simulated for different scatter angles (45 , 90 , 135 ), tube voltages (60-120 kV), and filtration (0.1-1 mm added copper). Analytical primary spectra were then matched to scatter spectra in terms of first and second tenth-value layer (TVL) thicknesses in lead. RESULTS: The method is accurate to within approximately 3% and is suitable for both narrow and broad beams. For broad beams, it is necessary to scale the measured transmission by the buildup factor for lead, as the analytical spectrum model does not account for scatter. This factor, which transfers broad-beam air kerma to narrow-beam air kerma, ranges from 1.0 to 1.5 for 50-120-kV beams incident upon lead sheets with thicknesses of 0.1-1.0 mm. Without this factor, the lead equivalence can be underestimated by up to 28%. Using the method developed, it was found that the effectiveness of lead-free aprons decreases by up to 20% for high-kV and high-filtration beams, while other equipment investigated agreed more closely with specifications. The MC simulations of scatter spectra indicated that scatter beams are generally softer than primary beams, with a reduction in TVL by up to 54% (average of 25%). The entire range of scatter-mimicking primary beams can be realized with tube voltages 50-100 kV and less than 0.3 mm added copper filtration. CONCLUSIONS: The method developed can accurately convert measured transmission into lead equivalence using a computational model, which eliminates the need to handle physical lead sheets. The transmission can be measured using recommended scatter-mimicking x-ray tube beams, derived here for a broader range of scatter angles and clinical beams with higher filtration than has previously been considered.
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Boone JM, Benedict SH
Med Phys · 2026 Apr · PMID 41933266 · Publisher ↗
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Impact of partial volume correction on radiomics reproducibility in theranostic SPECT/CT imaging.
Azimi MS, Cheraghi M, Ghodsi Rad MA … +9 more , Bayat M, Alhashim M, Dadgar H, Alabedi M, Ibrahim N, Alwuhaib E, Arabi H, Rahmim A, Zaidi H
Med Phys · 2026 Apr · PMID 41933215 · Full text
BACKGROUND: Radiomics has shown potential for quantitative characterization of tumors in molecular imaging; however, its clinical translation in theranostic Lu SPECT/CT remains limited due to poor robustness of extract...
BACKGROUND: Radiomics has shown potential for quantitative characterization of tumors in molecular imaging; however, its clinical translation in theranostic Lu SPECT/CT remains limited due to poor robustness of extracted features to reconstruction variability and partial volume effects. Establishing reproducible radiomics biomarkers across correction strategies is therefore a prerequisite for reliable clinical modeling and treatment monitoring. PURPOSE: This study aimed to evaluate radiomics feature reproducibility, defined as the stability of feature values across different partial volume correction (PVC) strategies and reconstruction settings, in clinical Lu SPECT/CT imaging. In addition, we explored two volumetric shape-based indices, the metastasis-to-liver ratio (MLR) and metastasis-to-spare liver ratio (MSLR), as surrogate markers of hepatic metastatic burden in the theranostic treatment setting. METHODS: In 13 patients (40 scans) treated with Lu, 837 radiomics features were extracted from 11 abdominal regions and metastases on SPECT/CT using original and wavelet-decomposed images across four bin widths (50-200). Two post-reconstruction PVC methods, namely Richardson-Lucy (RL) and Reblurred Van Cittert (RVC), were applied. Feature reproducibility was quantified using two complementary metrics: the intraclass correlation coefficient (ICC) to assess feature-level stability across PVC strategies, and the concordance correlation coefficient (CCC) to evaluate pairwise agreement and systematic bias among reconstruction methods. Visual image quality assessments were independently performed by two experienced nuclear medicine specialists in a blinded setting. Exploratory metastatic tumor burden was assessed descriptively using 3D shape-based MLR and MSLR indices. RESULTS: Low-frequency wavelet decomposition (LLL-wavelet) and original features showed the highest reproducibility (ICC ≥ 0.90 in >95% of liver and metastasis features at BW50), whereas high-frequency features and larger bin widths demonstrated reduced stability. CCC analysis revealed excellent agreement between RL and RVC (≥0.95 in major organs at BW50-100), while agreement with uncorrected SPECT (no PVC) was consistently lower, especially for high-frequency features. RL achieved higher visual scores in sharpness and contrast (p < 0.01), with good inter-reader agreement supporting the consistency of these assessments. MLR/MSLR demonstrated inter-patient variability and were explored descriptively as indices of metastatic liver burden. CONCLUSIONS: Reproducibility in theranostic SPECT radiomics is highly feature- and organ-dependent and is further influenced by scanner-specific factors and reconstruction protocols, which remain critical for real-world clinical translation. RL and RVC showed stronger mutual agreements than each with uncorrected SPECT. Importantly, only RVC translated visual improvements into enhanced feature-level reproducibility, while RL provided the most consistent overall balance of reproducibility and image quality, supporting its role as the preferred PVC strategy for clinical and modeling applications. Robust radiomics feature selection as well as standardized reproducible PVC strategies are essential to generate methodological harmonization for future clinical translation and to support integration of radiomics analyses into personalized SPECT theranostics.
On the shape of the radiation survival curve in tumor spheroids: The role of oxygen heterogeneity.
Schneider U, Liang N, Besserer J
Med Phys · 2026 Apr · PMID 41933094 · Full text
BACKGROUND: The shape of cell survival curves at the tissue level remains an open question in radiobiology. While homogeneous cell populations (so-called single cells) typically exhibit an exponential decrease in surviva...
BACKGROUND: The shape of cell survival curves at the tissue level remains an open question in radiobiology. While homogeneous cell populations (so-called single cells) typically exhibit an exponential decrease in survival with increasing dose, it is unclear whether this behavior persists in multicellular systems, where oxygen and nutrient gradients introduce additional complexity. PURPOSE: This study investigates how oxygen diffusion and consumption in tumor spheroids modify the aggregate radiation response and whether the resulting survival curves follow a purely exponential or a linear-quadratic (LQ) form on the logarithmic scale. METHODS: WiDr human colon adenocarcinoma cells were modeled using the track-event theory of cell survival. The parameters p = 0.04 Gy, q = 0.70 Gy, and OER = 3.44 were obtained by fitting oxic and anoxic single-cell data from West et al. Oxygen tension profiles pO2(r) in spheroids were calculated according to the diffusion-consumption model of Grimes et al. using p = 150 Torr, r = 216 µm, and a = 1.27×10 m kg s. Oxygen-dependent, location-specific cellular radiosensitivity was modeled via the oxygen enhancement ratio (OER), and the overall spheroid survival fraction was obtained by integrating survival over the viable spheroid volume, using both numerical calculation and a closed-form analytical approximation. RESULTS: Both the mechanistic oxygen-diffusion-based numerical survival model and the simplified approximation reproduced experimental survival data for WiDr spheroids of diameters 100-1200 µm reported by Buffa et al. and West et al. The predicted survival curves become progressively less steep as spheroid size increases, reflecting the larger hypoxic fraction. For large spheroids, both model and data exhibit a distinct upward curvature of the survival curve at high doses, deviating from both exponential and downward-bending LQ behavior. This effect arises from dose-dependent weighting of oxic and hypoxic cell subpopulations within the heterogeneous spheroid. CONCLUSIONS: The results support the hypothesis that oxygen heterogeneity fundamentally alters the apparent dose-response relationship in multicellular systems. The transition from single-cell to spheroid-level behavior introduces non-linear averaging effects that produce survival curves not captured by standard exponential or LQ models. These findings provide a mechanistic bridge between cellular radiobiology and tissue-scale dose-response modeling.
Comparative evaluation of dual-layer spectral CT protocols for mouse chest imaging.
Zhong S, Gao C, Huang Q … +8 more , Wu T, Zhang F, Zheng H, Dong S, Yin Q, Lou X, Wu L, Xu M
Med Phys · 2026 Apr · PMID 41932862 · Publisher ↗
BACKGROUND: Imaging studies using mouse models provide key technical support for dynamic monitoring of lung diseases, and spectral CT provides high-precision tissue contrast and compositional analysis; however, a paramet...
BACKGROUND: Imaging studies using mouse models provide key technical support for dynamic monitoring of lung diseases, and spectral CT provides high-precision tissue contrast and compositional analysis; however, a parameter framework for mouse lung imaging has yet to be established. PURPOSE: This study investigates the effect of the filtering, slice thickness, and spectral parameters on the quality of chest scan images. METHODS: Thirty C57BL/6 mice were selected and allowed to acclimate to conditions inside the animal facility. After conducting Philips spectral CT chest scans on mice weighing 20, 25, and 30 g, six filters and two slice thickness settings were employed for multi-dimensional reconstruction. Using the repeated regions of interest (ROI) measurement method, we systematically evaluated both quantitative and qualitative image quality. Quantitative indicators included CT value, noise level, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). Qualitative scores were assigned to four types of images: virtual monoenergetic images (VMI), virtual unenhanced images (VNC), and effective atomic number maps (z-effective). The Kruskal-Wallis test was used to assess quantitative metrics, whereas the Jonckheere-Terpstra trend test was used to analyze ordinal qualitative scores. RESULTS: Qualitative analysis confirmed no significant differences in body weight across groups. Evaluation of filter settings revealed that among the different spectral CT filter settings, YC and YD produced images with superior sharpness. Conversely, quantitative analysis showed that the filter settings (YC, YD) generated significantly higher noise levels than those of A, B, C, and F. For slice thickness, qualitative assessments preferred the images at 0.67 mm. The analysis of VMIs suggested that 40-keV images had better qualitative quality. Interestingly, quantitative metrics showed that these 40-keV images had the lowest SNR and lung parenchymal CNR among all the energy levels tested. CONCLUSIONS: Our study revealed an apparent paradox between qualitative and quantitative assessments of image quality. Combining the YC/YD filter settings, a 0.67 mm slice thickness, and 40-keV VMIs significantly enhances the Philips spectral CT image quality of mouse chests.
Correction to "Cross-scan fusion network: A registration-based framework for annotation-efficient 3D ultrasound segmentation in low back pain assessment".
Med Phys · 2026 Apr · PMID 41932857 · Publisher ↗
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Passive cavitation imaging with p root coherence factor and sparse arrays: In vitro and in vivo assessment for histotripsy monitoring.
Singh AK, Soni R, Basterrechea KF … +2 more , Bader K, Shekhar H
Med Phys · 2026 Apr · PMID 41925696 · Full text
BACKGROUND: Passive cavitation imaging (PCI) is under development to monitor histotripsy and other cavitation-mediated therapies. Image reconstruction using the conventional delay, sum, and integrate (DSI) beamforming ap...
BACKGROUND: Passive cavitation imaging (PCI) is under development to monitor histotripsy and other cavitation-mediated therapies. Image reconstruction using the conventional delay, sum, and integrate (DSI) beamforming approach produces PCI reconstructions with poor axial resolution and side lobe artifacts. Robust capon beamforming (RCB) improves imaging performance but is computationally expensive. Nonlinear beamforming approaches such as p root delay sum integrate (prDSI) and delay multiply and sum (DMAS) beamforming offer comparable or better performance than RCB without extensive computational overhead. However, enhancing imaging performance without compromising frame rates remains an active research area. PURPOSE: This work reports a coherence-factor modified with p root algebra p coherence factor-weighted delay sum and integrate (pCFwDSI) and evaluates its performance in vitro and in vivo. To reduce computational complexity, sparse array imaging was implemented with 32 and 16 transducer elements. We also employed graphical processing unit (GPU) computation to achieve real time frame rates. METHODS: Histotripsy bubble clouds were generated in vitro in a red blood cell-doped phantom and in vivo in a porcine femoral vein using focused sources with 1 MHz and 1.5 MHz center frequencies. The acoustic emissions were received passively with a curvilinear (C5-2v) and linear (L11-5v) array transducer, respectively. Beamforming was performed using RCB, prDSI, and pCFwDSI with 128, 32 and 16 elements. The performance achieved was compared using the following metrics: -6 dB axial width, signal-to-interference ratio (SIR), binary statistical analysis, and structural similarity index measure (SSIM). RESULTS: The pCFwDSI approach performed the best in terms of axial width and SIR, and prDSI showed intermediate performance between pCFwDSI and RCB. For binary statistical metrics, the performance achieved with p = 3 and 128 elements was similar for both approaches (within 2% of each other). In sparse array images implemented with 16 elements, grating lobes were observed in RCB and prDSI, but were suppressed in pCFwDSI. The SSIM of the sparse array (16 elements) with pCFwDSI (p = 3) was 96.34% relative to the images generated with the full aperture of 128 elements. Frame rates ranged from 18 to 91 Hz for pCFwDSI using RF data from 128 to 16 elements, respectively, which were similar to standard DSI. CONCLUSIONS: These results demonstrate pCFwDSI can improve axial resolution, reduce artifacts, and achieve clinically-relevant frame rates without increasing computational and data storage overhead. These findings could be a step towards enabling improved real time PCI monitoring of histotripsy.
Assessing variations in 3D image quality in chest CT across sites and scanners.
Hernandez AM, Uneri A, Bevins N … +9 more , Kanal K, Zamora D, Supanich M, Maloney B, Mahesh M, McNitt-Gray MF, Kinahan P, Siewerdsen JH, Boone JM
Med Phys · 2026 Apr · PMID 41922272 · Publisher ↗
BACKGROUND: Large CT image databases are critical to the development and validation of protocol harmonization strategies and AI models. However, image quality (IQ) can vary significantly due to differences in technology...
BACKGROUND: Large CT image databases are critical to the development and validation of protocol harmonization strategies and AI models. However, image quality (IQ) can vary significantly due to differences in technology and site practices, even for scanners from the same manufacturer, which can have considerable effects on harmonization efforts and AI algorithm development. Quantifying the 3D IQ variability represented in these databases is essential to characterize protocol heterogeneity, the training data distribution, and to assess test data overlap. PURPOSE: To quantify and characterize sources of 3D IQ variability in chest CT across scanner models and imaging sites. METHODS: A previously-reported phantom and its automated analysis software was employed across 6 sites, 3 CT manufacturers, and 27 scanners (10 unique models) to rigorously quantify IQ metrics, including image noise, image contrast (low-contrast objects: -26 HU, 41 HU; medium: -84 HU; high: 276 HU, 817 HU), the 3D MTF (axial plane and oblique direction), and the 3D NPS. The MTF was summarized using the frequency at 10% modulation "f", and NPS using average frequency "f". Sites were instructed to use their non-contrast chest CT protocols for fixed mAs phantom scanning at CTDI levels of 2.1 (low dose "LD"), 4.2 (MD), and 6.3 mGy (HD), and provide four reconstructions, including standard 'Std' and thin 'Thn' slice thicknesses for sharp "Sh" and soft "So" kernels. Variance component analysis (VCA) was performed on the resulting phantom series to quantify sources of variability in IQ partitioned into inter-scanner model, inter-site, and residual (i.e., unexplained) components. RESULTS: IQ metrics dominated by inter-scanner differences (> 50% of total variance) included image noise for Sh-Std-LD/MD, Sh-Thn-LD, and So-Std/Thn for all doses (51%-84%), high-contrast (276, 817 HU) image contrast for all protocols (68%-93%), medium-contrast image contrast for all MD/HD protocols (64%-88%), low-contrast (-26 HU) image contrast for So-Std-MD (65%) and Sh-Std-LD/MD (64%/51%), axial and oblique for nearly all protocols (58%-88% and 56%-58%, respectively), axial f for Sh-Thn across all dose levels (51%-65%), and oblique f for So-Thn-HD (58%) and So-Thn across all dose levels (56%-91%). Metrics dominated by inter-site differences were image noise for Sh-Std/Thn-HD (57%/58%), low-contrast (41 HU) for So-Std-MD/HD (77%/54%) and Sh-Std-MD (64%), and axial f for So-Thn-LD/MD (54%, 70%). Residual variance was the dominant contributor to variability in medium-contrast image contrast for So/Sh-Std-LD (91%/56%), low-contrast (41 HU, -26 HU) image contrast for So-Std-LD (58%-70%) and Sh-Std-LD/HD (76%/66%), and axial for So-Thn-HD (54%). CONCLUSION: This multisite phantom study demonstrates that substantial, systematic variability in 3D IQ exists across scanners, sites, metrics, dose levels, and reconstruction settings despite use of a routine non-contrast chest CT protocol. Variability was primarily driven by scanner model differences, with additional contributions from inter-site differences and residual variance for select metrics and protocols. Regardless of controlled imaging conditions that limit variability from patient anatomy, size-dependent dose effects, and tube current modulation, substantial variability in 3D IQ persists. The size-specific, relative trends observed in this study emphasize the importance of accounting for scanner model, site, and protocol-specific heterogeneity when using large CT image databases.
Integrated optimization of needle paths and dwell time for individualized template-guided interstitial brachytherapy.
Yao Q, Wang K, Liu B … +4 more , Jiang P, Zhou F, Wang J, Wu Q
Med Phys · 2026 Apr · PMID 41912351 · Publisher ↗
BACKGROUND: 3D-printed individualized template (3D-PIT) guided interstitial brachytherapy (ISBT) is an effective treatment modality for cervical cancer. However, the current practice of pre-operative planning requires ma...
BACKGROUND: 3D-printed individualized template (3D-PIT) guided interstitial brachytherapy (ISBT) is an effective treatment modality for cervical cancer. However, the current practice of pre-operative planning requires manual needle paths design, which is highly dependent on operator experience and may lead to unnecessary insertion trauma. PURPOSE: To address this issue, this study introduces and validates an automated integrated optimization method for needle paths and dwell times for an institutional protocol of 3D-PIT based ISBT for locally recurrent cervical cancer. METHODS AND MATERIALS: To automatically generate a treatment plan, a candidate needle path set was first generated based on patient's anatomy and the transvaginal template. Then, a two-layer optimization strategy was introduced for automated integrated optimization of the needle paths and dwell times, with the outer layer employing simulated annealing to optimize the needle paths, and the inner layer to optimize the dwell times. A total of 40 patient cases (with the prescribed dose to HR-CTV D being 6 Gy (physical dose) per fraction, and 2-8 fractions per case, totaling 219 independent fraction plans) with locally recurrent cervical cancer previously treated with 3D-PIT-assisted ISBT were enrolled in this study. Automatic plans for all fractions were generated and evaluated using the same number of needles as in the clinical plans, with the dosimetric results of the clinical plans used as constraints. In addition, the quality of automatic plans using fewer needles was also investigated. RESULTS: The method generated clinically acceptable plans in 1.5 ± 1.2 min, requiring 145 ± 74 iterations, according to institutional protocols based on the EMBRACE II. In terms of dosimetric quality, the automatic plans met the constraints and generally outperformed the clinical plans in protecting organs-at-risk (OARs). When normalizing both plans to the same HR-CTV D and comparing the dosimetric outcomes of OARs, the D of rectum, bladder, colon, and small intestine were reduced from 363 to 350 cGy, 397 to 376 cGy, 226 to 204 cGy, and 140 to 123 cGy, respectively (all p < 0.001). The D of urethra was reduced from 406 to 351 cGy (p < 0.001). V of HR-CTV remained the same at 78% (p = 0.28), and V of HR-CTV was increased from 42% to 44% (p < 0.001). Total dwell time decreased from 278 to 271 seconds (p < 0.001). In addition, plans with fewer needles generally had higher doses to OARs. CONCLUSIONS: The automated integrated optimization method provides a fast, standardized pre-planning tool for 3D-PIT-assisted ISBT. By reducing operator dependence, it serves as a valuable clinical baseline to help determine optimal needle configurations and maintain consistent dosimetric quality.
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