Radiation Dose Reduction Research Articles

Dual-Split CT to Simulate Multiple Radiation Doses From a Single Scan-Liver Lesion Detection Compared With Dose-Matched Single-Energy CT.

The aim of this study was to evaluate the potential use of simulated radiation doses from a dual-split CT scan for dose optimization by comparing their lesion detectability to dose-matched single-energy CT acquisitions at different radiation dose levels using a mathematical model observer. An anthropomorphic abdominal phantom with liver lesions (5-10 mm, both hyperattenuating and hypoattenuating) was imaged using a third-generation dual-source CT in single-energy dual-source mode at 100 kVp and 3 radiation doses (5, 2.5, 1.25 mGy). The tube current was 67% for tube A and 33% for tube B. For each dose, 5 simulated radiation doses (100%, 67%, 55%, 45%, 39%, and 33%) were generated through linear image blending. The phantom was also imaged using traditional single-source single-energy mode at equivalent doses. Each setup was repeated 10 times. Image noise texture was evaluated by the average spatial frequency (fav) of the noise power spectrum. Liver lesion detection was measured by the area under the receiver operating curve (AUC), using a channelized Hotelling model observer with 10 dense Gaussian channels. Fav decreased at lower radiation doses and differed between simulated and single-energy images (eg, 0.16 mm-1 vs 0.14 mm-1 for simulated and single-energy images at 1.25 mGy), indicating slightly blotchier noise texture for dual-split CT. For hyperattenuating lesions, the mean AUC ranged between 0.92-0.99, 0.81-0.96, and 0.68-0.89 for single-energy, and between 0.91-0.99, 0.78-0.91, and 0.70-0.85 for dual-split at 5 mGy, 2.5 mGy, and 1.25 mGy, respectively. For hypoattenuating lesions, the AUC ranged between 0.90-0.98, 0.75-0.93, and 0.69-0.86 for the single-energy, and between 0.92-0.99, 0.76-0.87, and 0.67-0.81 for dual-split at 5 mGy, 2.5 mGy, and 1.25 mGy, respectively. AUC values were similar between both modes at 5 mGy, and slightly lower, albeit not significantly, for the dual-split mode at 2.5 and 1.25 mGy. Lesion detectability was comparable between multiple simulated radiation doses from a dual-split CT scan and dose-matched single-energy CT. Noise texture was slightly blotchier in the simulated images. Simulated doses using dual-split CT can be used to assess the impact of radiation dose reduction on lesion detectability without the need for repeated patient scans.

REDUCTION OF POTENTIAL RADIOLOGICAL RISKS FOR PATIENTS UNDERGOING DIAGNOSTIC EXAMS THROUGH MODIFICATION OF THE X-RAY SPECTRUM

The diagnostic medical practice using X-rays significantly contributes to the collective dose worldwide, where the inherent risk in each examination is proportional to the absorbed dose, which is related to deterministic and stochastic effects of ionizing radiation. Therefore, due to the necessity of optimizing each radiological procedure, this study aimed to reduce the absorbed dose in patients undergoing X-ray examinations by evaluating each parameter that modifies the spectral distribution. The Birch and Marshall method was employed to reconstruct and modify the X-ray spectra based on tube voltage, filtration, tube current, anode angle, and energy fluence modulation. By modifying these parameters, it was possible to reduce the absorbed dose in the patient’s skin by up to 38%. The proposed methodology is feasible for implementation in clinical centers, given the availability of copper filters incorporated into X-ray equipment. Additionally, an alternative technique involving tantalum filters is presented, achieving a reduction in absorbed dose of up to 57%. Thus, with the developed methodology, it is demonstrated that it is possible to reduce radiation doses by modifying spectral distributions, reproducing medical images with a significant reduction in the absorbed dose to the patient, while ensuring quality and safety in X-ray diagnostic procedures.

Improving image quality and in-stent restenosis diagnosis with high-resolution "double-low" coronary CT angiography in patients after percutaneous coronary intervention.

This study aims to investigate the image quality of a high-resolution, low-dose coronary CT angiography (CCTA) with deep learning image reconstruction (DLIR) and second-generation motion correction algorithms, namely, SnapShot Freeze 2 (SSF2) algorithm, and its diagnostic accuracy for in-stent restenosis (ISR) in patients after percutaneous coronary intervention (PCI), in comparison with standard-dose CCTA with high-definition mode reconstructed by adaptive statistical iterative reconstruction Veo algorithm (ASIR-V) and the first-generation motion correction algorithm, namely, SnapShot Freeze 1 (SSF1). Patients after PCI and suspected of having ISR scheduled for high-resolution CCTA (randomly for 100 kVp low-dose CCTA or 120 kVp standard-dose) and invasive coronary angiography (ICA) were prospectively enrolled in this study. After the basic information pairing, a total of 105 patients were divided into the LD group (60 patients underwent 100 kVp low-dose CCTA reconstructed with DLIR and SSF2) and the SD group (45 patients underwent 120 kVp standard-dose CCTA reconstructed with ASIR-V and SSF1). Radiation and contrast medium doses, objective image quality including CT value, image noise (standard deviation), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) for the aorta, left main artery (LMA), left ascending artery (LAD), left circumflex artery (LCX), and right coronary artery (RCA) of the two groups were compared. A five-point scoring system was used for the overall image quality and stent appearance evaluation. Binary ISR was defined as an in-stent neointimal proliferation with diameter stenosis ≥50% to assess the diagnostic performance between the LD group and SD group with ICA as the standard reference. The LD group achieved better objective and subjective image quality than that of the SD group even with 39.1% radiation dose reduction and 28.0% contrast media reduction. The LD group improved the diagnostic accuracy for coronary ISR to 94.2% from the 83.8% of the SD group on the stent level and decreased the ratio of false-positive cases by 19.2%. Compared with standard-dose CCTA with ASIR-V and SSF1, the high-resolution, low-dose CCTA with DLIR and SSF2 reconstruction algorithms further improves the image quality and diagnostic performance for coronary ISR at 39.1% radiation dose reduction and 28.0% contrast dose reduction.

An Analysis of Computed Tomography Diagnostic Reference Levels in India Compared to Other Countries.

Computed Tomography (CT) is vital for diagnosing and monitoring medical conditions. However, increased usage raises concerns about patient radiation exposure. Diagnostic Reference Levels (DRLs) aim to minimize radiation doses in CT imaging. This study examines CT DRLs in India compared to other countries to identify optimization opportunities. A literature review was conducted to gather data from published studies, guidelines, and regulatory authorities. Findings show significant international variations in CT DRLs, with differences up to 50%. In India, DRLs also vary significantly across states. For head CT exams, Indian DRLs are generally 20-30% lower than international standards (27-47 mGy vs. 60 mGy). Conversely, for abdominal CT scans, Indian DRLs are 10-15% higher (12-16 mGy vs. 13 mGy). Factors influencing DRL variations include equipment differences, imaging protocols, patient demographics, and regulatory conditions. Dose-optimization techniques like automatic exposure control and iterative reconstruction can reduce radiation exposure by 25-60% while maintaining image quality. Comparative data highlight best practices, such as the United Kingdom's 30% reduction in CT doses from 1984 to 1995 via DRL implementation. This study suggests that adopting similar practices in India could reduce radiation doses by 20-40% for common CT procedures, promoting responsible CT usage and minimizing patient exposure.

Optimizing computed tomography image reconstruction for focal hepatic lesions: Deep learning image reconstruction vs iterative reconstruction

BackgroundDeep learning image reconstruction (DLIR) is a novel computed tomography (CT) reconstruction technique that minimizes image noise, enhances image quality, and enables radiation dose reduction. This study aims to compare the diagnostic performance of DLIR and iterative reconstruction (IR) in the evaluation of focal hepatic lesions. MethodsWe conducted a retrospective study of 216 focal hepatic lesions in 109 adult participants who underwent abdominal CT scanning at our institution. We used DLIR (low, medium, and high strength) and IR (0 %, 10 %, 20 %, and 30 %) techniques for image reconstruction. Four experienced abdominal radiologists independently evaluated focal hepatic lesions based on five qualitative aspects (lesion detectability, lesion border, diagnostic confidence level, image artifact, and overall image quality). Quantitatively, we measured and compared the level of image noise for each technique at the liver and aorta. ResultsThere were significant differences (p < 0.001) among the seven reconstruction techniques in terms of lesion borders, image artifacts, and overall image quality. Low-strength DLIR (DLIR-L) exhibited the best overall image quality. Although high-strength DLIR (DLIR-H) had the least image noise and fewest artifacts, it also had the lowest scores for lesion borders and overall image quality. Image noise showed a weak to moderate positive correlation with participants’ body mass index and waist circumference. ConclusionsThe optimal-strength DLIR significantly improved overall image quality for evaluating focal hepatic lesions compared to the IR technique. DLIR-L achieved the best overall image quality while maintaining acceptable levels of image noise and quality of lesion borders.

Mitigation of Parasitic and Drift Capacitance-Induced Nonlinear Current Responses for Stable and Sensitive Perovskite X-ray Detectors.

The development of perovskite direct X-ray detectors shows potential for advancing medical imaging and industrial inspection precision. To ensure the optimal energy conversion efficiency of X-rays for reducing radiation doses, it is necessary for perovskites with thicknesses reaching hundreds of micrometers or even several millimeters to be utilized. However, the nonlinear current response becomes uncertain with such high thicknesses. For instance, the prevailing theory regarding the rapid trapping and release of charges by shallow-level defects falls short in explaining the nonlinear current response observed in high-quality single-crystal samples. Moreover, a significant nonlinear current response can degrade the detection performance. Here, we elucidate peculiar parasitic and drift capacitance-induced nonlinear current responses in perovskites, which arise from bulk structural deficiencies and interface junction width variation in addition to shallow-level defects. Both theoretical analysis and experimental findings demonstrate the effective suppression of nonlinear current responses by establishing bulk heterojunctions and refining interface junctions. Consequently, we have successfully developed highly linear current-responsive detectors based on polycrystalline MAPbI3 thick films. Notably, these detectors achieve a record sensitivity of 2.3 × 104 μC·Gyair-1·cm-2 under 100 kVp X-ray irradiation with a low bias of 0.1 V/μm, enabling enduring and high-resolution X-ray imaging for high-density objects. Successful fabrication and testing of a 64 × 64-pixel flat-panel prototype detector affirm the widespread applicability of these strategies in rectifying nonlinear current responses in perovskite-based X-ray detectors.

Quantitative Digital Subtraction Angiography Measurement of Arterial Velocity at Low Radiation Dose Rates.

Quantitative digital subtraction angiography (qDSA) has been proposed to quantify blood velocity for monitoring treatment progress during blood flow altering interventions. The method requires high frame rate imaging [~ 30 frame per second (fps)] to capture temporal dynamics. This work investigates performance of qDSA in low radiation dose acquisitions to facilitate clinical translation. Velocity quantification accuracy was evaluated at five radiation dose rates in vitro and in vivo. Angiographic technique ranged from 30 fps digital subtraction angiography ( at the interventional reference point) down to a 30 fps protocol at 23% higher radiation dose per frame than fluoroscopy ( ). The in vitro setup consisted of a 3D-printed model of a swine hepatic arterial tree connected to a pulsatile displacement pump. Five different flow rates (3.5-8.8mL/s) were investigated in vitro. Angiography-based fluid velocity measurements were compared across dose rates using ANOVA and Bland-Altman analysis. The experiment was then repeated in a swine study (n = 4). Radiation dose rate reductions for the lowest dose protocol were 99% and 96% for the phantom and swine study, respectively. No significant difference was found between angiography-based velocity measurements at different dose rates in vitro or in vivo. Bland-Altman analysis found little bias for all lower-dose protocols (range: [- 0.1, 0.1]cm/s), with the widest limits of agreement ([- 3.3, 3.5]cm/s) occurring at the lowest dose protocol. This study demonstrates the feasibility of quantitative blood velocity measurements from angiographic images acquired at reduced radiation dose rates.

Evaluation of the performance of digital x-ray systems in pelvis radiography

The aim of this study was to investigate the performance of eight digital radiography systems and to optimise the dose-image quality relationship for digital pelvis radiography. The study involved eight digital radiography systems used for general examinations at Vilnius University Hospital Santaros Klinikos. An anthropomorphic pelvic phantom (CIRS, US) was used to simulate a patient undergoing clinical pelvis radiography. Dose quantities entrance surface dose, dose area product (DAP) and exposure parameters (kVp, mA, mAs) were measured and the effects on the images were evaluated, considering physical contrast to noise ratio (CNR) and observer-based evaluations as image quality metrics. Increasing the tube voltage by 5 kVp from standard protocol led to a reduction in radiation dose (DAP) by 12%–20% with a slight impact on image quality (CNR decreases by 2%–10%). There was an inter-observer variability in image rating across different equipment (kappa value between 0 and 0.3); however, both observers agreed that increasing kVp up to 85–90 kV had no effect on perceived image quality. The results indicate that optimisation strategies should be tailored specifically for each x-ray system since significant performance differences and wide variations in radiation dose exist across various digital radiography systems used in clinical settings. The use of high kVp can be used for dose optimisation in digital pelvis radiography without compromising image diagnostic accuracy.

Improving diagnostic confidence in low-dose dual-energy CTE with low energy level and deep learning reconstruction

ObjectiveTo demonstrate the value of using 50 keV virtual monochromatic images with deep learning image reconstruction (DLIR) in low-dose dual-energy CT enterography (CTE). MethodsIn this prospective study, 114 participants (62 % M; 41.9 ± 16 years) underwent dual-energy CTE. The early-enteric phase was performed using standard-dose (noise index (NI): 8) and images were reconstructed at 70 keV and 50 keV with 40 % strength ASIR-V (ASIR-V40%). The late-enteric phase used low-dose (NI: 12) and images were reconstructed at 50 keV with ASIR-V40%, and DLIR at medium (DLIR-M) and high strength (DLIR-H). Image standard deviation (SD), signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), edge-rise-slope (ERS) were computed. The quantitative comb sign score was calculated for the 27 patients with Crohn’s disease. The subjective noise, image contrast, display of rectus artery were scored using a 5-point scale by two radiologists blindly. ResultsEffective dose was reduced by 50 % (P < 0.001) in the late-enteric phase to 3.26 mSv. The lower-dose 50 keV-DLIR-H images (SD:17.7 ± 0.5HU) had similar image noise (P = 0.97) as the standard-dose 70 keV-ASIR-V40% images (SD:17.7 ± 0.73HU), but with higher (P < 0.001) SNR, CNR, ERS and quantitative comb sign score (5.7 ± 0.17, 1.8 ± 0.12, 156.04 ± 5.21 and 5.05 ± 0.73, respectively). Furthermore, the lower-dose 50 keV-DLIR-H images obtained the highest score in the rectus artery visibility (4.27 ± 0.6). ConclusionsThe 50 keV images in dual-energy CTE with DLIR provides high-quality images, with a 50 % reduction in radiation dose. Images with high contrast and density resolutions significantly enhance the diagnostic confidence of Crohn’s disease and are essential for the clinical development of individualized treatment plans.

In vitro accuracy of ultra-low dose cone-beam CT for detection of proximal caries.

This study aimed to assess the accuracy of ultra-low dose (ULD) cone-beam CT (CBCT) for detection of proximal caries. This in vitro study evaluated 104 molar and premolar teeth. The teeth were mounted in dry skulls and underwent CBCT with 4 protocols of high-resolution (HR), normal (NORM), ULD-HR, and ULD-NORM; 78 CBCT images were scored by 3 observers for the presence and penetration depth of caries twice with a 2-week interval using a 5-point Likert scale. The teeth were then sectioned and observed under a stereomicroscope (gold standard). The 4 protocols were compared with each other and with the gold standard. The receiver operating characteristic curve was drawn, and the area under the curve (AUC) was calculated and compared by the Chi-square test (alpha = .05). The interobserver agreement ranged from 0.5233 to 0.6034 for ULD-NORM, 0.5380 to 0.6279 for NORM, 0.5856 to 0.6300 for ULD-HR, and 0.6614 to 0.7707 for HR images. The intra-observer agreement ranged from 0.6027 to 0.8812 for ULD-HR, 0.7083 to 0.7556 for HR, 0.6076 to 0.9452 for ULD-NORM, and 0.7012 to 0.9221 for NORM images. Comparison of AUC revealed no significant difference between NORM and ULD-NORM (P > .05), or HR and ULD-HR (P > .05). The highest AUC belonged to HR (0.8529) and the lowest to NORM (0.7774). Considering the significant reduction in radiation dose in ULD CBCT and its acceptable diagnostic accuracy for detection of proximal caries, this protocol may be used for detection of proximal carious lesions and assessment of their depth.

Development and validation of an automated Tomotherapy planning method for cervical cancer

PurposeThis study aimed to develop an automated Tomotherapy (TOMO) planning method for cervical cancer treatment, and to validate its feasibility and effectiveness.Materials and methodsThe study enrolled 30 cervical cancer patients treated with TOMO at our center. Utilizing scripting and Python environment within the RayStation (RaySearch Labs, Sweden) treatment planning system (TPS), we developed automated planning methods for TOMO and volumetric modulated arc therapy (VMAT) techniques. The clinical manual TOMO (M-TOMO) plans for the 30 patients were re-optimized using automated planning scripts for both TOMO and VMAT, creating automated TOMO (A-TOMO) and automated VMAT (A-VMAT) plans. We compared A-TOMO with M-TOMO and A-VMAT plans. The primary evaluated relevant dosimetric parameters and treatment plan efficiency were assessed using the two-sided Wilcoxon signed-rank test for statistical analysis, with a P-value < 0.05 indicating statistical significance.ResultsA-TOMO plans maintained similar target dose uniformity compared to M-TOMO plans, with improvements in target conformity and faster dose drop-off outside the target, and demonstrated significant statistical differences (P+ < 0.01). A-TOMO plans also significantly outperformed M-TOMO plans in reducing V50Gy, V40Gy and Dmean for the bladder and rectum, as well as Dmean for the bowel bag, femoral heads, and kidneys (all P+ < 0.05). Additionally, A-TOMO plans demonstrated better consistency in plan quality. Furthermore, the quality of A-TOMO plans was comparable to or superior than A-VMAT plans. In terms of efficiency, A-TOMO significantly reduced the time required for treatment planning to approximately 20 min.ConclusionWe have successfully developed an A-TOMO planning method for cervical cancer. Compared to M-TOMO plans, A-TOMO plans improved target conformity and reduced radiation dose to OARs. Additionally, the quality of A-TOMO plans was on par with or surpasses that of A-VMAT plans. The A-TOMO planning method significantly improved the efficiency of treatment planning.

DdeNet: A dual-domain end-to-end network combining Pale-Transformer and Laplacian convolution for sparse view CT reconstruction

Sparse view (SV) computed tomography (CT) is a clinical diagnostic technique aimed at reducing radiation dose to the human body from X-rays. However, SVCT reconstructed using conventional filtered back-projection (FBP) algorithms will produce severe streak artifacts. In recent years, convolutional neural networks (CNNs) have demonstrated considerable success in addressing the inverse problem of SVCT reconstruction. However, the local convolutional operations of CNNs ignores long-range dependencies of contextual feature information, thereby limiting their capability in feature extraction. To address this limitation, we propose a dual-domain end-to-end network (DdeNet) combining Pale-Transformer and Laplacian convolution for SVCT reconstruction. Initially, in the projection domain, a UNet is employed to restore the interpolated sinogram. Subsequently, in the image domain, we introduce Pale-Transformer and Laplacian convolution to design a dual-stream feature fusion network for finely restoring the CT images reconstructed by FBP. The dual-stream feature fusion network comprises an image restoration network (IRN) module and an edge enhancement network (EEN) module. The depthwise separable convolution based modified pale-shaped self-attention mechanism in Pale-Transformer captures global feature information of the CT image in the IRN, while the Laplacian convolution and multi-scale convolution block with a squeeze and excitation mechanism in the EEN further extract and restore edge feature information of the CT image. Finally, the feature information output from IRN and EEN is fused along the channel dimension and then convolved to obtain the final reconstructed CT image. Experimental results demonstrate that DdeNet exhibits superior generalization and reconstruction performance compared to the previous CNN or Transformer-based reconstruction methods.

Dose robustness of deep learning models for anatomic segmentation of computed tomography images.

The trend towards lower radiation doses and advances in computed tomography (CT) reconstruction may impair the operation of pretrained segmentation models, giving rise to the problem of estimating the dose robustness of existing segmentation models. Previous studies addressing the issue suffer either from a lack of registered low- and full-dose CT images or from simplified simulations. We employed raw data from full-dose acquisitions to simulate low-dose CT scans, avoiding the need to rescan a patient. The accuracy of the simulation is validated using a real CT scan of a phantom. We consider down to 20% reduction of radiation dose, for which we measure deviations of several pretrained segmentation models from the full-dose prediction. In addition, compatibility with existing denoising methods is considered. The results reveal the surprising robustness of the TotalSegmentator approach, showing minimal differences at the pixel level even without denoising. Less robust models show good compatibility with the denoising methods, which help to improve robustness in almost all cases. With denoising based on a convolutional neural network (CNN), the median Dice between low- and full-dose data does not fall below 0.9 (12 for the Hausdorff distance) for all but one model. We observe volatile results for labels with effective radii less than 19mm and improved results for contrasted CT acquisitions. The proposed approach facilitates clinically relevant analysis of dose robustness for human organ segmentation models. The results outline the robustness properties of a diverse set of models. Further studies are needed to identify the robustness of approaches for lesion segmentation and to rank the factors contributing to dose robustness.

RAdiation Dose Attenuation using RADPAD in CATH lab for primary and secondary operators - RADAR-CATH STUDY.

Radiation injury is an important concern for interventional cardiologists and needs to be addressed. RADPAD is a radiation protection drape that has been shown to reduce the radiation exposure of the primary operator (PO). While Indian data on radiation exposure of the PO in the cath lab are scarce, the exposure of the secondary operator (SO) is even less well studied. The aim of this study was to evaluate the efficacy of RADPAD drapes in reducing radiation doses in the cath lab for the primary as well as the secondary operator. A total of 160 patients (40 patients each with single vessel disease [SVD], double vessel disease [DVD] and triple vessel disease [TVD] undergoing coronary angioplasty, and 40 patients undergoing balloon mitral valvuloplasty [BMV]) were randomised in a 1:1 pattern to undergo a procedure with or without the use of RADPAD. For patients with SVD, DVD and TVD undergoing percutaneous coronary intervention (PCI) and those undergoing BMV, the % reduction with the use of RADPAD reduced the PO's received dose (in mrem) by 65%, 54%, 28% and 67%, respectively, as compared to without RADPAD. The % reduction in relative operator exposure for the PO for the 4 groups was 55%, 34%, 18% and 75%, respectively, with the use of RADPAD. The corresponding % reduction for the SO's received dose (in mrem) was 80%, 63%, 33% and 69% and for relative operator exposure was 74%, 46%, 23% and 76% in the 4 groups, respectively. RADPAD significantly reduces the radiation exposure of the primary and secondary operator during prolonged complex PCI and BMV procedures.

Impact of the Endonaut® Angio-Navigation System on Radiation Exposure in Endovascular Aortic Repair Performed with Mobile C-Arms

Fusion imaging systems have proved to reduce radiation exposure mostly in hybrid rooms but reports with mobile C-arms are few. The aim of this study was to analyze the impact of the Endonaut navigation system on radiation exposure in endovascular aneurysm repair (EVAR) performed with mobile C-arms. All patients undergoing EVAR and/or iliac branched devices implantation between January 2016 and August 2022 were included. All procedures were performed with a mobile C-arm (Siemens Avantic or GE Elite until March 2018, Siemens Cios Alpha thereafter). The Endonaut navigation system has been used since January 2021. Two groups were, therefore, compared: before (control group [CGr]) and after the use of Endonaut. Radiation data including Dose Area Product (DAP) values, Air Kerma (AK) and fluoroscopy time (FT) were collected retrospectively. Overall, 153 patients were included: CGr, n=121; Endonaut group (EnGr), n=32. No significant difference was found between the 2 groups regarding demographic data. DAP values were significantly lower in the EnGr (38Gycm2±24) vs. the CGr (76Gycm2±51) (P<0.05) despite a significantly higher number of complex procedures such as iliac branched devices (P<0.05). AK values were not significantly different between the EnGr and the CGr (196mGy±114 vs. 209mGy±138) as well as FT (33minutes±18 vs. 33minutes±16). Technical success was 97% (31/32) in the EnGr vs. 96% (116/121) in the CGr (P=0.79). The volume of contrast media was significantly lower in the EnGr (94cc±41) vs. the CGr (143cc±66) (P<0.05). In this study, the use of the Endonaut angio-navigation system when performing EVAR with mobile C-arms led to a radiation dose reduction without compromising technical success or procedural time.

Pharyngeal Constrictor-Sparing Salvage Stereotactic Body Radiation Therapy With Tongue-Out for In-Field Recurrence After Definitive Radiation Therapy for Head and Neck Cancer: Guide to Tongue-Out Radiation Therapy

This report details a pharyngeal constrictor muscle (PCM)–sparing stereotactic body radiation therapy (SBRT) using our institutional technique of “tongue-out” radiation therapy (TORT) for treating a local recurrent cancer in the uvula (GTVuvula) in a patient with history of a definitive chemotherapy with radiation therapy (70 Gy with weekly cisplatin) for a locally advanced laryngeal cancer 4 years ago. TORT includes optimizing the patients’ reproducible tongue-out position using readily available medicine cup (30 cc) followed by sculping the thermoplastic mask with tongue-out, and real-time visual monitoring of the tongue position during the computed tomography simulation scan, cone beam computed tomography acquisition, and treatment. Between arcs during volumetric modulated arc therapy, time for tongue relaxation and saliva swallowing can be given to the patient. Without TORT, the patient's GTVuvula abutted the medial aspect of superior PCM (medial-sPCM) and a substantial volume of the previously irradiated superior PCM (sPCM) would have received high radiation dose from this salvage SBRT (32.5 Gy in 5 fractions). Comparing without TORT, the shortest distance between medial-sPCM-to-GTVuvula was increased by 13 mm with TORT, which reduced radiation dose to sPCM in the salvage SBRT plan. The mean dose to sPCM was decreased from 20.5 Gy without TORT to 12.7 Gy with TORT. With TORT, minimal sPCM volumes fell within higher isodose line: volume receiving ≥ 60% prescription dose (V60%Rx), V80%Rx, and V100%Rx to sPCM was, 4.8 versus 0.7 cc (without vs with TORT, respectively), 2.9 versus 0.19 cc, and 1.6 versus 0.04 cc, respectively. Maximum dose (Dmax) to medial-sPCM was 34.6 Gy without TORT versus 22.7 Gy with TORT. These high doses to the sPCM and intrafractional swallowing-related geographic misses of GTVuvula were avoided through the application of TORT in this salvage reirradiation setting. The patient successfully finished salvage SBRT with TORT resulting in no dysphagia or mucositis and maintained complete response at 12 months after treatment.

Evolving Oral Diagnostics: Cone-beam Computed Tomography's (CBCT) Importance in Contemporary Dentistry

Recent improvements in cone-beam computed tomography (CBCT) have transformed maxillofacial imaging, which formerly depended on 2D imaging. This review highlights the benefits of CBCT in many dental specialties, including implant dentistry, endodontics, orthodontics, and temporomandibular joint examination. CBCT provides remarkable diagnostic accuracy while reducing radiation exposure, making it an invaluable tool in the dental practice. Artificial Intelligence and machine learning integration in CBCT technology offers numerous benefits, including automated image analysis, pathology detection, treatment planning, radiation dose reduction, image enhancement, workflow optimization, predictive analytics, personalized treatment plans, tele dentistry, and dental education. AI's role in dentistry is expected to improve diagnostic and therapeutic capacities while optimizing CBCT scans, resulting in better patient care.

HEAL: High-Frequency Enhanced and Attention-Guided Learning Network for Sparse-View CT Reconstruction.

X-ray computed tomography (CT) imaging technology has become an indispensable diagnostic tool in clinical examination. However, it poses a risk of ionizing radiation, making the reduction of radiation dose one of the current research hotspots in CT imaging. Sparse-view imaging, as one of the main methods for reducing radiation dose, has made significant progress in recent years. In particular, sparse-view reconstruction methods based on deep learning have shown promising results. Nevertheless, efficiently recovering image details under ultra-sparse conditions remains a challenge. To address this challenge, this paper proposes a high-frequency enhanced and attention-guided learning Network (HEAL). HEAL includes three optimization strategies to achieve detail enhancement: Firstly, we introduce a dual-domain progressive enhancement module, which leverages fidelity constraints within each domain and consistency constraints across domains to effectively narrow the solution space. Secondly, we incorporate both channel and spatial attention mechanisms to improve the network's feature-scaling process. Finally, we propose a high-frequency component enhancement regularization term that integrates residual learning with direction-weighted total variation, utilizing directional cues to effectively distinguish between noise and textures. The HEAL network is trained, validated and tested under different ultra-sparse configurations of 60 views and 30 views, demonstrating its advantages in reconstruction accuracy and detail enhancement.

Task-based assessment for radiation dose optimization in CT abdominal examinations: A phantom study

Recent advancements in Computed Tomography (CT) imaging technology have significantly enhanced healthcare delivery. However, public concern regarding the safety and health risks associated with increased exposure to ionizing radiation has escalated. In response, this study performs a quantitative analysis comparing the image quality of the standard CT abdomen protocol (P1 protocols) with alternative optimization techniques. Adjustments to standard CT scan parameters, including tube potential (P2 protocols), effective mAs value (P3), and pitch factor (P4, P5, P6 protocols), were made to evaluate the effectiveness of these optimization strategies. A 64-slice CT scanner (Canon, Japan) and a polymethylmethacrylate (PMMA) textural water phantom was utilized in this study. CT dose descriptors, volume weighted CT Dose Index (CTDIvol) and dose-length product (DLP) alongside evaluation parameters such as Hounsfield Unit (HU) number, noise levels, Signal-to-Noise Ratio (SNR), and Contrast-to-Noise Ratio (CNR) were measured and analysed. Furthermore, this research introduced a Figure of Merit (FOM) based on the ratio of image quality parameters (SNR and CNR) to the CTDIvol, establishing a quantitative measure for optimization. A notable reduction in radiation dose—34.85% below the standard protocol (P1)—was observed in protocol P6, attributed to an increased pitch factor. Conversely, increase the effective mAs value has improved SNR and CNR values. The findings reveal that protocols P1 and P2 deliver the highest FOM for soft tissue and fat imaging, respectively. Protocol P1, with its higher attenuation factor, is optimal for abdominal examinations targeting soft tissues. Meanwhile, protocol P2's increase effective mAs value enhances beam intensity, improving CT numbers for fat tissues with their high-density composition. The study also found a strong correlation between FOM based on SNR and CNR values. In conclusion, adjustments to primary CT parameters significantly influence image quality. The FOM serves as an effective tool for measuring the overall performance of image quality, facilitating post-optimization assessment and contributing to the development of safer, more efficient CT imaging protocols.

Dosimetric analysis of six whole-breast irradiation techniques in supine and prone positions

In breast cancer radiation therapy, minimizing radiation-related risks and toxicity is vital for improving life expectancy. Tailoring radiotherapy techniques and treatment positions can reduce radiation doses to normal organs and mitigate treatment-related toxicity. This study entailed a dosimetric comparison of six different external beam whole-breast irradiation techniques in both supine and prone positions. We selected fourteen breast cancer patients, generating six treatment plans in both positions per patient. We assessed target coverage and organs at risk (OAR) doses to evaluate the impact of treatment techniques and positions. Excess absolute risk was calculated to estimate potential secondary cancer risk in the contralateral breast, ipsilateral lung, and contralateral lung. Additionally, we analyzed the distance between the target volume and OARs (heart and ipsilateral lung) while considering the treatment position. The results indicate that prone positioning lowers lung exposure in X-ray radiotherapy. However, particle beam therapies (PBTs) significantly reduce the dose to the heart and ipsilateral lung regardless of the patient’s position. Notably, negligible differences were observed between arc-delivery and static-delivery PBTs in terms of target conformity and OAR sparing. This study provides critical dosimetric evidence to facilitate informed decision-making regarding treatment techniques and positions.