Radiation protection dosimetry最新文献

Optimizing radiation dose while maintaining image quality remains a key challenge in computed tomography (CT). This study used a thorax-specific anthropomorphic phantom to assess patient dose, image quality, and artefact presence under automated tube current modulation settings and to evaluate the effect of tube voltage on Hounsfield Unit (HU) response for different iodine concentrations. Dose metrics, noise levels, and image quality indicators were extracted from Digital Imaging and Communications in Medicine (DICOM) metadata and image analysis. The study examined how patient positioning affects modulation performance and how tube voltage influences HU values in iodinated inserts. Results revealed inconsistencies in dose modulation across CT systems and highlighted the importance of synchronized protocols. A methodology was proposed to harmonize scanning protocols, ensuring consistent image quality and improved patient safety. These findings demonstrate the value of anthropomorphic phantoms in validating and optimizing CT protocols across clinical environments.

To assess how computed tomography (CT) image reconstruction techniques affect perceived diagnostic image quality at varying radiation dose levels in chest imaging. A PBU-50 anthropomorphic phantom (small adult-sized model) and an air-dried human lung specimen were scanned on the same CT system (Revolution Apex™, GE Healthcare) at six dose levels (CTDIvol) from 0.07 to 2.19 mGy for the smallest phantom size. Images were reconstructed using deep learning image reconstruction-high (DLIR-H), adaptive statistical iterative reconstruction at 40 per cent (ASiR-V), and filtered back projection (FBP). Five radiologists assessed anatomical reproduction, noise, artefacts, and diagnostic quality using ViewDEX. Descriptive statistics and visual grading characteristics analysis were used. In general, DLIR-H scored higher than ASiR-V and FBP. While maintaining image quality, DLIR-H allowed dose reduction compared to FBP. All methods were deemed acceptable for diagnosing pulmonary nodules, fibrosis, and peribronchial pathology. The results indicate that DLIR-H improves image quality in comparison to FBP and ASiR-V and may enable radiation dose reduction while maintaining clinical image quality.

The efficacy of proton beam therapy is limited by stopping power ratio (SPR) prediction uncertainties in patient tissues. This study compared image artefacts and SPR prediction accuracy across a single-energy computed tomography (SECT) and three dual-energy computed tomography (DECT) workflows: SECT with a clinical Hounsfield look-up table (HLUT), two commercial DECT algorithms (DirectSPR and MMSim), and an in-house developed model applied to material density (MD) images, called MD-SPR. SPR images of a head-sized phantom with 24 inserts of tissue surrogate and non-tissue materials were evaluated for image artefacts and compared with measured reference SPRs of the inserts. The root-mean-square SPR differences for tissue surrogates were 0.011 (HLUT), 0.005 (DirectSPR), 0.007 (MMSim), and 0.005 (MD-SPR). For non-tissue materials, the differences were 0.167, 0.028, 0.034, and 0.011, respectively. These results indicate that DECT-based SPR prediction workflows, particularly MD-SPR, can reduce both image artefacts and range uncertainties, compared with a SECT-based HLUT workflow.

This study evaluates radiation dose and risk in computed tomography angiography (CTA) of the carotid arteries by comparing a low-dose protocol with conventional settings. A total of 100 patients were included and equally divided into two groups: 50 underwent scanning with 100 kV and 30 ml of contrast, and 50 with 120 kV and 100 ml. The low-dose protocol significantly reduced the effective dose and the estimated risk of exposure-induced death. Risk prediction was modelled using multiple linear regression: a pre-procedure model based on tube voltage, age, and sex, and a post-procedure model incorporating the volume CT air kerma index, which showed higher precision. These models enable individual risk estimation with or without dosimetric data. The findings support low-dose CTA for carotid imaging to minimize radiation risk while maintaining objective image-quality parameters, and they provide a practical approach to personalized risk assessment in stroke patients.

Reject rate analysis focuses traditionally on frequency rather than radiation impact, thus limiting its alignment with radiation protection goals. This study examined reject rates by body part in digital radiography at a Finnish imaging department and introduced an evaluation of their relative contribution to patients' additional radiation exposure by calculating a median effective dose-weighted reject rate. The resulting metric may serve as a practical tool to support optimization of radiation burden. The pelvic region and lumbar spine rejected radiographs contributed the highest additional radiation dose, followed by the chest, where the high examination volume outweighed the low relative rejection rate in population-wide dose impact. Extremities contributed negligibly to additional effective dose irrespective of their reject rates, primarily due to a substantially lower radiation sensitivity. These findings emphasize the value of integrating effective dose metrics into reject analysis to better reflect patient risk and enhance quality assurance.

Beta-amyloid positron emission tomography/computed tomography (PET/CT) with [18F]flutemetamol is used to demonstrate presence of Alzheimer's disease. With the possibility to use [18F]flutemetamol PET/CT for early detection of mild cognitive impairment and the development of prevention drugs, the demand for the procedure may increase significantly. The biokinetics and dosimetry of [18F]flutemetamol in 7 patients (62-73 y) were studied. Knee-to-head PET/CT scans were acquired 15 min, 1, 2, 3, 4, and 5 hours after intravenous injection of 185 MBq. Activity in blood samples and 20-hour urine was analyzed. Volumes of interest for organs with enhanced activity content were segmented in the PET-images. A biokinetic compartment model was created to derive time-activity data for different organs. Organ doses and effective dose were calculated using IDAC-Dose 2.1 in accordance with ICRP publication 103. The effective dose coefficient for [18F]flutemetamol was 21 μSv/MBq (4 mSv@185 MBq). The colon received highest absorbed dose, 17 mGy.

Rapid adoption of artificial intelligence methods in breast imaging research emphasizes the need for large, appropriately curated image databases for development and validation. For digital breast tomosynthesis (DBT), there are few public databases with only limited lesion annotation. Recently, we have developed Malmö Breast ImaginG (M-BIG), a large database of 104 791 women screened at Skåne University Hospital, Malmö. M-BIG also includes all images from the Malmö Breast Tomosynthesis Screening Trial, MBTST of 14 848 women, with 139 biopsy-confirmed cancers from DBT screening. To annotate lesions in M-BIG, we designed a semi-automated custom software tool for DBT, and corresponding digital mammography (DM) images. A reader manually draws an outline; or marks nodes around the lesion which are automatically connected by an edge-following algorithm. Our custom tool enables detailed annotation of DBT and DM lesions, as opposed to the rectangular regions present in other published material, allowing extensive evaluation of tumor segmentation, and analysis of size and shape descriptors.

Magnetic Resonance Imaging (MRI) exposes patients to radiofrequency energy measured by the specific absorption rate (SAR), a key safety metric. This study aimed to compare SAR values in brain MRI scans performed at 1.5 Tesla (T) and 3 T to inform safer imaging practices. A retrospective analysis of 200 adult brain MRI scans (100 at 1.5 T and 100 at 3 T) from King Khalid University Hospital was conducted. Data included SAR, demographics, scan parameters, and contrast use. Statistical tests assessed differences (P < .05). Brain SAR was significantly higher in 1.5 T scans (mean = 3.01 W/kg) than in 3 T (mean = 1.37 W/kg). Higher SAR values were noted in females and younger patients. Factors like image type, sequence, weight, flip angle, and contrast use significantly impacted SAR. SAR is more influenced by imaging parameters and patient characteristics than MRI magnetic field strength. Personalized MRI protocols and SAR monitoring are essential for patient safety.

Positron Emission Tomography Response Criteria in Solid Tumors (PERCIST) quantifies changes in radiotracer uptake to assess therapeutic response in cancer. However, the accuracy of these quantifications depends on imaging parameters, tumor size, and the local tumor-to-background uptake ratio (local-TBR). In this study, 'background' refers to the surroundings of the lesion rather than a standardized reference tissue. A NEMA Image Quality phantom was filled with 18F-FDG at varying sphere-to-background ratios to simulate clinical scenarios corresponding to PERCIST-defined thresholds for partial metabolic response (-30%) and progressive metabolic disease (+30%). Positron emission tomography (PET)/computed tomography imaging revealed that measured uptake changes systematically underestimated the true ±30% differences, particularly in smaller spheres. These findings indicate a potential source of systematic error in PET-based tumor response assessment, which may influence clinical interpretation. Further studies are recommended to investigate the effects of varying imaging parameters, tumor types, and clinical settings to improve the robustness of PERCIST-based evaluations.

To assess the robustness of risk scores provided by an artificial intelligence (AI) system for digital mammography (DM), when varying the exposure conditions. An anthropomorphic breast phantom containing a lesion, was imaged with DM at different tube voltages (kV), tube loadings (mAs), and anode/filter combinations (W/Rh, Mo/Mo, and Mo/Rh). The organ doses were extracted from the DICOM header and used as a substitute for average glandular dose. The images were analyzed with an AI system, which provided a lesion risk score which translates to suspicion for malignancy. Correlations between the lesion risk score and the exposure conditions were investigated. In most imaging conditions, weak to moderately strong positive associations between lesion risk scores and kV and mAs, respectively, were reported (varying by anode/filter combinations). When organ dose increased the AI risk scores plateaued, and further increase did not increase the lesion risk score. For typical clinical settings (W/Rh, 27 kV and 71 mAs) the range of lesion risk scores was 33-56 (mean: 42, SD: 9). Greatest reported variability (range: 36-63, mean: 51, SD: 12) was found at 27 kV and 36 mAs (using W/Rh). Images of suboptimal quality may result in inaccurate AI system performance. The unexpectedly large intra-group variability of AI risk scores should be further investigated.