Significant but reasonable radiation exposure from computed tomography-related medical imaging in the ICU

Objective: Physicians who often request for computed tomography (CT) scan examinations are expected to have sound knowledge of radiation exposure (risks) to patients in line with the basic radiation protection principles according to the International Commission on Radiological Protection (ICRP), the Protection of Persons Undergoing Medical Exposure or Treatment (POPUMET), and the Ionizing Radiation (Medical Exposure) Regulations (IR(ME)R). The aim is to assess the level of requesting physicians’ knowledge of ionizing radiation from CT scan examinations in two Nigerian tertiary hospitals. Materials and Methods: An 18-item-based questionnaire was distributed to 141 practicing medical doctors, excluding radiologists with work experience from 0 to >16 years in two major teaching hospitals in Nigeria with a return rate of 69%, using a voluntary sampling technique. Results: The results showed that 25% of the respondents identified CT thorax, abdomen, and pelvis examination as having the highest radiation risk, while 22% said that it was a conventional chest X-ray. Furthermore, 14% concluded that CT head had the highest risk while 9% gave their answer to be conventional abdominal X-ray. In addition, 17% inferred that magnetic resonance imaging had the highest radiation risk while 11% had no idea. Furthermore, 25.5% of the respondents have had training on ionizing radiation from CT scan examinations while 74.5% had no training. Majority (90%) of the respondents were not aware of the ICRP guidelines for requesting investigations with very little (<3%) or no knowledge (0%) on the POPUMET and the IR(ME)R respectively. Conclusion: There is low level of knowledge of ionizing radiation from CT scan examinations among requesting physicians in the study locations.

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Faculty Opinions recommendation of Estimating risk of cancer associated with radiation exposure from 64-slice computed tomography coronary angiography.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.1089280.552885 ◽

2007 ◽

Author(s):

Paul Stein

Keyword(s):

Computed Tomography ◽

Coronary Angiography ◽

Radiation Exposure ◽

Computed Tomography Coronary Angiography ◽

Risk Of Cancer

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Faculty Opinions recommendation of Computed tomography--an increasing source of radiation exposure.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.717989859.793473049 ◽

2013 ◽

Author(s):

David Midthun

Keyword(s):

Computed Tomography ◽

Radiation Exposure

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Faculty Opinions recommendation of Estimated radiation exposure from medical imaging in hemodialysis patients.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.9284956.9893054 ◽

2011 ◽

Author(s):

David Goldsmith ◽

Behdad Afzali

Keyword(s):

Medical Imaging ◽

Radiation Exposure ◽

Hemodialysis Patients

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Data augmentation for computed tomography angiography via synthetic image generation and neural domain adaptation

Current Directions in Biomedical Engineering ◽

10.1515/cdbme-2020-0015 ◽

2020 ◽

Vol 6 (1) ◽

Author(s):

Malte Seemann ◽

Lennart Bargsten ◽

Alexander Schlaefer

Keyword(s):

Computed Tomography ◽

Neural Networks ◽

Deep Learning ◽

Medical Imaging ◽

Computed Tomography Angiography ◽

Data Augmentation ◽

Domain Adaptation ◽

Synthetic Image ◽

Wide Range ◽

The Impact

AbstractDeep learning methods produce promising results when applied to a wide range of medical imaging tasks, including segmentation of artery lumen in computed tomography angiography (CTA) data. However, to perform sufficiently, neural networks have to be trained on large amounts of high quality annotated data. In the realm of medical imaging, annotations are not only quite scarce but also often not entirely reliable. To tackle both challenges, we developed a two-step approach for generating realistic synthetic CTA data for the purpose of data augmentation. In the first step moderately realistic images are generated in a purely numerical fashion. In the second step these images are improved by applying neural domain adaptation. We evaluated the impact of synthetic data on lumen segmentation via convolutional neural networks (CNNs) by comparing resulting performances. Improvements of up to 5% in terms of Dice coefficient and 20% for Hausdorff distance represent a proof of concept that the proposed augmentation procedure can be used to enhance deep learning-based segmentation for artery lumen in CTA images.

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Evaluation of Velopharyngeal Closure Function With 4-Dimensional Computed Tomography and Assessment of Radiation Exposure in Pediatric Patients: A Cross-Sectional Study

The Cleft Palate-Craniofacial Journal ◽

10.1177/10556656211001732 ◽

2021 ◽

pp. 105566562110017

Author(s):

Yoshikazu Kobayashi ◽

Masanao Kobayashi ◽

Daisuke Kanamori ◽

Naoko Fujii ◽

Yumi Kataoka ◽

...

Keyword(s):

Computed Tomography ◽

Radiation Exposure ◽

Exposure Dose ◽

Velopharyngeal Insufficiency ◽

Radiation Doses ◽

Secondary Surgery ◽

Cross Sectional ◽

Computed Tomography Images ◽

Velopharyngeal Closure ◽

Closure Function

Objective: Some patients with cleft palate (CP) need secondary surgery to improve functionality. Although 4-dimensional assessment of velopharyngeal closure function (VPF) in patients with CP using computed tomography (CT) has been existed, the knowledge about quantitative evaluation and radiation exposure dose is limited. We performed a qualitative and quantitative assessment of VPF using CT and estimated the exposure doses. Design: Cross-sectional. Setting: Computed tomography images from 5 preoperative patients with submucous CP (SMCP) and 10 postoperative patients with a history of CP (8 boys and 7 girls, aged 4-7 years) were evaluated. Patients: Five patients had undergone primary surgery for SMCP; 10 received secondary surgery for hypernasality. Main Outcome Measures: The presence of velopharyngeal insufficiency (VPI), patterns of velopharyngeal closure (VPC), and cross-sectional area (CSA) of VPI was evaluated via CT findings. Organ-absorbed radiation doses were estimated in 5 of 15 patients. The differences between cleft type and VPI, VPC patterns, and CSA of VPI were evaluated. Results: All patients had VPI. The VPC patterns (SMCP/CP) were evaluated as coronal (1/4), sagittal (0/1), circular (1/2), and circular with Passavant’s ridge (2/2); 2 patients (1/1) were unevaluable because of poor VPF. The CSA of VPI was statistically larger in the SMCP group ( P = .0027). The organ-absorbed radiation doses were relatively lower than those previously reported. Conclusions: Four-dimensional CT can provide the detailed findings of VPF that are not possible with conventional CT, and the exposure dose was considered medically acceptable.

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Application of 3D tooth model for monitoring of implant space and inter-root distance without radiographs: a proof of concept study

International Journal of Implant Dentistry ◽

10.1186/s40729-020-00253-3 ◽

2020 ◽

Vol 6 (1) ◽

Author(s):

Kyungmin Lee ◽

Gyu-Hyoung Lee

Keyword(s):

Computed Tomography ◽

Radiation Exposure ◽

Cone Beam Computed Tomography ◽

Alveolar Bone ◽

Tooth Movement ◽

Treatment Evaluation ◽

Cone Beam ◽

Proof Of Concept ◽

Cbct Image ◽

Root Position

Abstract Background Radiographs are integral in evaluating implant space and inter-root distance. The purpose of this report is to introduce a method for evaluating the 3D root position with minimal radiation using a 3D tooth model composed of an intraoral-scanned crown and a cone-beam computed tomography (CBCT)-scanned root. Materials and methods Intraoral scan and CBCT scan of the patient were obtained before treatment. In the CBCT image, tooth segmentation was performed by isolating individual teeth from the maxillary and mandibular alveolar bone using software program. The 3D tooth model was fabricated by combining segmented individual teeth with the intraoral scan. Results A post-treatment intraoral scan was integrated into the tooth model, and the resulting position of the root could be predicted without additional radiographs. It is possible to monitor the root position after a pretreatment CBCT scan using a 3D tooth model without additional radiographs. Conclusion The application of the 3D tooth model benefits the patient by reducing repeated radiation exposure while providing the clinician with a precise treatment evaluation to monitor tooth movement.

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