Dose Reduction In Computed Tomography Research Articles

Ultra-low dose CT scanning for PET/CT.

The use of computed tomography (CT) for attenuation correction (AC) in whole-body PET/CT can result in a significant contribution to radiation exposure. This can become a limiting factor for reducing considerably the overall radiation exposure of the patient when using the new long axial field of view (LAFOV) PET scanners. However, recent CT technology have introduced features such as the tin (Sn) filter, which can substantially reduce the CT radiation dose. The purpose of this study was to investigate the ultra-low dose CT for attenuation correction using the Sn filter together with other dose reduction options such as tube current (mAs) reduction. We explore the impact of dose reduction in the context of AC-CT and how it affects PET image quality. The study evaluated a range of ultra-low dose CT protocols using five physical phantoms that represented a broad collection of tissue electron densities. A long axial field of view (LAFOV) PET/CT scanner was used to scan all phantoms, applying various CT dose reduction parameters such as reducing tube current (mAs), increasing the pitch value, and applying the Sn filter. The effective dose resulting from the CT scans was determined using the CTDIVol reported by the scanner. Several voxel-based and volumes of interest (VOI)-based comparisons were performed to compare the ultra-low dose CT images, the generated attenuation maps, and corresponding PET images against those images acquired with the standard low dose CT protocol. Finally, two patient datasets were acquired using one of the suggested ultra-low dose CT settings. By incorporating the Sn filter and adjusting mAs to the lowest available value, the radiation dose in CT images of PBU-60 phantom was significantly reduced; resulting in an effective dose of nearly 2% compared to the routine low dose CT protocols currently in clinical use. The assessment of PET images using VOI and voxel-based comparisons indicated relative differences (RD%) of under 6% for mean activity concentration (AC) in the torso phantom and patient dataset and under 8% for a source point in the CIRS phantom. The maximum RD% value of AC was 14% for the point source in the CIRS phantom. Increasing the tube current from 6 mAs to 30 mAs in patients with high BMI, or with arms down, can suppress the photon starvation artifact, whilst still preserving a dose reduction of 90%. Introducing a Sn filter in CT imaging lowers radiation dose by more than 90%. This reduction has minimal effect on PET image quantification at least for patients without Body Mass Index (BMI) higher than 30. Notably, this study results need validation using a larger clinical PET/CT dataset in the future, including patients with higher BMI.

Reduced-dose CT in detecting solid liver tumors: A comparison of image quality between automatic exposure control and organ effective modulation

PurposeTo evaluate the subjective and objective image quality of solid liver tumors as well as the radiation dose using organ effective modulation (OEM) technology for abdominopelvic computed tomography (CT). Material and methodsA total of 74 patients who underwent contrast-enhanced abdominopelvic CT between January and April 2022 were prospectively enrolled in this study. Patients were randomly assigned to two groups: the non-OEM group underwent CT scans with automatic exposure control (AEC), while the OEM group underwent CT scans with OEM. The radiation dose was compared between the two groups. Objective image quality was quantitatively assessed using image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). Two experienced radiologists independently evaluated the CT images (5, best; 1, worst) by four characteristics including sharpness, contrast, noise, and diagnostic confidence. ResultsThe OEM group presented a significant reduction in volume CT dose index (CTDIvol), dose-length product (DLP), and effective dose (ED) by 11.4%, 12.2%, and 12.2%, respectively (p < 0.05). There were no significant differences between two groups concerning image noise, SNR, and CNR (p > 0.05). Expect for the left and right liver lobes in portal images, OEM was slightly higher than the non-OEM (p < 0.05). The subjective scores of two radiologists demonstrated good agreement (kappa value = 0.84). No statistically significant differences were observed in subjective grading (p > 0.05). ConclusionOEM technology can effectively reduce the radiation dose of abdominopelvic-enhanced CT without affecting the subjective and objective image quality of solid liver tumors.

A Study of CT-derived Radiation Dose Calculation in Lung Q-SPECT/CT Imaging.

To investigate the amount of effective dose (ED) due to the computed tomography (CT) component of lung perfusion-single-photon emission computed tomography (Q-SPECT)/CT. In this single-center retrospective study, imaging data were collected from the clinic database for the period 2016-2022. The 327 patients identified were aged between 20 and 94 years. Tube voltage, tube current, pitch, gantry rotation time, volume CT dose index, and dose-length product (DLP) were recorded. The DLP was then converted to an ED using the conversion factors. The comparison of the ED between two groups was performed using the Mann-Whitney U non-parametric test. ED (mean ± standard deviation, mSv) was 1.20±0.70 for the pulmonary embolism (PE) (-) and 1.54±1.04 for the PE (+) cases (p<0.05). It was observed that there was a 28% increase in the ED for the PE (+) cases. In addition, each of the PE (-) and PE (+) cases was divided into two groups according to the use of the computed tomography dose reduction (CTDR): without CTDR protocol group (non-CTDR) and with CTDR protocol group (CTDR). For those groups, ED were obtained as 0.87±0.72 and 1.55±0.47 for PE (-) cases (p<0.05); 1.56±1.17 and 1.49±0.54 for PE (+) cases (p>0.05) correspondingly. For a deeper understanding, ED was calculated for all three groups formed with different tube voltage values applied for the non-CTDR and CTDR groups.There was a 42% decrease in the ED for group 1 PE (+) compared to group 2 PE (+) (1.21±0.28, 2.07±0.91, p<0.05) and there was a 41% decrease in the ED for group 1 PE (-) compared to group 2 PE (-) cases (1.17±0.32, 1.97±0.65, p<0.05). It could be concluded that the effective DR protocol is the non-CTDR protocol for the PE (-) cases and the application of the tube voltage at the level of 100 kVp for the PE (+) cases.

How low can we go? CT dose reduction in the assessment of the medial clavicular epiphysis in forensic age estimation: a prospective postmortem CT study.

Projection radiography and, more recently, computed tomography (CT) play an important role in forensic age estimation. Both in terms of general criminal responsibility and government regulations concerning refugee care, it is important to differentiate correctly between youths and adults. A disadvantage of age estimation in CT is the ionizing radiation exposure. To investigate how far the CT dose can be reduced without losing diagnostic confidence in assessing the different stages of ossification of the medial clavicle. We prospectively scanned 25 postmortem cases with a fixed parameters protocol (FPP) and a care dose modulation protocol (CDMP) for different scan parameters. Two radiologists assessed the diagnostic image quality using a 5-point Likert scale. Inter-reader agreement was evaluated with Cohen's kappa. Differences in doses between FPP and CDMP were assessed with the one-tailed t-test. The best combination of diagnostic image quality and lowest radiation dose was obtained using a CDMP with 100 kV and 40 mAs and an FPP with 100 kV and 30 mAs. Doses for 120 kV were significantly higher (one-tailed P < 0.001). The diagnostic image quality for 80 kV was insufficient overall. Our results confirm that CT imaging at 100 kV allows a sufficient image quality that is diagnostic for age estimation in the ossification of the medial clavicle.

Evaluation of radiation dose reduction in head CT using the half-dose method

PurposeThe present study introduced the half-dose method (HDM), which halves the radiation dose for conventional head computed tomography (CT), for postoperative hydrocephalus and follow-up for craniosynostosis at a children’s hospital. This study aimed to evaluate the contribution of selective head CT scanning optimization towards the overall reduction of radiation exposure.Materials and methodsWe retrospectively assessed 1227 and 1352 head CT examinations acquired before and after the introduction of the HDM, respectively, in children aged 0–15 years. The radiation exposure was evaluated using the CT dose index volume (CTDI-vol), dose-length product (DLP), rate of HDM introduction, and effect of reducing in-hospital radiation dose before and after the introduction of the HDM. For an objective evaluation of the image quality, head CT scans acquired with HDM and full-dose method (FDM) were randomly selected, and the image noise standard deviation (SD) was measured for each scan. In addition, some HDM images were randomly selected and independently reviewed by two radiologists.ResultsThe HDM was introduced in 27.9% of all head CTs. The mean CTDI-vol of all head CTs was 21.5 ± 6.9 mGy after the introduction, a 14.9% reduction. The mean DLP was 418.4 ± 152.9 mGy.cm after the introduction, a 17.2% reduction. Compared to the FDM images, the noise SD of the HDM ones worsened by almost 0.9; however, none of the images were difficult or impossible to evaluate.ConclusionThe HDM yielded diagnostically acceptable images. In addition, a change in protocol for only two diseases successfully reduced the patients’ overall radiation exposure by approximately 15%. Introducing and optimizing the HDM for frequently performed target diseases will be useful in reducing the exposure dose for the hospital’s patient population.

Application of Deep Learning-Based Denoising Technique for Radiation Dose Reduction in Dynamic Abdominal CT: Comparison with Standard-Dose CT Using Hybrid Iterative Reconstruction Method.

The purpose is to evaluate whether deep learning-based denoising (DLD) algorithm provides sufficient image quality for abdominal computed tomography (CT) with a 30% reduction in radiation dose, compared to standard-dose CT reconstructed with conventional hybrid iterative reconstruction (IR). The subjects consisted of 50 patients who underwent abdominal CT with standard dose and reconstructed with hybrid IR (ASiR-V50%) and another 50 patients who underwent abdominal CT with approximately 30% less dose and reconstructed with ASiR-V50% and DLD at low-, medium- and high-strength (DLD-L, DLD-M and DLD-H, respectively). The standard deviation of attenuation in liver parenchyma was measured as image noise. Contrast-to-noise ratio (CNR) for portal vein on portal venous phase was calculated. Lesion conspicuity in 23 abdominal solid mass on the reduced-dose CT was rated on a 5-point scale: 0 (best) to -4 (markedly inferior). Compared with hybrid IR of standard-dose CT, DLD-H of reduced-dose CT provided significantly lower image noise (portal phase: 9.0 (interquartile range, 8.7-9.4) HU vs 12.0 (11.4-12.7) HU, P < 0.0001) and significantly higher CNR (median, 5.8 (4.4-7.4) vs 4.3 (3.3-5.3), P = 0.0019). As for DLD-M of reduced-dose CT, no significant difference was found in image noise and CNR compared to hybrid IR of standard-dose CT (P > 0.99). Lesion conspicuity scores for DLD-H and DLD-M were significantly better than hybrid IR (P < 0.05). Dynamic contrast-enhanced abdominal CT acquired with approximately 30% lower radiation dose and generated with the DLD algorithm exhibit lower image noise and higher CNR compared to standard-dose CT with hybrid IR.

Impact of dose reduction and iterative reconstruction algorithm on the detectability of pulmonary nodules by artificial intelligence

PurposeThe purpose of this study was to assess whether the performances of an automated software for lung nodule detection with computed tomography (CT) are affected by radiation dose and the use of iterative reconstruction algorithm. Materials and methodsA chest phantom (Multipurpose Chest Phantom N1; Kyoto Kagaku Co. Ltd, Kyoto, Japan) with 15 pulmonary nodules was scanned with a total of five CT protocol settings with up to 20-fold dose reduction. All CT examinations were reconstructed with iterative reconstruction algorithms ADMIRE 3 and ADMIRE 5 and were then analyzed for the presence of pulmonary nodules with a fully automated computer aided detection software system (InferReadTM CT Lung, Infervision), which is based on deep neural networks. ResultsThe sensitivity of fully automated pulmonary nodule detection for ground-glass nodules at standard dose CT was greater (70.0%; 14/20; 95% CI: 51.6-88.4%) than at 10-fold and 20-fold dose reduction (30.0%; 6/20; 95% CI: 0.0%-62.5%). There were less false positive findings when ADMIRE 5 reconstruction was used (4.0 ± 2.8 [SD]; range: 2–6) instead of ADMIRE 3 reconstruction (25.0 ± 15.6 [SD]; range: 14–36). There was no difference in the sensitivity of detection of solid and subsolid nodules between standard dose (100%; 95% CI: 100–100%) and 10- and 20-fold reduced dose CT (92.5%; 95% CI: 83.8–100.0%). Image noise was significantly greater with ADMIRE 3 (81 ± 2 [SD] [range: 79–84]; 104 ± 3 [SD] [range: 101–107]; 114 ± 5 [SD] [range: 110–119]; 193 ± 10 [SD] [range: 183-203]; 220 ± 16 [SD] [range: 210–238]) compared to ADMIRE 5 (44 ± 2 [SD] [range: 42–46]; 60 ± 2 [SD] [range: 57–61]; 66 ± 1 [SD] [range: 65–67]; 103 ± 4 [SD] [range: 98–106]; 110 ± 1 [SD] [range: 109–111]), respectively in each of the five CT protocols. ConclusionThis phantom study suggests that dose reduction and iterative reconstruction settings have an impact on detectability of pulmonary nodules by artificial intelligence software and we therefore encourage adaption of dose levels and reconstruction methods prior to widespread implementation of fully automatic nodule detection software for lung cancer screening purposes.

Evaluation of computed tomography dose Reduction and image Quality in Ingenuity TOF PET/CT.

Objectives: The aim of this study is to evaluate the various automatic tube current modulation combined with iterative reconstruction (iDose4) in commercially available positron emission computed tomography/computed tomography (PET/CT, Philips healthcare) imaging scanner. Methods: A Rando phantom was scanned according to the high dose routine protocol (CTDI=19.3 mGy) using Atomic Exposure Control (Dose Right) with two different dose right modulation Z and 3D modulation.At each modulation, four different values of Dose right index 5, 10, 15, 20 and 30 were applied. Raw data were reconstructed with 4 iDose4 levels (0, 2, 4 and 6).Results: We found that no significant difference in image noise (SD) of bone, lung, liver issue between the two ATCM including 3D-DOM and Z-DOM (p>0.05). However, significant difference in SD measurements was found in soft tissue (p < 0.05). A significant image noise improvement on iDose4 L2 images at DRI 5 and Z-DOM modulation represented by a reduction in SD of 10.1%, 18.5%, 12.8% and 17.5% for bone, soft tissue, lung and liver respectively.The greatest reduction of image noise was observed when using iDose4 L6 by 20.9%, 39.3%, 40.7 and 72.7% for bone, soft tissue, lung and liver respectively. Z-DOM and 3D-DOM protocols were observed to lead significant reduction in CTDI vol, DLP and effective dose. The reduction in effective radiation exposure was between 15% and 63% according to the value of DRI used. Conclusion: While maintaining a diagnostic level of image quality, combining AEC software with iDose4 levels can effectively reduce the radiation effective dose significantly (up to 60%) in comparison with constant tube current (AEC-off). The results demonstrate also that no significant reduction in radiation dose exposure between using Z-DOM and 3D-DOM modulation.

Comparison of image quality and lesion diagnosis in abdominopelvic unenhanced CT between reduced-dose CT using deep learning post-processing and standard-dose CT using iterative reconstruction: A prospective study

PurposeTo compare image quality and lesion diagnosis between reduced-dose abdominopelvic unenhanced computed tomography (CT) using deep learning (DL) post-processing and standard-dose CT using iterative reconstruction (IR). MethodTotally 251 patients underwent two consecutive abdominopelvic unenhanced CT scans of the same range, including standard and reduced doses, respectively. In group A, standard-dose data were reconstructed by (blend 30 %) IR. In group B, reduced-dose data were reconstructed by filtered back projection reconstruction to obtain group B1 images, and post-processed using the DL algorithm (NeuAI denosing, Neusoft medical, Shenyang, China) with 50 % and 100 % weights to obtain group B2 and B3 images, respectively. Then, CT values of the liver, the second lumbar vertebral centrum, the erector spinae and abdominal subcutaneous fat were measured. CT values, noise levels, signal-to-noise ratios (SNRs), contrast-to-noise ratios (CNRs), radiation doses and subjective scores of image quality were compared. Subjective evaluations of low-density liver lesions were compared by diagnostic results from enhanced CT or Magnetic Resonance Imaging. ResultsGroups B3 and B1 showed the lowest and highest noise levels, respectively (P < 0.001). The SNR and CNR in group B3 were highest (P < 0.001). The radiation dose in group B was reduced by 71.5 % on average compared to group A. Subjective scores in groups A and B2 were highest (P < 0.001). Diagnostic sensitivity and confidence for liver metastases in groups A and B2 were highest (P < 0.001). ConclusionsReduced-dose abdominopelvic unenhanced CT combined with DL post-processing could ensure image quality and satisfy diagnostic needs.

Two‐stage deep learning model for fully automated pancreas segmentation on computed tomography: Comparison with intra‐reader and inter‐reader reliability at full and reduced radiation dose on an external dataset

To develop a two-stage three-dimensional (3D) convolutional neural networks (CNNs) for fully automated volumetric segmentation of pancreas on computed tomography (CT) and to further evaluate its performance in the context of intra-reader and inter-reader reliability at full dose and reduced radiation dose CTs on a public dataset. A dataset of 1994 abdomen CT scans (portal venous phase, slice thickness≤3.75-mm, multiple CT vendors) was curated by two radiologists (R1 and R2) to exclude cases with pancreatic pathology, suboptimal image quality, and image artifacts (n=77). Remaining 1917 CTs were equally allocated between R1 and R2 for volumetric pancreas segmentation [ground truth (GT)]. This internal dataset was randomly divided into training (n=1380), validation (n=248), and test (n=289) sets for the development of a two-stage 3D CNN model based on a modified U-net architecture for automated volumetric pancreas segmentation. Model's performance for pancreas segmentation and the differences in model-predicted pancreatic volumes vs GT volumes were compared on the test set. Subsequently, an external dataset from The Cancer Imaging Archive (TCIA) that had CT scans acquired at standard radiation dose and same scans reconstructed at a simulated 25% radiation dose was curated (n=41). Volumetric pancreas segmentation was done on this TCIA dataset by R1 and R2 independently on the full dose and then at the reduced radiation dose CT images. Intra-reader and inter-reader reliability, model's segmentation performance, and reliability between model-predicted pancreatic volumes at full vs reduced dose were measured. Finally, model's performance was tested on the benchmarking National Institute of Health (NIH)-Pancreas CT (PCT) dataset. Three-dimensional CNN had mean (SD) Dice similarity coefficient (DSC): 0.91 (0.03) and average Hausdorff distance of 0.15 (0.09)mm on the test set. Model's performance was equivalent between males and females (P=0.08) and across different CT slice thicknesses (P>0.05) based on noninferiority statistical testing. There was no difference in model-predicted and GT pancreatic volumes [mean predicted volume 99cc (31cc); GT volume 101cc (33cc), P=0.33]. Mean pancreatic volume difference was -2.7cc (percent difference: -2.4% of GT volume) with excellent correlation between model-predicted and GT volumes [concordance correlation coefficient (CCC)=0.97]. In the external TCIA dataset, the model had higher reliability than R1 and R2 on full vs reduced dose CT scans [model mean (SD) DSC: 0.96 (0.02), CCC=0.995 vs R1 DSC: 0.83 (0.07), CCC=0.89, and R2 DSC:0.87 (0.04), CCC=0.97]. The DSC and volume concordance correlations for R1 vs R2 (inter-reader reliability) were 0.85 (0.07), CCC=0.90 at full dose and 0.83 (0.07), CCC=0.96 at reduced dose datasets. There was good reliability between model and R1 at both full and reduced dose CT [full dose: DSC: 0.81 (0.07), CCC=0.83 and reduced dose DSC:0.81 (0.08), CCC=0.87]. Likewise, there was good reliability between model and R2 at both full and reduced dose CT [full dose: DSC: 0.84 (0.05), CCC=0.89 and reduced dose DSC:0.83(0.06), CCC=0.89]. There was no difference in model-predicted and GT pancreatic volume in TCIA dataset (mean predicted volume 96cc (33); GT pancreatic volume 89cc (30), p=0.31). Model had mean (SD) DSC: 0.89 (0.04) (minimum-maximum DSC: 0.79 -0.96) on the NIH-PCT dataset. A 3D CNN developed on the largest dataset of CTs is accurate for fully automated volumetric pancreas segmentation and is generalizable across a wide range of CT slice thicknesses, radiation dose, and patient gender. This 3D CNN offers a scalable tool to leverage biomarkers from pancreas morphometrics and radiomics for pancreatic diseases including for early pancreatic cancer detection.

Radiation dose reduction in CT-guided cryoablation of renal tumors.

We aimed to evaluate the effect on the radiation dose to the patient by reducing the tube current during the placement of the ablation needles (reduced dose group) compared with the patient doses delivered when scanning at the standard fully diagnostic level (full dose group) in computed tomography (CT)-guided percutaneous cryoablation. We conducted a retrospective study of 103 patients undergoing cryoablation in a tertiary cancer center. Overall, 62 patients were scanned with standard exposure parameters (full dose group) set on a 64-slice multidetector CT scanner, while 41 patients were scanned on a reduced dose protocol. Dose levels were retrieved from the hospital picture and archiving communication system including the volumetric CT dose index (CTDIvol), total dose length product (DLP), length of cryoablation procedure, number of cryoablation needles and patient size. Wilcoxon Mann-Whitney (rank-sum) tests were used to compare the median DLP, CTDIvol and skin dose between the two groups. Median total DLP for the full dose group was 6025 mGy•cm (1909-13353 mGy•cm) compared with 3391 mGy•cm (1683-6820 mGy•cm) for the reduced dose group. The reduced dose group had a 44% reduction in total DLP and 42% reduction in total CTDIvol (p < 0.001). The estimated skin doses were 384 mGy for the full dose group and 224 mGy for the reduced dose group (42% reduction) (p < 0.001). At 12-month follow-up, the technical success for the full dose (n=62) was 97% with 2 patients requiring a further cryoablation treatment for residual tumor. The technical success for the reduced dose group (n=41) was 100%. CT dose reduction technique during image-guided cryoablation treatment of renal tumors can achieve significant radiation dose reduction whilst maintaining sufficient image quality.

Radiation dose reduction in extremity multi-detector CT: A comparison of image quality with a standard dose protocol

PurposeTo analyze the quantitative and qualitative image quality of computed tomography (CT) of the extremities (shoulder, wrist, pelvis, and ankle joints) with low-dose radiation and standard-dose radiation. Materials and methodsIn this study, we included 400 individuals who underwent CT of the extremities, comprising 50 cases of each joint (shoulder, wrist, pelvis, and ankle) at low and standard dose regimens. Low-dose CTs were performed using identical voltage and parameters with the exception of decreased (half of standard dose) tube current. Low-dose and standard-dose images were compared in terms of radiation dose, objective image quality according to the standard deviation (SD) of the Hounsfield unit value of the medulla, cortex, muscle, subcutaneous fat, and air, and subjective image quality according to noise, sharpness, diagnostic acceptability, and artifacts. ResultsIn the shoulder and pelvis, the mean value of the SD for all tissue on low dose CT images was significantly higher than that of standard dose CT, except for the SD of cortex in the shoulder joint and marrow in the pelvis. In the wrist, the mean value of the SD for all tissue was not significantly different between low dose and standard CT (p > 0.05). In the ankle, the mean value of the SD of the medulla and cortex was not different (p > 0.05), but the remaining measurements were significantly higher in low dose CT. Subjective image quality in the shoulder and pelvis were significantly reduced in low dose CT. In the wrist, all categories of subjective image quality except artifacts were similar. In the ankle, all categories of subjective image quality except for artifacts were degraded in low dose CT. ConclusionsObjective image noise is more increased in low dose CT images of the shoulder and pelvis. Although diagnostic performance was acceptable, mean subjective image quality also decreased. In the wrist, objective image noise and subjective image quality were not degraded in low dose CT. In the ankle, some measurements of objective and subjective image quality were similar between low dose and standard dose CT.

Pneumonia Detection in Chest X-Ray Dose-Equivalent CT: Impact of Dose Reduction on Detectability by Artificial Intelligence

There has been a significant increase of immunocompromised patients in recent years due to new treatment modalities for previously fatal diseases. This comes at the cost of an elevated risk for infectious diseases, most notably pathogens affecting the respiratory tract. Because early diagnosis and treatment of pneumonia can help reducing morbidity and mortality, we assessed the performance of a deep neural network in the detection of pulmonary infection in chest X-ray dose-equivalent computed tomography (CT). The 100 patients included in this retrospective study were referred to our department for suspicion of pulmonary infection and/or follow-up of known pulmonary nodules. Every patient was scanned with a standard dose (1.43 ± 0.54 mSv) and a 20 times dose-reduced (0.07 ± 0.03 mSv) CT protocol. We trained a deep neural network to perform binary classification (pulmonary consolidation present or not) and assessed diagnostic performance on both standard dose and reduced dose CT images. The areas under the curve of the deep learning algorithm for the standard dose CT was 0.923 (confidence interval [CI] 95%: 0.905-0.941) and significantly higher than the areas under the curve (0.881, CI 95%: 0.859-0.903) of the reduced dose CT (p = 0.001). Sensitivity and specificity of the standard dose CT was 82.9% and 93.8%, and of the reduced dose CT 71.0% and 93.3%. Pneumonia detection with X-ray dose-equivalent CT using artificial intelligence is feasible and may contribute to a more robust and reproducible diagnostic performance. Dose reduction lowered the performance of the deep neural network, which calls for optimization and adaption of CT protocols when using AI algorithms at reduced doses.

Optimization of acquisition parameters for reduced-dose thoracic CT: A phantom study

PurposeThe purpose of this study was to analyze the impact of different options for reduced-dose computed tomography (CT) on image noise and visibility of pulmonary structures in order to define the best choice of parameters when performing ultra-low dose acquisitions of the chest in clinical routine. Materials and methodsUsing an anthropomorphic chest phantom, CT images were acquired at four defined low dose levels (computed tomography dose index [CTDIvol]=0.15, 0.20, 0.30 and 0.40mGy), by changing tube voltage, pitch factor, or rotation time and adapting tube current to reach the predefined CTDIvol-values. Images were reconstructed using two different levels of iteration (adaptive statistical iterative reconstruction [ASIR®]-v70% and ASIR®-v100%). Signal-to-noise ratio (SNR) as well as contrast-to-noise ratio (CNR) was calculated. Visibility of pulmonary structures (bronchi/vessels) were assessed by two readers on a 5-point-Likert scale. ResultsBest visual image assessments and CNR/SNR were obtained with high tube voltage, while lowest scores were reached with lower pitch factor followed by high tube current. Protocols favoring lower pitch factor resulted in decreased visibility of bronchi/vessels, especially in the periphery. Decreasing radiation dose from 0.40 to 0.30mGy was not associated with a significant decrease in visual scores (P<0.05), however decreasing radiation dose from 0.30mGy to 0.15mGy was associated with a lower visibility of most of the evaluated structures (P<0.001). While image noise could be significantly reduced when ASIR®-v100% instead of ASIR®-v70% was used, the visibility-scores of pulmonary structures did not change significantly. ConclusionFavoring high tube voltage is the best option for reduced-dose protocols. A decrease of SNR and CNR does not necessarily go along with reduced visibility of pulmonary structures.

Computed Tomography Dose Reduction in Children: Review Paper

Increasing the needs of Computed Tomography (CT) for children is quietly augmented over the last decades, although it’s one of the most important modalities in diagnostic finalization. However, it carries a higher risk for the patient in term of radiation dose and cancer risk due to higher sensitivity to radiation than the adult. This study was conducted to review the multiple methods of dose reduction technique as presented by different authors where the different scanning protocols, machine and types of the studies were presented Here, more studies and books were selected, where they are carefully summarized and outlined into different categories for which the result stated that; the most frequent examination done in the CT department is head, neck, and sinuses in which where taken as an example of dose reduction methods. The use of the most modern technical advances was recommended in order to optimize the dose level, comfortable, constants (anesthesia if required) position and using low number of phases as possible according to the pathology of interest (low phases with better visualizations), scanning with thin collimation and view thicker as possible, increasing pitch, automatic exposure control, only the area of interest should be examined, with low tube voltage and using of tube current modulation system can give better result of dose reduction and there were multiple methods presented here. Where is most important for radiologist, technicians, and the person who conduct such studies to increase their knowledge in radiation protection, technical advances and how to interpret the different CT protocols.

Feasibility of extremely reduced-dose CT of the thoracic spine in human cadavers.

According to the as low as reasonably achievable (ALARA) principle, radiation exposure in computed tomography (CT) should be minimized while maintaining adequate image quality. Dedicated CT protocols combined with iterative reconstruction (IR) can reduce radiation dose and/or improve image quality. To investigate the feasibility of extremely reduced-dose (RD) CT of the thoracic spine in human cadavers using a standard-dose (SD) and three different RDCT protocols reconstructed with filtered back projection (FBP) and IR. The thoracic spines of 11 cadavers were examined using different RDCT protocols with decreasing reference tube currents (RDCT-1: 50 mAs; RDCT-2: 30 mAs; RDCT-3: 10 mAs) at 140 kV. A clinical SDCT (70 mAs, 140 kV) served as reference. Raw data were reconstructed using FBP and two increasing levels of IR (IRL4 and IRL6). Images were evaluated for image quality, diagnostic acceptability, and visibility of anatomical structures according to a 5-point-scale. Regardless of the reconstruction technique, image quality was rated as diagnostically acceptable for all cadavers in SDCT and RDCT-1. Image quality of reconstructions with FBP were generally rated lower. Application of IR improved image quality ratings in SDCT and RDCT. RDCT-2 with IR was the most reduced-dose CT protocol which enabled diagnostically acceptable image quality in all cadavers. Compared to SDCT, RDCT protocols resulted in significantly reduced effective radiation doses (SDCT: 4.1 ± 1.5 mSv; RDCT-1: 2.9 ± 1.1 mSv; 2:1.7 ± 0.6 mSv; 3:0.6 ± 0.1 mSv; P = 0.001). Diagnostically acceptable RDCT of the thoracic spine with 1.7 mSv is feasible using IR.

Generalized Gaussian model-based reconstruction method of computed tomography image from fewer projections

In modern computed tomography (CT) imaging, a high-quality image is produced by passing the X-ray radiation dose through the human body. The strategy for CT dose reduction is to reduce the projection views or to limit the scan angle. However, the reduction of radiation doses generates insufficient projection data which often leads the reconstruction problem. Iterative techniques are widely used addressing this issue where a prior-based method is more beneficial to reconstruct CT images. In this paper, the soft-thresholding-based reconstruction method is presented, and the use of the generalized Gaussian distribution model is considered to find the optimal thresholding value. Experimental results show that the reconstructed CT image from fewer projection views using the proposed method has higher quality compared with the other reconstruction approaches.

Thorax CT Dose Reduction Based on Patient Features: Effect of Patient Characteristics on Image Quality and Effective Dose.

Computed tomography (CT) radiation dose reduction is vital without compromising image quality. The aim was to determine the effects of patient characteristics on the received radiation dose and image quality in chest CT examinations and to be able to predict dose and image quality prior to scanning. Consecutive 230 patients underwent routine chest CT examinations were included. CT examination and patients input parameters were recorded for each patient. The effect of patients' demographics/anthropometrics on received dose and image quality was investigated by linear regression analysis. All parameters were evaluated using an artificial neural network (ANN). Of all parameters, patient demographics/anthropometrics were found to be 98% effective in calculating dose reduction. Using ANN on 60 new patients was more than 90% accurate for output parameters and 91% for image quality. Patient characteristics have a significant impact on radiation dose and image quality. Dose and image quality can be determined before CT. This will allow setting the most appropriate scanning parameters before the CT scan.

Feasibility of reduced-dose CT of the head and neck with iterative reconstruction: a phantom and prospective clinical study.

BackgroundThere is growing concern over computed tomography (CT)-related radiation exposure, particularly in patients requiring head and neck CT due to the proximity of radiosensitive organs.Purpos...

Feasibility of radiation dose reduction with iterative reconstruction in abdominopelvic CT for patients with inappropriate arm positioning.

BackgroundThe arms-down position increases computed tomography (CT) radiation dose. Iterative reconstruction (IR) could enhance image quality without increasing radiation dose in patients with arms-down position.AimTo investigate the feasibility of reduced-dose CT with IR for patients with inappropriate arm positioningMethodsTwenty patients who underwent two-phase abdominopelvic CT including standard-dose and reduced-dose CT (performed with 80% of the radiation dose of the standard protocol) with their arms positioned in the abdominal area were included in this study. Reduced-dose CT images were reconstructed using filtered back projection (FBP), hybrid IR, and iterative model reconstruction (IMR). These images were compared with standard-dose CT images reconstructed with FBP. Objective image noise in the liver and subcutaneous fat was measured by standard deviation for the quantitative analysis. Then, two radiologists qualitatively assessed beam hardening artifacts, artificial texture, noise, sharpness, and overall image quality in consensus.ResultsReduced-dose CT with all IR levels had lower objective image noise compared to standard-dose CT with FBP reconstruction (P < 0.05). Quantitatively measured beam hardening artifacts were similar in reduced-dose CT with iDose levels 5–6 and fewer with IMR compared to standard-dose CT. In the qualitative analysis, beam hardening artifacts and noise decreased as the IR levels increased. However, artificial texture was significantly aggravated with iDose 5–6 and IMR, and overall image quality significantly worsened with IMR.ConclusionsIR algorithms can reduce beam hardening artifacts in a reduced-dose CT setting in patients with arms-down position, and an intermediate level of hybrid IR allows radiologists to obtain the best image quality. Because the retrospective and single-center nature of our study limited the number of patients, multicenter prospective clinical studies are required to validate our results.