Diagnostic Acceptability Research Articles

Multireader image quality evaluation of dynamic myocardial computed tomography perfusion imaging with a novel four-dimensional noise reduction filter.

Dynamic myocardial computed tomography perfusion (CTP) is a novel technique able to depict cardiac ischemia. To evaluate the impact of a four-dimensional noise reduction filter (similarity filter [4D-SF]) on image quality in dynamic CTP imaging, allowing for substantial radiation dose reduction. Dynamic CTP datasets of 30 patients (16 women) with suspected coronary artery disease, acquired with a 320-slice CT system, were retrieved, reconstructed with the deep learning-based algorithm of the system (DLR), and filtered with the 4D-SF. For each case, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) in six regions of interest (33-38mm2) were calculated before and after filtering, in four-chamber and short-axis views, and t-tested. Furthermore, six radiologists of different expertise evaluated subjective image preference by answering five visual grading analysis-type questions (regarding acceptable level of noise, absence of artifacts, natural appearance, cardiac contour sharpness, diagnostic acceptability) using a 5-point scale. The results were analyzed using visual grade characteristics (VGC) and intraclass correlation coefficient (ICC). Mean SNR in four-chamber view (unfiltered vs. filtered) were: septum=4.1 ± 2.1 versus 7.6 ± 5.6; lateral wall=4.5 ± 2.0 versus 8.0 ± 4.9; CNRseptum=16.6 ± 8.9 versus 31.7 ± 28; lateral wall=16.2 ± 8.9 versus 31.3 ± 28.9. Similar results were obtained in short-axis view. The perceived filtered image quality indicated decreased noise (VGCAUC=0.96) and artifacts (0.65), improved natural appearance (0.59), cardiac contour sharpness (0.74), and diagnostic acceptability (0.78). The inter-observer variability was excellent (ICC=0.79). All results were statistically significant (P < 0.05). Similarity filtering after DLR improves image quality, possibly enabling dose reduction in dynamic CTP imaging in patient with suspected chronic coronary syndrome.

Deep learning-based reconstruction of virtual monoenergetic images of kVp-switching dual energy CT for evaluation of hypervascular liver lesions: Comparison with standard reconstruction technique

ObjectiveTo investigate clinical applicability of deep learning(DL)-based reconstruction of virtual monoenergetic images(VMIs) of arterial phase liver CT obtained by rapid kVp-switching dual-energy CT for evaluation of hypervascular liver lesions. Materials and MethodsWe retrospectively included 109 patients who had available late arterial phase liver CT images of the liver obtained with a rapid switching kVp DECT scanner for suspicious intra-abdominal malignancies. Two VMIs of 70 keV and 40 keV were reconstructed using adaptive statistical iterative reconstruction (ASiR-V) for arterial phase scans. VMIs at 40 keV were additionally reconstructed with a vendor-agnostic DL-based reconstruction technique (ClariCT.AI, ClariPi, DL 40 keV). Qualitative, quantitative image quality and subjective diagnostic acceptability were compared according to reconstruction techniques. ResultsIn qualitative analysis, DL 40 keV images showed less image noise (4.55 vs 3.11 vs 3.95, p < 0.001), better image sharpness (4.75 vs 4.16 vs 4.3, p < 0.001), better image contrast (4.98 vs 4.72 vs 4.19, p < 0.017), better lesion conspicuity (4.61 vs 4.23 vs 3.4, p < 0.001) and diagnostic acceptability (4.59 vs 3.88 vs 4.09, p < 0.001) compared with ASiR-V 40 keV or 70 keV image sets. In quantitative analysis, DL 40 keV significantly reduced image noise relative to ASiR-V 40 keV images (49.9%, p < 0.001) and ASiR-V 70 keV images (85.2%, p = 0.012). DL 40 keV images showed significantly higher CNRlesion to the liver and SNRliver than ASiR-V 40 keV image and 70 keV images (p < 0.001). ConclusionDL-based reconstruction of 40 keV images using vendor-agnostic software showed greater noise reduction, better lesion conspicuity, image contrast, image sharpness, and higher overall image diagnostic acceptability than ASiR for 40 keV or 70 keV images in patients with hypervascular liver lesions.

Evaluating bone biopsy quality by technique in an animal model.

Powered bone biopsy technique is popular due to its ease of use. However, there is conflicting evidence regarding the diagnostic quality of the samples. The purpose of this study is to evaluate the diagnostic adequacy of different bone biopsy devices and techniques as it relates to the frequency of sample artifacts. Bone biopsy was performed on same-day processed lamb femora using the following techniques: manual, pulsed powered and full powered. Ten samples were collected using each method by a single musculoskeletal-trained radiologist and were reviewed by 3 blinded pathologists. Samples were compared across multiple categories: length, bone dust, thermal/crush artifact, cellular morphology, fragmentation, and diagnostic acceptability. Bayesian Multilevel Nonlinear Regression models were performed assessing the association between the techniques across the categories. Statistical analysis revealed that the manual technique outperformed any powered technique across all categories: decreased thermal/crush artifact (P = 0.014), decreased bone dust (p<0.001), better cellular morphology (P = 0.005), less fragmentation (P < 0.0001) and better diagnostic acceptability (P < 0.0001). Manually obtained bone biopsy samples generally produce a more diagnostic sample as compared to powered techniques in an animal model. Given these results, manual bone biopsy methods should be encouraged after consideration for lesion composition, difficulty of access and the patient's overall condition.

Radiation and iodine dose reduced thoraco-abdomino-pelvic dual-energy CT at 40 keV reconstructed with deep learning image reconstruction.

To evaluate the feasibility of a simultaneous reduction of radiation and iodine doses in dual-energy thoraco-abdomino-pelvic CT reconstructed with deep learning image reconstruction (DLIR). Thoraco-abdomino-pelvic CT was prospectively performed in 111 participants; 52 participants underwent a standard-dose single-energy CT with a standard iodine dose (600 mgI/kg; SD group), while 59 underwent a low-dose dual-energy CT with a reduced iodine dose [300 mgI/kg; double low-dose (DLD) group]. CT data were reconstructed with a hybrid iterative reconstruction in the SD group and a high-strength level of DLIR at 40 keV in the DLD group. Two radiologists measured the CT numbers of the descending and abdominal aorta, portal vein, hepatic vein, inferior vena cava, liver, pancreas, spleen, and kidney, and background noise. Two other radiologists assessed diagnostic acceptability using a 5-point scale. The CT dose-index volume (CTDIvol), iodine weight, CT numbers of anatomical structures, background noise, and diagnostic acceptability were compared between the two groups using Mann-Whitney U test. The median CTDIvol [10 mGy; interquartile range (IQR), 9-13 mGy vs 4 mGy; IQR, 4-5 mGy] and median iodine weight (35 g; IQR, 31-38 g vs 16 g; IQR, 14-18 g) were lower in the DLD group than in the SD group (p < 0.001 for each). The CT numbers of all anatomical structures and background noise were higher in the DLD group than in the SD group (p < 0.001 for all). The diagnostic image quality was obtained in 100% (52/52) of participants in the SD group and 95% (56/59) of participants in the DLD group. Virtual monochromatic images at 40 keV reconstructed with DLIR could achieve half doses of radiation and iodine while maintaining diagnostic image quality. Virtual monochromatic images at 40 keV reconstructed with DLIR algorithm allowed to reduce the doses of radiation and iodine while maintaining diagnostic image quality.

Low Tube Voltage Chest Computed Tomography With Enhancement Using Low-Concentration Iodinated Contrast Media: Comparison of 240mg/mL Versus 300mg/mL Iodinated Contrast Media.

Purpose: To evaluate the image quality of low voltage chest computed tomography with enhancement (CECT) using low-concentration-iodine contrast media (LCCM). Method: From 9 December to 19 December 2019, three different protocols were used for 263 patients undergoing chest CECT. Chest CECT was done using routine (300 mgI/ml contrast media with 100kVp) protocol (group 1), LCCM (240mgI/ml contrast media)-100 kVp protocol (group 2) and LCCM-80 kVp protocol (group 3) in 91, 97 and 75 patients, respectively. The overall diagnostic acceptability, anatomical depiction, noise and contrast-related artifacts were assessed. Additionally, the mean attenuation, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and figure of merit (FOM) in the aorta and the main pulmonary trunk were measured. Results: The overall diagnostic acceptability scores were not significantly different between groups 1 and 2 (P = .261); group 3 demonstrated significantly lower overall diagnostic acceptability score compared with group 1 (P = .011) or group 2 (P < .001). However, in CECT with iterative reconstruction (IR), the overall diagnostic acceptability scores did not show significant difference among 3 groups. Group 3 showed significantly lower effective radiation dose compared with group 1 (2.33 vs 1.22mSv, P < .001) or group 2 (2.28 vs .22mSv, P < .001). Conclusions: In 100 kVp chest CECT, the image quality of using 240mg/mL iodinated contrast media is comparable to that using 300mg/mL iodine contrast media, regardless of application of IR; with IR, chest CECT using 80kVp and 240mg/mL iodinated contrast media results in acceptable image quality and lower radiation dose.

Feasibility of half the recommended dose of IV contrast in DECT: image quality evaluation and diagnostic acceptability in cancer patients

PurposeTo assess the quality of dual-energy computed tomography (DECT) images in patients receiving 50% of the recommended weight-based volume of iodinated intravenous contrast medium. MethodsThe study included cancer patients who previously underwent abdominal CT on a DECT scanner using a single source with the full recommended weight-based dose of Iohexol 350. Using the same scanner, the patients underwent a portovenous phase DECT scan following intravenous injection of half of the recommended weight-based dose. Monochromatic energy images were processed at 60 and 70kEv and compared to polychromatic 140kVp images. Three radiologists independently scored the images for overall diagnostic acceptability and image quality of solid organs and vasculature. Regions of interest were drawn on the portal vein, aorta, liver, and fat to calculate contrast to noise ratio (CNR) and signal to noise ratio (SNR). A multivariate ordinal generalized estimating equations model was used to assess image quality score. Pairwise comparisons were performed of the readers' scores, CNR, and SNR. Agreement with respect to quality score was calculated by using Fleiss's kappa value. ResultsDiagnostic acceptability was better for the SECT (120kVp) scans than for the 70 and 60kEv scans, and better for the 70 and 60kEv scans than for the 140kVp scans. Noise was subjectively rated as best on the 70kEv images. SNR of the liver was highest on 70kEv images. SNR of the liver on 70kEv images was significantly better than SECT images (p < 0.0001). Liver CNR was highest on SECT (120kVp) images. ConclusionDECT with 50% reduction in the volume of intravenous contrast produces image quality comparable to that of SECT in cancer patients.

Deep learning reconstruction allows low-dose imaging while maintaining image quality: comparison of deep learning reconstruction and hybrid iterative reconstruction in contrast-enhanced abdominal CT.

We aimed to compare the radiation dose and image quality of a low-dose abdominal computed tomography (CT) protocol reconstructed with deep learning reconstruction (DLR) with those of a routine-dose protocol reconstructed with hybrid-iterative reconstruction. This retrospective study enrolled 71 patients [61 men; average age, 71.9 years; mean body mass index (BMI), 24.3 kg/m2] who underwent both low-dose abdominal CT with DLR [advanced intelligent clear-IQ engine (AiCE)] and routine-dose abdominal CT with hybrid-iterative reconstruction [adaptive iterative dose reduction 3D (AIDR 3D)]. Radiation dose parameters included volume CT dose index (CTDIvol), effective dose (ED), and size-specific dose estimate (SSDE). Mean image noise and contrast-to-noise ratio (CNR) were calculated. Image noise was measured in the hepatic parenchyma and bilateral erector spinae muscles. Moreover, subjective assessment of perceived image quality and diagnostic acceptability was performed. The low-dose protocol helped reduce the CTDIvol by 44.3%, ED by 43.7%, and SSDE by 44.9%. Moreover, the noise was significantly lower and CNR significantly higher with the low-dose protocol than with the normal-dose protocol (P<0.001). In the subjective assessment of image quality, there was no significant difference between the protocols with regard to image noise. Overall, AiCE was superior to AIDR 3D in terms of diagnostic acceptability (P=0.001). The use of AiCE can reduce overall radiation dose by more than 40% without loss of image quality compared to routine-dose abdominal CT with AIDR 3D.

Image quality comparison of single-energy and dual-energy computed tomography for head and neck patients: a prospective randomized study

ObjectivesThe aim of this study was to compare the quality of images obtained using single-energy computed tomography (SECT) performed with automated tube voltage adaptation (TVA) with dual-energy CT (DECT) weighted average images.MethodsEighty patients were prospectively randomized to undergo either SECT with TVA (n = 40, ref. mAs 200) or radiation dose–matched DECT (n = 40, 80/Sn150 kV, ref. mAs tube A 91/tube B 61) on a dual-source CT scanner. Objective image quality was evaluated as dose-normalized contrast-to-noise ratio (CNRD) for the jugular veins relative to fatty tissue and muscle tissue and for muscle tissue relative to fatty issue. For subjective image quality, reproduction of anatomical structures, image artifacts, image noise, spatial resolution, and overall diagnostic acceptability were evaluated at sixteen anatomical substructures using Likert-type scales.ResultsEffective radiation dose (ED) was comparable between SECT and DECT study groups (2.9 ± 0.6 mSv/3.1 ± 0.7 mSv, p = 0.5). All examinations were rated as excellent or good for clinical diagnosis. Compared to the CNRD in the SECT group, the CNRD in the DECT group was significantly higher for the jugular veins relative to fatty tissue (7.51/6.08, p < 0.001) and for muscle tissue relative to fatty tissue (4.18/2.90, p < 0.001). The CNRD for the jugular veins relative to muscle tissue (3.33/3.18, p = 0.51) was comparable between groups. Image artifacts were less pronounced and overall diagnostic acceptability was higher in the DECT group (all p = 0.01).ConclusionsDECT weighted average images deliver higher objective and subjective image quality than SECT performed with TVA in head and neck imaging.Key Points• Weighted average images derived from dual-energy CT deliver higher objective and subjective image quality than single-energy CT using automated tube voltage adaptation in head and neck imaging.• If available, dual-energy CT acquisition may be preferred over automated low tube voltage adopted single-energy CT for both malignant and non-malignant conditions.

Low dose protocol for high resolution CT thorax: influence of matrix size and tube voltage on image quality and radiation dose

Background: High-resolution CT (HRCT) thorax has increase demand due to its advantage in diagnosing chronic respiratory diseases. The feasibility of matrix size with different tube voltage in the HRCT protocol of thorax is unknown. Therefore, this study aimed to compare the effect of matrix sizes and tube voltage on image quality and radiation dose on adult HRCT thorax. Methods: A Phantom experiment was performed, followed by a patient scan. For phantom and patient scan, a total of six protocols with two tube voltage settings, 120 kVp and 100 kVp, with a combination of three matrix sizes, 512, 768, and 1024 were used. In this study, 180 adult patients who had HRCT thorax scan were considered. Dose data was collected, and quantitative image analysis was performed by drawing region of interests on the acquired phantom and patient images. Qualitative image analysis was performed independently by two blinded radiologists. Results: The dose report of the phantom experiment revealed that the 100kVp with selected matrix size delivered 15.64% and 15.62% less radiation dose in terms of volumetric computed tomography dose index (CTDIvol) and dose length product (DLP), respectively, compared to 120kVp settings with selected matrix sizes. Similarly, for the patient population, the CTDIvol and DLP difference noted for 120kVp and 100kVp with different matrix sizes was statistically significant (p&lt;0.001). For quantitative image quality, the difference noted was also statistically significant among two kVp settings. The mean score for subjective image assessment was greater than 4.5 for diagnostic acceptability and streak artefacts. Conclusion: The result suggests that the 100 kVp with 512 X 512 matrix size is preferable in the HRCT Lung to achieve the optimal diagnostic image quality with a reduction of almost 40% of the dose to the patients compared to 120 kVp techniques.

Deep learning-based image reconstruction of 40-keV virtual monoenergetic images of dual-energy CT for the assessment of hypoenhancing hepatic metastasis.

To evaluate the diagnostic value of deep learning model (DLM) reconstructed dual-energy CT (DECT) low-keV virtual monoenergetic imaging (VMI) for assessing hypoenhancing hepatic metastases. This retrospective study included 131 patients who underwent contrast-enhanced DECT (80-kVp and 150-kVp with a tin filter) in the portal venous phase for hepatic metastasis surveillance. Linearly blended images simulating 100-kVp images (100-kVp), standard 40-keV VMI images (40-keV VMI), and post-processed 40-keV VMI using a vendor-agnostic DLM (i.e., DLM 40-keV VMI) were reconstructed. Lesion conspicuity and diagnostic acceptability were assessed by three independent reviewers and compared using the Wilcoxon signed-rank test. The contrast-to-noise ratios (CNRs) were also measured placing ROIs in metastatic lesions and liver parenchyma. The detection performance of hepatic metastases was assessed by using a jackknife alternative free-response ROC method. The consensus by two independent radiologists was used as the reference standard. DLM 40-keV VMI, compared to 40-keV VMI and 100-kVp, showed a higher lesion-to-liver CNR (8.25 ± 3.23 vs. 6.05 ± 2.38 vs. 5.99 ± 2.00), better lesion conspicuity (4.3 (4.0-4.7) vs. 3.7 (3.7-4.0) vs. 3.7 (3.3-4.0)), and better diagnostic acceptability (4.3 (4.0-4.3) vs. 3.0 (2.7-3.3) vs. 4.0 (4.0-4.3)) (p < 0.001 for all). For lesion detection (246 hepatic metastases in 68 patients), the figure of merit was significantly higher with DLM 40-keV VMI than with 40-keV VMI (0.852 vs. 0.822, p = 0.012), whereas no significant difference existed between DLM 40-keV VMI and 100-kVp (0.852 vs. 0.842, p = 0.31). DLM 40-keV VMI provided better image quality and comparable diagnostic performance for detecting hypoenhancing hepatic metastases compared to linearly blended images. • DLM 40-keV VMI provides a superior image quality compared with 40-keV or 100-kVp for assessing hypoenhancing hepatic metastasis. • DLM 40-keV VMI has the highest CNR and lesion conspicuity score for hypoenhancing hepatic metastasis due to noise reduction and structural preservation. • DLM 40-keV VMI provides higher lesion detectability than standard 40-keV VMI (p = 0.012).

Acceptance and Commitment Therapy for Patients with a First Psychotic Episode.

The search for the most effective methods of therapy for mental disorders is a priority for modern psychiatry. An approach to the early diagnostics and rehabilitation of patients experiencing psychotic episodes for the first time is proposed in the present article. The proposed approach is based on the combination of drug therapy and acceptance and commitment therapy (ACT) characterized by the development of the patient's psychological flexibility, rather than controlling the disease symptoms. The article describes the main processes of the ACT model: acceptance, cognitive defusion, contact with the present moment, understanding of the inner world, awareness of significant values, and the regulation of purposeful behaviour for the implementation of these values. Recommendations for different stages of treatment were also developed by specialists of the First Psychotic Episode Clinic at the Mental Health Clinic No.1 named after N.A. Alexeev. The psychological rehabilitation of patients with the use of ACT in the case of psychotic disorders with both negative and positive symptoms was elaborated. The application of acceptance and commitment therapy in the early diagnostics and treatment of patients experiencing a first psychotic episode results in fewer readmissions and improved psychosocial functioning in both inpatient and outpatient care.

Model-based iterative reconstruction in CT of paranasal sinuses in cystic fibrosis

To assess image quality and dose-reduction efficacy of model-based iterative reconstruction (MBIR) in computed tomography (CT) of the paranasal sinus (CTPNS) compared with adaptive statistical iterative reconstruction (ASIR) in cystic fibrosis (CF) patients. Unenhanced CTPNS studies performed in adult CF patients from 2014 to 2020 were included. MBIR and ASIR were used and compared. Two radiologists assessed the CT images blindly and randomly. Quantitative assessment of noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) was performed in the maxillary sinus, sphenoid body, temporalis, and background air. Qualitative assessment performed included image sharpness, noise and contrast. Thirty-seven MBIR and 45 ASIR CT PNS studies were included. MBIR achieved a 74% effective median dose reduction (0.039 mSv) compared with ASIR (0.147 mSv). Measured noise was significantly lower in all regions using MBIR (p<0.001) with superior SNR (p<0.001). MBIR had higher CNR compared to ASIR (4.567 versus 2.03, p<0.001). MBIR images were sharper and less noisy, with equal contrast. Cohen's weighted kappa value was 0.824 for qualitative analysis, indicating good inter-rater agreement. Both methods had 100% diagnostic acceptability. MBIR produces high-quality CTPNS images at a significantly lower dose compared with ASIR. It is the preferred imaging surveillance method in CF patients and may have roles in other patient cohorts.

Deep learning image reconstruction algorithm for pancreatic protocol dual-energy computed tomography: image quality and quantification of iodine concentration.

To evaluate the image quality and iodine concentration (IC) measurements in pancreatic protocol dual-energy computed tomography (DECT) reconstructed using deep learning image reconstruction (DLIR) and compare them with those of images reconstructed using hybrid iterative reconstruction (IR). The local institutional review board approved this prospective study. Written informed consent was obtained from all participants. Thirty consecutive participants with pancreatic cancer (PC) underwent pancreatic protocol DECT for initial evaluation. DECT data were reconstructed at 70 keV using 40% adaptive statistical iterative reconstruction-Veo (hybrid-IR) and DLIR at medium and high levels (DLIR-M and DLIR-H, respectively). The diagnostic acceptability and conspicuity of PC were qualitatively assessed using a 5-point scale. IC values of the abdominal aorta, pancreas, PC, liver, and portal vein; standard deviation (SD); and coefficient of variation (CV) were calculated. Qualitative and quantitative parameters were compared between the hybrid-IR, DLIR-M, and DLIR-H groups. The diagnostic acceptability and conspicuity of PC were significantly better in the DLIR-M group compared with those in the other groups (p < .001-.001). The IC values of the anatomical structures were almost comparable between the three groups (p = .001-.9). The SD of IC values was significantly lower in the DLIR-H group (p < .001) and resulted in the lowest CV (p < .001-.002) compared with those in the hybrid-IR and DLIR-M groups. DLIR could significantly improve image quality and reduce the variability of IC values than could hybrid-IR. Image quality and conspicuity of pancreatic cancer were the best in DLIR-M. DLIR significantly reduced background noise and improved SNR and CNR. The variability of iodine concentration was reduced in DLIR.

Deep learning image reconstruction for pancreatic low-dose computed tomography: comparison with hybrid iterative reconstruction.

To evaluate image quality, image noise, and conspicuity of pancreatic ductal adenocarcinoma (PDAC) in pancreatic low-dose computed tomography (LDCT) reconstructed using deep learning image reconstruction (DLIR) and compare with those of images reconstructed using hybrid iterative reconstruction (IR). Our institutional review board approved this prospective study. Written informed consent was obtained from all patients. Twenty-eight consecutive patients with PDAC undergoing chemotherapy (14 men and 14 women; mean age, 68.4 years) underwent pancreatic LDCT for therapy evaluation. The LDCT images were reconstructed using 40% adaptive statistical iterative reconstruction-Veo (hybrid-IR) and DLIR at medium and high levels (DLIR-M and DLIR-H). The image noise, diagnostic acceptability, and conspicuity of PDAC were qualitatively assessed using a 5-point scale. CT numbers of the abdominal aorta, portal vein, pancreas, PDAC, background noise, signal-to-noise ratio (SNR) of the anatomical structures, and tumor-to-pancreas contrast-to-noise ratio (CNR) were calculated. Qualitative and quantitative parameters were compared between the hybrid-IR, DLIR-M, and DLIR-H images. CT dose-index volumes and dose-length product in pancreatic LDCT were 2.3 ± 1.0 mGy and 74.9 ± 37.0 mGy•cm, respectively. The image noise, diagnostic acceptability, and conspicuity of PDAC were significantly better in DLIR-H than those in hybrid-IR and DLIR-M (all P < 0.001). The background noise was significantly lower in the DLIR-H images (P < 0.001) and resulted in improved SNRs (P < 0.001) and CNR (P < 0.001) compared with those in the hybrid-IR and DLIR-M images. DLIR significantly reduced image noise and improved image quality in pancreatic LDCT images compared with hybrid-IR.

Deep-learning-based image reconstruction in dynamic contrast-enhanced abdominal CT: image quality and lesion detection among reconstruction strength levels

To evaluate the use of deep-learning-based image reconstruction (DLIR) algorithms in dynamic contrast-enhanced computed tomography (CT) of the abdomen, and to compare the image quality and lesion conspicuity among the reconstruction strength levels. This prospective study included 59 patients with 373 hepatic lesions who underwent dynamic contrast-enhanced CT of the abdomen. All images were reconstructed using four reconstruction algorithms, including 40% adaptive statistical iterative reconstruction-Veo (ASiR-V) and DLIR at low, medium, and high-strength levels (DLIR-L, DLIR-M, and DLIR-H, respectively). The signal-to-noise ratio (SNR) of the abdominal aorta, portal vein, liver, pancreas, and spleen and the lesion-to-liver contrast-to-noise ratio (CNR) were calculated and compared among the four reconstruction algorithms. The diagnostic acceptability was qualitatively assessed and compared among the four reconstruction algorithms and the conspicuity of hepatic lesions was compared between <5 and≥5 mm lesions. The SNR of each anatomical structure (p<0.0001) and CNR (p<0.0001) were significantly higher in DLIR-H than the other reconstruction algorithms. Diagnostic acceptability was significantly better in DLIR-M than the other reconstruction algorithms (p<0.0001). The conspicuity of hepatic lesions was highest when using 40% ASiR-V and tended to lessen as the reconstruction strength level was getting higher in DLIR, especially in <5 mm lesions; however, all hepatic lesions could be detected. DLIR improved the SNR, CNR, and image quality compared with 40% ASiR-V, while making it possible to decrease lesion conspicuity using higher reconstruction strength.

Diagnostic yield of colonoscopy surveillance in testicular cancer survivors treated with platinum-based chemotherapy: study protocol of a prospective cross-sectional cohort study

BackgroundTesticular cancer (TC) survivors have an increased risk of various second primary malignancies. A recent cohort study detected an increased risk of colorectal cancer (CRC) in TC survivors treated with platinum-based chemotherapy with a hazard ratio of 3.9. CRC risk increased with higher cisplatin-dose. We know that colonoscopy surveillance in high-risk populations results in reduced incidence and mortality of CRC. TC survivors treated with platinum-based chemotherapy can potentially benefit from colonoscopy surveillance; however, to which extent is unknown. Furthermore, the pathogenesis of these secondary CRCs is unknown, and better insights into the carcinogenesis may affect surveillance decisions.MethodsThis prospective multicenter study will be performed in four Dutch hospitals. TC survivors are eligible if treated with ≥ 3 cycles of cisplatin before age 50. Colonoscopy will be performed ≥ 8 years after initial treatment (minimum and maximum ages at colonoscopy, 35 and 75 years, respectively). The primary aim of the study is the diagnostic yield of advanced neoplasia detected during colonoscopy. As secondary aim, we will evaluate the molecular profile of advanced colorectal neoplasia and will assess current platinum levels in blood and urine and correlate blood-platinum levels with prevalence of colorectal lesions. Furthermore, we will investigate effectiveness of fecal immunochemical testing (FIT) and burden of colonoscopy by two questionnaires. Demographic data, previous history, results of colonoscopy, hemoglobin level of FIT and results of molecular and platinum levels will be obtained. Yield of colonoscopy will be determined by detection rate of adenoma and serrated lesions, advanced adenoma detection rate and CRC detection rate. The MISCAN model will be used for cost-effectiveness analyses of CRC surveillance. With 234 participants undergoing colonoscopy, we can detect an absolute difference of 6% of advanced neoplasia with 80% power.DiscussionTC survivors treated with cisplatin-based chemotherapy can benefit from CRC surveillance. Evaluation of the diagnostic performance and patient acceptance of CRC surveillance is of importance to develop surveillance recommendations. Insight into the carcinogenesis of cisplatin-related advanced colorectal lesions will contribute to CRC prevention in the increasing number of TC survivors. The results may also be important for the many other cancer survivors treated with platinum-based chemotherapy.Trial registrationClinical Trials: NCT04180033, November 27, 2019, https://clinicaltrials.gov/ct2/show/NCT04180033.

Ultra-low-dose thoracic CT with model-based iterative reconstruction (MBIR) in cystic fibrosis patients undergoing treatment with cystic fibrosis transmembrane conductance regulators (CFTR)

To assess the utility of a volumetric low-dose computed tomography (CT) thorax (LDCTT) protocol at a dose equivalent to a posteroanterior (PA) and lateral chest radiograph for surveillance of cystic fibrosis (CF) patients. A prospective study was undertaken of 19 adult patients with CF that proceeded to LDCTT at 12 and 24 months following initiation of ivacaftor. A previously validated seven-section, low-dose axial CT protocol was used for the 12-month study. A volumetric LDCTT protocol was developed for the 24-month study and reconstructed with hybrid iterative reconstruction (LD-ASIR) and pure iterative reconstruction (model-based IR [LD-MBIR]). Radiation dose was recorded for each scan. Image quality was assessed quantitatively and qualitatively, and disease severity was assessed using a modified Bhalla score. Statistical analysis was performed and p-values of <0.05 were considered statistically significant. Volumetric LD-MBIR studies were acquired at a lower radiation dose than the seven-section studies (0.08±0.01 versus 0.10±0.02 mSv; p=0.02). LD-MBIR and seven-section ASIR images had significantly lower levels of image noise compared with LD-ASIR images (p<0.0001). Diagnostic acceptability scores and depiction of bronchovascular structures were found to be acceptable for axial and coronal LD-MBIR images. LD-MBIR images were superior to LD-ASIR images for all qualitative parameters assessed (p<0.0001). No significant change was observed in mean Bhalla score between 1-year and 2-year studies (p=0.84). The use of a volumetric LDCTT protocol (reconstructed with pure IR) enabled acquisition of diagnostic quality CT images, which were considered extremely useful for surveillance of CF patients, at a dose equivalent to a PA and lateral chest radiograph.

Model-based iterative reconstruction in paediatric head computed tomography: a pilot study on dose reduction in children.

PurposeTo evaluate the potential of model-based iterative reconstruction (MBIR) on dose reduction and image quality in children undergoing computed tomography (CT) head examinations.Material and methodsThis prospective study was approved by the institutional ethics committee. A total of 88 children (age range of 5 to 16 years) with a history of seizures underwent contrast-enhanced CT scan. Forty-one children underwent CT study according to the MBIR technique, while 47 children underwent CT of the head with the non-MBIR protocol. Images were reviewed by 2 blinded paediatric radiologists in a random order. Mean dose-length product, CT dose index (CTDI) volume, and mean effective dose were recorded for both groups. Image quality, image noise, and diagnostic acceptability of 2 image sets were also recorded.ResultsIn the MBIR group, the mean dose-length product was reduced by 79.8%; the mean CTDI volume was reduced by 88.5%, while the mean effective dose was reduced by 81% when compared to the non-MBIR group. No significant difference was seen in diagnostic acceptability, image noise, and image quality between the 2 groups.ConclusionsMBIR technique is highly effective in reducing radiation dose in paediatric head CT examinations without any significant difference in image quality, image noise, and diagnostic acceptability.

Utility of fast non-local means (FNLM) filter for detection of pulmonary nodules in chest CT for pediatric patient.

This study was aimed to evaluate the utility based on imaging quality of the fast non-local means (FNLM) filter in diagnosing lung nodules in pediatric chest computed tomography (CT). We retrospectively reviewed the chest CT reconstructed with both filtered back projection (FBP) and iterative reconstruction (IR) in pediatric patients with metastatic lung nodules. After applying FNLM filter with six h values (0.0001, 0.001, 0.01, 0.1, 1, and 10) to the FBP images, eight sets of images including FBP, IR, and FNLM were analyzed. The image quality of the lung nodules was evaluated objectively for coefficient of variation (COV), contrast to noise ratio (CNR), and point spread function (PSF), and subjectively for noise, sharpness, artifacts, and diagnostic acceptability. The COV was lowest in IR images and decreased according to increasing h values and highest with FBP images (P<0.001). The CNR was highest with IR images, increased according to increasing h values and lowest with FBP images (P<0.001). The PSF was lower only in FNLM filter with h value of 0.0001 or 0.001 than in IR images (P<0.001). In subjective analysis, only images of FNLM filter with h value of 0.0001 or 0.001 rarely showed unacceptable quality and had comparable results with IR images. There were less artifacts in FNLM images with h value of 0.0001 compared with IR images (p<0.001). FNLM filter with h values of 0.0001 allows comparable image quality with less artifacts compared with IR in diagnosing metastatic lung nodules in pediatric chest CT.

Clinical Awareness and Acceptance of Sonographically Diagnosed Epiploic Appendagitis (EA): A Retrospective Analysis of EA in a Single Tertiary Academic Referral Center.

Purpose To describe the clinical awareness and acceptance of ultrasound-diagnosed acute epiploic appendagitis (EA) and their importance to avoid unnecessary therapeutic and imaging measures. Patients and Methods The data were obtained of n=54 patients with acute, localized, peritonitic pain and EA diagnosed by B-mode ultrasound and contrast-enhanced ultrasound examination from November 2003 to September 2020. All examinations were performed by a German Society for Ultrasound in Medicine (DEGUM) Level III qualified examiner. Based on documentation by the treating physicians, the clinical awareness and acceptance of EA diagnosis was determined in all patients and compared between subgroups diagnosed before 2013 and from 2013 onwards. In 2013, a local educational training program regarding the diagnosis of and therapy for EA was initiated for physicians. Results In all patients, EA was sonographically diagnosed by a DEGUM level III qualified examiner. At enrollment, EA was mentioned as a suspected clinical diagnosis in n=1/54 (1.9%) patient. Furthermore, in n=39/54 (72.2%) cases, the EA was documented and accepted by the treating physicians at the time of patient discharge as the final clinical diagnosis. The clinical acceptance was significantly higher from 2013 onwards compared with before 2013 (p<0.05). Moreover, in n=26/54 (48.1%) patients, unnecessary therapeutic measures were initiated, with no significant difference between pre-2013 and post-2013 numbers (p>0.05). Conclusion In our retrospective study, we showed that awareness and acceptance of the disease EA are low. Low diagnostic acceptance of EA by the clinician leads to unnecessary therapeutic and imaging measures and is a general problem related to rare diseases in the healthcare system.