Standard CT Research Articles

Diagnostic Accuracy of Ultra-Low Dose CT Compared to Standard Dose CT for Identification of Fresh Rib Fractures by Deep Learning Algorithm.

The present study aimed to evaluate the diagnostic accuracy of ultra-low dose computed tomography (ULD-CT) compared to standard dose computed tomography (SD-CT) in discerning recent rib fractures using a deep learning algorithm detection of rib fractures (DLADRF). A total of 158 patients undergoing forensic diagnosis for rib fractures were included in this study: 50 underwent SD-CT, and 108 were assessed using ULD-CT. Junior and senior radiologists independently evaluated the images to identify and characterize the rib fractures. The sensitivity of rib fracture diagnosis by radiologists and radiologist + DLADRF was better using SD-CT than ULD-CT. However, the diagnosis sensitivity of DLADRF using ULD-CT alone was slightly more than SD-CT. Nonetheless, no substantial differences were observed in specificity, positive predictive value, and negative predictive value between SD-CT and ULD-CT by the same radiologist, radiologist + DLADRF, and DLADRF (P > 0.05). The area under the curve (AUC) of receiver operating characteristic indicated that senior radiologist + DLADRF was significantly better than senior and junior radiologists, junior radiologists + DLADRF, and DLADRF alone using SD-CT or ULD-CT (all P < 0.05). Also, junior radiologists + DLADRF was better with ULD-CT than senior and junior radiologists (P < 0.05). The AUC of the rib fracture diagnosed by senior radiologists did not differ from DLADRF using ULD-CT. Also, no significant differences were observed between junior + AI and senior and between junior and DLADRF using SD-CT. DLADRF enhanced the diagnostic performance of radiologists in detecting recent rib fractures. The diagnostic outcomes between SD-CT and ULD-CT across radiologists' experience and DLADRF did not differ significantly.

MR Cranial Bone Imaging: Evaluation of Both Motion-Corrected and Automated Deep Learning Pseudo-CT Estimated MR Images.

CT imaging exposes patients to ionizing radiation. MR imaging is radiation free but previously has not been able to produce diagnostic-quality images of bone on a timeline suitable for clinical use. We developed automated motion correction and use deep learning to generate pseudo-CT images from MR images. We aim to evaluate whether motion-corrected pseudo-CT produces cranial images that have potential to be acceptable for clinical use. Patients younger than age 18 who underwent CT imaging of the head for either trauma or evaluation of cranial suture patency were recruited. Subjects underwent a 5-minute golden-angle stack-of-stars radial volumetric interpolated breath-hold MR image. Motion correction was applied to the MR imaging followed by a deep learning-based method to generate pseudo-CT images. CT and pseudo-CT images were evaluated and, based on indication for imaging, either presence of skull fracture or cranial suture patency was first recorded while viewing the MR imaging-based pseudo-CT and then recorded while viewing the clinical CT. A total of 12 patients underwent CT and MR imaging to evaluate suture patency, and 60 patients underwent CT and MR imaging for evaluation of head trauma. For cranial suture patency, pseudo-CT had 100% specificity and 100% sensitivity for the identification of suture closure. For identification of skull fractures, pseudo-CT had 100% specificity and 90% sensitivity. Our early results show that automated motion-corrected and deep learning-generated pseudo-CT images of the pediatric skull have potential for clinical use and offer a high level of diagnostic accuracy when compared with standard CT scans.

Deep learning CT reconstruction improves liver metastases detection

ObjectivesDetection of liver metastases is crucial for guiding oncological management. Computed tomography through iterative reconstructions is widely used in this indication but has certain limitations. Deep learning image reconstructions (DLIR) use deep neural networks to achieve a significant noise reduction compared to iterative reconstructions. While reports have demonstrated improvements in image quality, their impact on liver metastases detection remains unclear. Our main objective was to determine whether DLIR affects the number of detected liver metastasis. Our secondary objective was to compare metastases conspicuity between the two reconstruction methods.MethodsCT images of 121 patients with liver metastases were reconstructed using a 50% adaptive statistical iterative reconstruction (50%-ASiR-V), and three levels of DLIR (DLIR-low, DLIR-medium, and DLIR-high). For each reconstruction, two double-blinded radiologists counted up to a maximum of ten metastases. Visibility and contour definitions were also assessed. Comparisons between methods for continuous parameters were performed using mixed models.ResultsA higher number of metastases was detected by one reader with DLIR-high: 7 (2–10) (median (Q₁–Q₃); total 733) versus 5 (2–10), respectively for DLIR-medium, DLIR-low, and ASiR-V (p < 0.001). Ten patents were detected with more metastases with DLIR-high simultaneously by both readers and a third reader for confirmation. Metastases visibility and contour definition were better with DLIR than ASiR-V.ConclusionDLIR-high enhanced the detection and visibility of liver metastases compared to ASiR-V, and also increased the number of liver metastases detected.Critical relevance statementDeep learning-based reconstruction at high strength allowed an increase in liver metastases detection compared to hybrid iterative reconstruction and can be used in clinical oncology imaging to help overcome the limitations of CT.Key PointsDetection of liver metastases is crucial but limited with standard CT reconstructions.More liver metastases were detected with deep-learning CT reconstruction compared to iterative reconstruction.Deep learning reconstructions are suitable for hepatic metastases staging and follow-up.Graphical

Early bifurcation of the common hepatic artery: A pitfall that should be known and recognized

Early bifurcation of the common hepatic artery (EBCHA) is a rare anatomical variation (1%), that is often overlooked but can lead to accidental ligation of the right branch of the hepatic artery with consequent arterial ischemia of the right liver and potentially very serious complications during pancreaticoduodenectomy, partial hepatectomy, or liver harvesting for transplantation. It may be difficult to diagnose EBCHA using transverse imaging sections. However, on standard CT sections with intravenous contrast injection, three warning signs should allow the image reader to suspect it: presence of two hepatic arteries to the right of the celiac trunk, presence of a retro-portal hepatic artery, and absence of a right hepatic artery arising from the superior mesenteric artery. Analysis of the CT with reconstruction then allows for definitive diagnosis and limits the risk of accidental arterial injury or ligation.

The feasibility of CT simulation-free adaptive radiation therapy.

Novel on-board CBCT allows for improved image quality and Hounsfield unit accuracy. When coupled with online adaptive tools, this may have potential to allow for simulation and treatment to be completed in a single on-table session. To study the feasibility of a high-efficiency radiotherapy treatment workflow without the use of a separate session for simulation imaging. The dosimetric accuracy, overall efficiency, and technical feasibility were used to evaluate the clinical potential of CT simulation-free adaptive radiotherapy. Varian's Ethos adaptive radiotherapy treatment platform was upgraded with a novel CBCT system, HyperSight which reports image quality and Hounsfield unit accuracy specifications comparable to standard fan-beam CT. Using in-house developed MATLAB software, CBCT images were imported into the system and used for planning. Two test cases were completed on anthropomorphic phantoms equipped with small volume ion chambers (cross-calibrated to an ADCL traceable dose standard) to evaluate the feasibility and accuracy of the workflows. A simulated palliative spine treatment was planned with 8Gy in one fraction, and an intact prostate treatment was planned with 60Gy in 20 fractions. The CBCTs were acquired using HyperSight with default thorax and pelvis imaging protocols and reconstructed using an iterative algorithm with scatter removal, iCBCT Acuros. CBCTs were used for contouring and planning, and treatment was delivered via an online adaptive workflow. In addition, an external dosimetry audit was completed using only on-board CBCT imaging in an end-to-end head and neck phantom irradiation. An extended-field CBCT acquisition can be acquired in 12s, in addition to the time for longitudinal table shifts, and reconstructed in approximately 1min. The superior-inferior extent for the CBCT planning images was 38.2cm, which captured the full extent of relevant anatomy. The contouring and treatment planning for the spine and prostate were completed in 30 and 18min, respectively. The dosimetric agreement between ion chamber measurements and the treatment plan was within a range of -1.4 to 1.6%, and a mean and standard deviation of 0.41±1.16%. All metrics used in the external audit met the passing criteria, and the dosimetric comparison between fan-beam and CBCT techniques had a gamma passing rate of 99.0% with a criteria of 2%/2mm. Using an in-house workflow, CT simulation-free radiation therapy was shown to be feasible with acceptable workflow efficiency and dosimetric accuracy. This approach may be particularly applicable for urgent palliative treatments. With the availability of software to enable this workflow, and the continued advancement of on-treatment adaptation, single-visit radiation therapy may replace current practice for some clinical indications.

Post-contrast CT liver attenuation alone is superior to the liver-spleen difference for identifying moderate hepatic steatosis.

To assess the diagnostic performance of post-contrast CT for predicting moderate hepatic steatosis in an older adult cohort undergoing a uniform CT protocol, utilizing hepatic and splenic attenuation values. A total of 1676 adults (mean age, 68.4 ± 10.2 years; 1045M/631F) underwent a CT urothelial protocol that included unenhanced, portal venous, and 10-min delayed phases through the liver and spleen. Automated hepatosplenic segmentation for attenuation values (in HU) was performed using a validated deep-learning tool. Unenhanced liver attenuation < 40.0 HU, corresponding to > 15% MRI-based proton density fat, served as the reference standard for moderate steatosis. The prevalence of moderate or severe steatosis was 12.9% (216/1676). The diagnostic performance of portal venous liver HU in predicting moderate hepatic steatosis (AUROC = 0.943) was significantly better than the liver-spleen HU difference (AUROC = 0.814) (p < 0.001). Portal venous phase liver thresholds of 80 and 90 HU had a sensitivity/specificity for moderate steatosis of 85.6%/89.6%, and 94.9%/74.7%, respectively, whereas a liver-spleen difference of -40 HU and -10 HU had a sensitivity/specificity of 43.5%/90.0% and 92.1%/52.5%, respectively. Furthermore, livers with moderate-severe steatosis demonstrated significantly less post-contrast enhancement (mean, 35.7 HU vs 47.3 HU; p < 0.001). Moderate steatosis can be reliably diagnosed on standard portal venous phase CT using liver attenuation values alone. Consideration of splenic attenuation appears to add little value. Moderate steatosis not only has intrinsically lower pre-contrast liver attenuation values (< 40 HU), but also enhances less, typically resulting in post-contrast liver attenuation values of 80 HU or less. Moderate steatosis can be reliably diagnosed on post-contrast CT using liver attenuation values alone. Livers with at least moderate steatosis enhance less than those with mild or no steatosis, which combines with the lower intrinsic attenuation to improve detection. The liver-spleen attenuation difference is frequently utilized in routine practice but appears to have performance limitations. The liver-spleen attenuation difference is less effective than liver attenuation for moderate steatosis. Moderate and severe steatosis can be identified on standard portal venous phase CT using liver attenuation alone.

Intraindividual Comparison of Dose Reduction and Coronary Calcium Scoring Accuracy Using Kilovolt-independent and Tin Filtration CT Protocols.

Purpose To investigate the ability of kilovolt-independent (hereafter, kV-independent) and tin filter spectral shaping to accurately quantify the coronary artery calcium score (CACS) and radiation dose reductions compared with the standard 120-kV CT protocol. Materials and Methods This prospective, blinded reader study included 201 participants (mean age, 60 years ± 9.8 [SD]; 119 female, 82 male) who underwent standard 120-kV CT and additional kV-independent and tin filter research CT scans from October 2020 to July 2021. Scans were reconstructed using a Qr36f kernel for standard scans and an Sa36f kernel for research scans simulating artificial 120-kV images. CACS, risk categorization, and radiation doses were compared by analyzing data with analysis of variance, Kruskal-Wallis test, Mann-Whitney test, Bland-Altman analysis, Pearson correlations, and κ analysis for agreement. Results There was no evidence of differences in CACS across standard 120-kV, kV-independent, and tin filter scans, with median CACS values of 1 (IQR, 0-48), 0.6 (IQR, 0-58), and 0 (IQR, 0-51), respectively (P = .85). Compared with standard 120-kV scans, kV-independent and tin filter scans showed excellent correlation in CACS values (r = 0.993 and r = 0.999, respectively), with high agreement in CACS risk categorization (κ = 0.95 and κ = 0.93, respectively). Standard 120-kV scans had a mean radiation dose of 2.09 mSv ± 0.84, while kV-independent and tin filter scans reduced it to 1.21 mSv ± 0.85 and 0.26 mSv ± 0.11, cutting doses by 42% and 87%, respectively (P < .001). Conclusion The kV-independent and tin filter research CT acquisition techniques showed excellent agreement and high accuracy in CACS estimation compared with standard 120-kV scans, with large reductions in radiation dose. Keywords: CT, Cardiac, Coronary Arteries, Radiation Safety, Coronary Artery Calcium Score, Radiation Dose Reduction, Low-Dose CT Scan, Tin Filter, kV-Independent Supplemental material is available for this article. © RSNA, 2024.

Study on evaluation method of circular small shadow profusion in chest CT reconstruction images of pneumoconiosis

Objective: To select chest CT image patterns for the diagnosis of pneumoconiosis and establish a method for determining the profusion of circular small shadows in chest CT. Methods: In April 2021, 66 cases of occupational pneumoconiosis patients with digital radiography (DR) chest radiographs and chest CT imaging data with circular small shadow as the main manifestations were selected as the study objects. 1.5 mm and 5 mm chest CT axial images, 1 mm and 5 mm chest CT coronal multi-plane recombination (MPR) images, and 5 mm chest CT coronal maximum intensity projection (MIP) images were used to observe the different characteristics of pneumoconiosis patients, and were compared and analyzed with DR chest radiographs to establish the experimental chest CT standards. The consistency of the profusion results between the experimental chest CT standards and GBZ 70-2015 Diagnosis of Occupational Pneumoconiosis was verified. Results: All the 66 objects were male, including 33 cases of stage Ⅰ pneumoconiosis, 17 cases of stage Ⅱ pneumoconiosis and 16 cases of stage Ⅲ pneumoconiosis. By observing five chest CT images of 66 objects, we found that chest CT images of different modes could clearly display and identify abnormal images such as small circular shadow, large shadow, small shadow aggregation, honeycomb glass shadow, flake glass shadow, uniform low-profusion glass shadow, mesh glass shadow, cable shadow, linear shadow, subpleural spinous shadow, subpleural nodules, various kinds of emphysema and lung texture distortion and fracture. Small shadow aggregation was usually accompanied by the appearance of large shadow. The vascular shadows in 5 mm CT images had good ductility, and small nodules were easy to distinguish. The coronal MIP image of 5 mm chest CT used edge enhancement technology, which was prone to small shadow fusion and fibrotic shadow fusion. The coronal MPR image of 5 mm chest CT was highly consistent with the DR chest radiographs in terms of the integrity of film reading. GBZ 70-2015 standard was used to compare the profusion of DR chest radiographs and 5 mm chest CT coronal MPR images of 66 objects, and the consistency test Kappa=0.64. GBZ 70-2015 standard and experimental chest CT standard were used to compare the profusion results of DR chest radiographs and 5 mm chest CT coronal MPR images of 66 objects, respectively, and the consistency test Kappa=0.80, with high consistency. Conclusion: 5 mm coronal MPR image is suitable for chest CT imaging in the diagnosis of pneumoconiosis. Following the selection path and method of GBZ 70-2015 profusion criterion, the established experimental chest CT standard in determining the profusion of small circular shadows in 5 mm coronal MPR images of chest CT with pneumoconiosis has a high consistency with GBZ 70-2015 standard.

Electron density dual-energy CT can improve the detection of lumbar disc herniation with higher image quality than standard and virtual non-calcium images.

To compare the diagnostic performance and image quality of dual-energy computed tomography (DECT) with electron density (ED) image reconstruction with those of DECT with standard CT (SC) and virtual non-calcium (VNCa) image reconstructions, for diagnosing lumbar disc herniation (L-HIVD). A total of 59 patients (354 intervertebral discs from T12/L1 to L5/S1; mean age, 60 years; 30 women and 29 men) who underwent DECT with spectral reconstruction and 3-T MRI within 2 weeks were enrolled between March 2021 and February 2022. Four radiologists independently assessed three image sets of randomized ED, SC, and VNCa images to detect L-HIVD at 8-week intervals. The coefficient of variance (CV) and the Weber contrast of the ROIs in the normal and diseased disc to cerebrospinal fluid space (NCR-normal/-diseased, respectively) were calculated to compare the image qualities of the noiseless ED and other series. Overall, 129 L-HIVDs were noted on MRI. In the detection of L-HIVD, ED showed a higher AUC and sensitivity than SC and VNCa; 0.871 vs 0.807 vs 833 (p = 0.002) and 81% vs 70% vs 74% (p = 0.006 for SC), respectively. CV was much lower in all measurements of ED than those for SC and VNCa (p < 0.001). Furthermore, NCR-normal and NCR-diseased were the highest in ED (ED vs SC in NCR-normal and NCR-diseased, p = 0.001 and p = 0.004, respectively; ED vs VNCa in NCR-diseased, p = 0.044). Compared to SC and VNCa images, DECT with ED reconstruction can enhance the AUC and sensitivity of L-HIVD detection with a lower CV and higher NCR. To our knowledge, this is the first study to quantify the image quality of noiseless ED images. ED imaging may be helpful for detecting L-HIVD in patients who cannot undergo MRI. ED images have diagnostic potential, but relevant quantitative analyses of image quality are limited. ED images detect disc herniation, with a better coefficient of variance and normalized contrast ratio values. ED images could detect L-HIVD when MRI is not an option.

Real-time diagnosis of intracerebral hemorrhage by generating dual-energy CT from single-energy CT

Real-time diagnosis of intracerebral hemorrhage after thrombectomy is crucial for follow-up treatment. However, this is difficult to achieve with standard single-energy CT (SECT) due to similar CT values of blood and contrast agents under a single energy spectrum. In contrast, dual-energy CT (DECT) scanners employ two different energy spectra, which allows for real-time differentiation between hemorrhage and contrast extravasation based on energy-related attenuation characteristics. Unfortunately, DECT scanners are not as widely used as SECT scanners due to their high costs. To address this dilemma, in this paper, we generate pseudo DECT images from a SECT image for real-time diagnosis of hemorrhage. More specifically, we propose a SECT-to-DECT Transformer-based Generative Adversarial Network (SDTGAN), which is a 3D transformer-based multi-task learning framework equipped with a shared attention mechanism. In this way, SDTGAN can be guided to focus more on high-density areas (crucial for hemorrhage diagnosis) during the generation. Meanwhile, the introduced multi-task learning strategy and the shared attention mechanism also enable SDTGAN to model dependencies between interconnected generation tasks, improving generation performance while significantly reducing model parameters and computational complexity. In the experiments, we approximate real SECT images using mixed 120kV images from DECT data to address the issue of not being able to obtain the true paired DECT and SECT data. Extensive experiments demonstrate that SDTGAN can generate DECT images better than state-of-the-art methods. The code of our implementation is available at https://github.com/jiang-cw/SDTGAN.

Calculation method for novel upright CT scanner isodose curves.

A computational method based on Monte-Carlo calculations is presented and used to calculate isodose curves for a new upright and tilting CT scanner useful for radiation protection purposes. The TOPAS code platform with imported CAD files for key components was used to construct a calculation space for the scanner. A sphere of water acts as the patient would by creating scatter out of the bore. Maximum intensity dose maps are calculated for various possible tilt angles to make sure radiation protection for site planning uses the maximum possible dose everywhere. The resulting maximum intensity isodose lines are more rounded than ones for just a single tilt angle and so closer to isotropic. These maximum intensity curves are closer to the isotropic assumption used in CTDI or DLP based methods of site planning and radiation protection. The isodose lines are similar to those of a standard CT scanner, just tilted upwards. There is more metal above the beam that lessens the dose above versus below isocenter. Aside from the orientation, this upright scanner is very similar to a typical CT scanner, and nothing different for shielding needs to be done for this new upright tilting CT scanner, because an isotropic scatter source is often assumed for any CT scanner.

The Additional Role of F18-FDG PET/CT in Characterizing MRI-Diagnosed Tumor Deposits in Locally Advanced Rectal Cancer.

Rationale: F18-FDG PET/CT may be helpful in baseline staging of patients with high-risk LARC presenting with vascular tumor deposits (TDs), in addition to standard pelvic MRI and CT staging. Methods: All patients with locally advanced rectal cancer that had TDs on their baseline MRI of the pelvis and had a baseline F18-FDG PET/CT between May 2016 and December 2020 were included in this retrospective study. TDs as well as lymph nodes identified on pelvic MRI were correlated to the corresponding nodular structures on a standard F18-FDG PET/CT, including measurements of nodular SUVmax and SUVmean. In addition, the effects of partial volume and spill-in on SUV measurements were studied. Results: A total number of 62 patients were included, in which 198 TDs were identified as well as 106 lymph nodes (both normal and metastatic). After ruling out partial volume effects and spill-in, 23 nodular structures remained that allowed for reliable measurement of SUVmax: 19 TDs and 4 LNs. The median SUVmax between TDs and LNs was not significantly different (p = 0.096): 4.6 (range 0.8 to 11.3) versus 2.8 (range 1.9 to 3.9). For the median SUVmean, there was a trend towards a significant difference (p = 0.08): 3.9 (range 0.7 to 7.8) versus 2.3 (range 1.5 to 3.4). Most nodular structures showing either an SUVmax or SUVmean ≥ 4 were characterized as TDs on MRI, while only two were characterized as LNs. Conclusions: SUV measurements may help in separating TDs from lymph node metastases or normal lymph nodes in patients with high-risk LARC.

Potential Benefits of Photon-Counting CT in Dental Imaging: A Narrative Review.

Background/Objectives: Advancements in oral imaging technology are continually shaping the landscape of dental diagnosis and treatment planning. Among these, photon-counting computed tomography (PCCT), introduced in 2021, has emerged as a promising, high-quality oral technology. Dental imaging typically requires a resolution beyond the standard CT systems achievable with the specialized cone-beam CT. PCCT can offer up to 100 µm resolution, improve soft-tissue contrast, and provide faster scanning times, which are crucial for detailed dental diagnosis and treatment planning. Using semiconductor detectors, PCCT produces sharper images and can potentially reduce the number of scans required, thereby decreasing patient radiation exposure. This review aimed to explore the potential benefits of PCCT in dental imaging. Methods: This review analyzed the literature on PCCT in dental imaging from January 2010 to February 2024, sourced from PubMed, Scopus, and Web of Science databases, focusing on high-resolution, patient safety, and diagnostic efficiency in dental structure assessment. We included English-language articles, case studies, letters, observational studies, and randomized controlled trials while excluding duplicates and studies unrelated to PCCT's application in dental imaging. Results: Studies have highlighted the superiority of PCCT in reducing artifacts, which are often problematic, compared to conventional CBCT and traditional CT scans, due to metallic dental implants, particularly when used with virtual monoenergetic imaging and iterative metal artifact reduction, thereby improving implant imaging. This review acknowledges limitations, such as the potential for overlooking other advanced imaging technologies, a narrow study timeframe, the lack of real-world clinical application data in this field, and costs. Conclusions: PCCT represents a promising advancement in dental imaging, offering high-resolution visuals, enhanced contrast, and rapid scanning with reduced radiation exposure.

Renal calculus composition analysis using dual-energy CT: a prospective observational study

BackgroundTo analyze preoperatively the composition of renal calculi using dual-energy computed tomography (DECT) and compare it with reference standard biochemical stone analysis.MethodsEighty-one participants who were diagnosed with renal calculi underwent DECT at 80 kVp and 140 kVp. Spectral analysis was performed, and the energy map generated was used to classify the calculus based on available preset data. Average Hounsfield units (HU) were calculated for the two energy levels, and ratio of HU was derived (DE ratio) and calculus was categorized into different stone compositions. Hounsfield units of each calculus was measured at 120 kVp standard dose CT, and Hounsfield density (HU/largest transverse diameter) was derived. Comparison of results of spectral analysis and DE ratio was done and correlated with the biochemical laboratory analysis as reference standard wherever available.ResultsSpectral analysis and CT prediction of stone were performed for all 81 patients. CT prediction of stone based on DE ratio into “uric acid,” “struvite,” “calcium oxalate” and “calcium carbonate apatite” was performed. Assessment of stone composition by biochemical analysis was done for 65 patients who eventually underwent PCNL for stone extraction.Both DE ratio and spectral analysis were able to differentiate calculus into various types based on composition with statistically significant p values. However, spectral analysis proved to be marginally better in renal stone characterization particularly for mixed stones. The DE ratio for uric acid stones was derived as 0.9–1.1, 0.9–2.3 for mixed stones and 1.0–2.4 for calcium stones.ConclusionsSpectral analysis promises a practical approach to predicting calculus composition preoperatively, thereby avoiding unnecessary surgical intervention.

Satisfactory results in five patients with septic clavicle nonunion using the modified Masquelet technique and structural iliac crest autograft

IntroductionIndications for clavicle fracture fixation have increased dramatically over the last 20 years. Chronic surgical site infection is a particularly severe complication arising from this procedure and can induce nonunion and clinical disability. In such cases, the Modified Masquelet technique using iliac crest autograft (cancellous or tricortical) enables treatment of any bone infection as well as reconstruction of the segmental defect. The aim of this study was to analyze clinical and radiological results of this procedure at mid-term follow-up. MethodsIn this monocentric retrospective study, patients suffering from a septic clavicle nonunion were treated with a Modified Masquelet technique and reviewed at a minimum follow-up point of two years. They were clinically assessed using active range of motion, pain score (Visual Analogic Scale VAS 0 to 10), Constant score, American Shoulder and Elbow Surgeon (ASES) score, and Subjective Shoulder Value score (SSV). Bone healing was measured using standard X-rays and CT scans. ResultsFive patients were included (mean age 49 years; range 30-62). C. acnes was involved in 80% (n=4) of these cases. Following the first stage of treatment, the mean bone defect was 3.4 cm (range 2.6-6.4 cm). The second stage, performed at a minimum of six weeks (mean 7±1 weeks), used an iliac crest bone autograft in all cases. At mean follow-up of 5±3 years, mean pain score was 0.3/10 points (0-1), mean Constant score was 86 points (78-96), mean ASES score was 98±2%, and the SSV score 91±11%, with two “forgotten shoulders” out of five. On CT scan analysis, bone healing was achieved in 100% of cases. One plate (20%) was removed one year following the procedure due to the patient’s discomfort; pain and discomfort at the iliac crest site was reported in 5/5 (100%) patients. ConclusionThe Modified Masquelet technique using iliac crest autograft is a reliable and effective technique for treating septic nonunion of the clavicle. It both treats the bony defect and eradicates infection when conducted in association with débridement and antibiotics. In the five cases reported here, this approach had satisfactory results, both subjectively and objectively, with a very low re-operation rate despite persistent pain from iliac bone harvesting.

Impact of temporal resolution on perfusion metrics, therapy decision, and radiation dose reduction in brain CT perfusion in patients with suspected stroke

PurposeCT perfusion of the brain is a powerful tool in stroke imaging, though the radiation dose is rather high. Several strategies for dose reduction have been proposed, including increasing the intervals between the dynamic scans. We determined the impact of temporal resolution on perfusion metrics, therapy decision, and radiation dose reduction in brain CT perfusion from a large dataset of patients with suspected stroke.MethodsWe retrospectively included 3555 perfusion scans from our clinical routine dataset. All cases were processed using the perfusion software VEOcore with a standard sampling of 1.5 s, as well as simulated reduced temporal resolution of 3.0, 4.5, and 6.0 s by leaving out respective time points. The resulting perfusion maps and calculated volumes of infarct core and mismatch were compared quantitatively. Finally, hypothetical decisions for mechanical thrombectomy following the DEFUSE-3 criteria were compared.ResultsThe agreement between calculated volumes for core (ICC = 0.99, 0.99, and 0.98) and hypoperfusion (ICC = 0.99, 0.99, and 0.97) was excellent for all temporal sampling schemes. Of the 1226 cases with vascular occlusion, 14 (1%) for 3.0 s sampling, 23 (2%) for 4.5 s sampling, and 63 (5%) for 6.0 s sampling would have been treated differently if the DEFUSE-3 criteria had been applied. Reduction of temporal resolution to 3.0 s, 4.5 s, and 6.0 s reduced the radiation dose by a factor of 2, 3, or 4.ConclusionReducing the temporal sampling of brain perfusion CT has only a minor impact on image quality and treatment decision, but significantly reduces the radiation dose to that of standard non-contrast CT.

Ultra-low dose chest CT with silver filter and deep learning reconstruction significantly reduces radiation dose and retains quantitative information in the investigation and monitoring of lymphangioleiomyomatosis (LAM)

PurposeFrequent CT scans to quantify lung involvement in cystic lung disease increases radiation exposure. Beam shaping energy filters can optimize imaging properties at lower radiation dosages. The aim of this study is to investigate whether use of SilverBeam filter and deep learning reconstruction algorithm allows for reduced radiation dose chest CT scanning in patients with lymphangioleiomyomatosis (LAM).Material and methodsIn a single-center prospective study, 60 consecutive patients with LAM underwent chest CT at standard and ultra-low radiation doses. Standard dose scan was performed with standard copper filter and ultra-low dose scan was performed with SilverBeam filter. Scans were reconstructed using a soft tissue kernel with deep learning reconstruction (AiCE) technique and using a soft tissue kernel with hybrid iterative reconstruction (AIDR3D). Cyst scores were quantified by semi-automated software. Signal-to-noise ratio (SNR) was calculated for each reconstruction. Data were analyzed by linear correlation, paired t-test, and Bland–Altman plots.ResultsPatients averaged 49.4 years and 100% were female with mean BMI 26.6 ± 6.1 kg/m2. Cyst score measured by AiCE reconstruction with SilverBeam filter correlated well with that of AIDR3D reconstruction with standard filter, with a 1.5% difference, and allowed for an 85.5% median radiation dosage reduction (0.33 mSv vs. 2.27 mSv, respectively, p < 0.001). Compared to standard filter with AIDR3D, SNR for SilverBeam AiCE images was slightly lower (3.2 vs. 3.1, respectively, p = 0.005).ConclusionSilverBeam filter with deep learning reconstruction reduces radiation dosage of chest CT, while maintaining accuracy of cyst quantification as well as image quality in cystic lung disease.Clinical relevance statementRadiation dosage from chest CT can be significantly reduced without sacrificing image quality by using silver filter in combination with a deep learning reconstructive algorithm.Key Points• Deep learning reconstruction in chest CT had no significant effect on cyst quantification when compared to conventional hybrid iterative reconstruction.• SilverBeam filter reduced radiation dosage by 85.5% compared to standard dose chest CT.• SilverBeam filter in coordination with deep learning reconstruction maintained image quality and diagnostic accuracy for cyst quantification when compared to standard dose CT with hybrid iterative reconstruction.Graphical abstract

Characteristic Features of the Novel Coronavirus Infection COVID-19 in Oncohematological Patients

Background. The novel coronavirus infection SARS-CoV-2 (COVID-19) is one of high-threat respiratory diseases, characterized by multiple organ disorders with primary respiratory failure and population mortality of 2–5 %. However, the mortality of oncohematological patients treated with chemotherapy is considerably higher.&#x0D; Aim. To analyze the COVID-19 treatment outcomes in hematological malignancy patients who received drug chemotherapy.&#x0D; Materials &amp; Methods. The clinical course of COVID-19 was analyzed in 32 hematological malignancy patients aged 31–81 years (median 62 years). The disease onset was the date of the first positive COVID-19 PCR test. These patients were transferred to an infectious hospital specialized in the therapy of the novel coronavirus infection. Pneumonia was confirmed by standard radiography and CT. Blood oxygen saturation, body temperature, ECG, and respiratory rate were monitored. Moderate and severe COVID-19 was observed in 17 (53.1 %) of 32 patients. The condition of 15 (46.9 %) patients was described as good. For comparison, a control group was collected from 32- to 79-year-old (median 63 years) patients (n = 28) having hematological malignancies but no COVID-19.&#x0D; Results. Nine (28.1 %) of 32 patients under analysis died upon increasing respiratory and multiple organ insufficiency on Day 3–17 (mean 8,6 ± 4,6 days) from the first positive COVID-19 PCR test. Death was predominantly reported in multiple myeloma patients (n = 5) as well as in a patient with Waldenstrom’s macroglobulinemia. In the control group (n = 28) with similar hematological tumors but without COVID-19, three (10.7 %) patients died throughout the 12-month follow-up period. The present paper contains a case report illustrating the clinical features of coronavirus infection in a patient with Waldenstrom’s macroglobulinemia, a monoclonal gammopathy with primary bone marrow lesions.&#x0D; Conclusion. COVID-19 is a life-threatening viral disease with high mortality in patients with hematological malignancies, especially those with plasma cell dyscrasias.

Cardiovascular Computed Tomography in the Diagnosis of Cardiovascular Disease: Beyond Lumen Assessment.

Cardiovascular CT is being widely used in the diagnosis of cardiovascular disease due to the rapid technological advancements in CT scanning techniques. These advancements include the development of multi-slice CT, from early generation to the latest models, which has the capability of acquiring images with high spatial and temporal resolution. The recent emergence of photon-counting CT has further enhanced CT performance in clinical applications, providing improved spatial and contrast resolution. CT-derived fractional flow reserve is superior to standard CT-based anatomical assessment for the detection of lesion-specific myocardial ischemia. CT-derived 3D-printed patient-specific models are also superior to standard CT, offering advantages in terms of educational value, surgical planning, and the simulation of cardiovascular disease treatment, as well as enhancing doctor-patient communication. Three-dimensional visualization tools including virtual reality, augmented reality, and mixed reality are further advancing the clinical value of cardiovascular CT in cardiovascular disease. With the widespread use of artificial intelligence, machine learning, and deep learning in cardiovascular disease, the diagnostic performance of cardiovascular CT has significantly improved, with promising results being presented in terms of both disease diagnosis and prediction. This review article provides an overview of the applications of cardiovascular CT, covering its performance from the perspective of its diagnostic value based on traditional lumen assessment to the identification of vulnerable lesions for the prediction of disease outcomes with the use of these advanced technologies. The limitations and future prospects of these technologies are also discussed.

General Algorithm Applicability in Determining DBS Lead Orientation: Adapting 2D and 3D X-Ray Techniques for SenSightTM Leads

Introduction: With recent advancements in deep brain stimulation (DBS), directional leads featuring segmented contacts have been introduced, allowing for targeted stimulation of specific brain regions. Given that manufacturers employ diverse markers for lead orientation, our investigation focuses on the adaptability of the 2017 techniques proposed by the Cologne research group for lead orientation determination. Methods: We tailored the two separate 2D and 3D X-ray-based techniques published in 2017 and originally developed for C-shaped markers, to the dual-marker of the Medtronic SenSight™ lead. In a retrospective patient study, we evaluated their feasibility and consistency by comparing the degree of agreement between the two methods. Results: The Bland-Altman plot showed favorable concordance without any noticeable systematic errors. The mean difference was 0.79°, with limits of agreement spanning from 21.4° to −19.8°. The algorithms demonstrated high reliability, evidenced by an intraclass correlation coefficient of 0.99 (p < 0.001). Conclusion: The 2D and 3D algorithms, initially formulated for discerning the circular orientation of a C-shaped marker, were adapted to the marker of the Medtronic SenSight™ lead. Statistical analyses revealed a significant level of agreement between the two methods. Our findings highlight the adaptability of these algorithms to different markers, achievable through both low-dose intraoperative 2D X-ray imaging and standard CT imaging.