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To investigate the diagnostic accuracy of color-coded dual-energy CT virtual non-calcium (VNCa) reconstructions for the assessment of bone marrow edema (BME) of the scaphoid in patients with acute wrist trauma. Our retrospective study included data from 141 patients (67 women, 74 men; mean age 43 years, range 19–80 years) with acute wrist trauma who had undergone third-generation dual-source dual-energy CT and 3-T MRI within 7 days. Eight weeks after assessment of conventional grayscale dual-energy CT scans for the presence of fractures, corresponding color-coded VNCa reconstructions were independently analyzed by the same six radiologists for the presence of BME. CT numbers on VNCa reconstructions were evaluated by a seventh radiologist. Consensus reading of MRI series by two additional radiologists served as the reference standard. MRI depicted 103 scaphoideal zones with BME in 76 patients. On qualitative analysis, VNCa images yielded high overall sensitivity (580/618 [94%]), specificity (1880/1920 [98%]), and accuracy (2460/2538 [97%]) for assessing BME as compared with MRI as reference standard. The interobserver agreement was excellent (κ = 0.98). CT numbers derived from VNCa images were significantly different in zones with and without edema (p

Rational and Objectives: This study investigated how an AI tool impacted radiologists reading time for non-contrast chest CT exams. Materials and Methods: An AI tool was implemented into the PACS reading workflow of non-contrast chest CT exams between April and May 2020. The reading time was recorded for one CONSULTANT RADIOLOGIST and one RADIOLOGY RESIDENT by an external observer. After each case radiologists answered questions regarding additional findings and perceived case overview. Reading times were recorded for 25 cases without and 20 cases with AI tool assistance for each reader. Differences in reading time with and without the AI tool were assessed using Welch's t-test for non-inferiority with non-inferiority limits defined as 100 seconds for the consultant and 200 seconds for the resident. Results: The mean reading time for the radiology resident was not significantly affected by the AI tool (without AI 370s vs with AI 437s; +67s 95% CI -28s to +163s, p = 0.16). The reading time for the radiology consultant was also not significantly affected by the AI tool (without AI 366s vs with AI 380s; +13s (95% CI - -57s to 84s, p = 0.70). The AI tool led to additional actionable findings in 5/40 (12.5%) studies and better overview in 18/20 (90%) of studies for the resident. Conclusion: A PACS based implementation of an AI tool for concurrent reading of chest CT exams did not increase reading time with additional actionable findings made as well as a perceived better case overview for the radiology resident.

Summary Background MRI is generally considered as the gold standard for measuring breast volume because of its high accuracy of the modality. Many techniques used to measure total breast volume have been validated, but none of these techniques have been validated for their ability to measure the volume retention of fat grafts in the breast. In this study, the authors investigated the accuracy of the most common MRI technique used to measure fat graft retention in the breast by measuring the volume changes after breast augmentation. Methods Patients undergoing breast augmentation with either breast implants or fat grafting underwent MRI scans before and after surgery. Blinded observers measured the change in breast volume from the MRI scans. The difference between the measured change in breast volume and the volume of the breast augmentation was used to determine the accuracy of the MRI technique. Results Twenty-eight patients with a total of 56 breasts were included. In total, 168 measurements of change in breast volume were performed by the observers. The MRI measurements of change in breast volume overestimated the true volumes of the breast augmentations by an average of 50.8%, and only 8 of the 168 individual measurements had measurement errors below 50 mL. Conclusion The MRI technique, which is considered as the gold standard for the quantification of fat graft volume retention, was associated with a significant measurement error. These findings have potential implications for the interpretation of previously published results of studies based on this technique.

Background Dual-energy CT (DECT) can acknowledge differences in tissue compositions and can colour-code tissues with specific features including monosodium urate (MSU) crystals. However, when evaluating gout patients, DECT frequently colour-codes material not truly representing MSU crystals and this might lead to misinterpretations. The characteristics of and variations in properties of colour-coded DECT lesions in gout patients have not yet been systematically investigated. The objective of this study was to evaluate the properties and locations of colour-coded DECT lesions in gout patients. Methods DECT of the hands, knees and feet were performed in patients with suspected gout using factory default gout settings, and colour-coded DECT lesions were registered. For each lesion, properties [mean density (mean of Hounsfield Units (HU) at 80 kV and Sn150kV), mean DECT ratio and size] and location were determined. Subgroup analysis was performed post hoc evaluating differences in locations of lesions when divided into definite MSU depositions and possibly other lesions. Results In total, 4033 lesions were registered in 27 patients (23 gout patients, 3918 lesions; 4 non-gout patients, 115 lesions). In gout patients, lesions had a median density of 160.6 HU and median size of 6 voxels, and DECT ratios showed an approximated normal distribution (mean 1.06, SD 0.10), but with a right heavy tail consistent with the presence of smaller amounts of high effective atomic number lesions (e.g. calcium-containing lesions). The most common locations of lesions were 1st metatarsophalangeal (MTP1), knee and midtarsal joints along with quadriceps and patella tendons. Subgroup analyses showed that definite MSU depositions (large volume, low DECT ratio, high density) had a similar distribution pattern, whereas possible calcium-containing material (high DECT ratio) and non-gout MSU-imitating lesions (properties as definite MSU depositions in non-gout patients) were primarily found in some larger joints (knee, midtarsal and talocrural) and tendons (Achilles and quadriceps). MTP1 joints and patella tendons showed only definite MSU depositions. Conclusion Colour-coded DECT lesions in gout patients showed heterogeneity in properties and distribution. MTP1 joints and patella tendons exclusively showed definite MSU depositions. Hence, a sole focus on these regions in the evaluation of gout patients may improve the specificity of DECT scans.

Joint pain and osteoarthritis (OA) are some of the most common causes of lameness in horses, and most of the available treatments focus on symptomatic relief without a disease-modifying effect. TRPV1 is a potential target for treating joint diseases, including OA, and the present study aims to investigate if the TRPV1 receptor is present in equine articular tissue and determine whether the number of receptors is upregulated in joint inflammation. Metacarpo/metatarsophalangeal (MCP/MTP) joints from 15 horses euthanised for reasons unrelated to this study were included. Based on synovial fluid analysis, macroscopic evaluation, and magnetic resonance imaging (MRI), joints were divided into two groups: healthy joints and joints with pathology. ELISA analysis was performed on synovial tissue harvested from all joints. TPRV1 was found in all joints. The mean concentration of TRPV1 compared to total protein in healthy joints (8.4 &times, 10&minus, 7 ng/mL) and joints with pathology (12.9 &times, 7 ng/mL) differed significantly (p = 0.01, t-test with Welch correction). Quantitative real-time reverse transcriptase PCR analysis was performed on RNA isolates from synovial tissue from all joints. TRPV1 mRNA expression ratio normalized to glyceraldehyde 3-phosphate dehydrogenase (GAPDH) in healthy joints (0.16 (SD: 0.19)) and joints with pathology (0.24 (SD: 0.14)) did not differ significantly (p = 0.43, t-test with Welch correction). mRNA expression of interleukin-6 (IL-6) and tumor necrosis factor alpha (TNF-) was very low for both groups. In conclusion, TRPV1 was detected both on mRNA and the protein level, with a higher expression of TRPV1 in samples from joints with pathology. Future studies will determine the clinical potential of equine TRPV1 as a target in the management of joint pain and inflammation.

Pneumoperitoneum, the presence of air within the peritoneal cavity, is a comparatively rare but potentially urgent critical finding in patients presenting with acute abdominal pain. When prior laparoscopic treatment can be ruled out as a cause, it can indicate perforation of the wall of a hollow organ, which typically necessitates immediate surgery. Computed tomography (CT) is the gold standard for detecting free intra-abdominal air, yet subtle cases are easy to miss. More crucially though, if there is no initial suspicion of pneumoperitoneum, the scans may not be read immediately as other emergency patients take precedence. Therefore, fully automatic detection would provide a direct clinical benefit. In this work, an algorithm for this purpose is proposed which follows a sliding-window approach and has a deep-learning based classifier at its core. In addition to the baseline method, variants that rely on multi-scale inputs and recurrent layers to increase robustness are presented. In a five-fold cross validation on the training data, consisting in abdominal CT scans of 110 affected patients and 29 controls, our method achieved an area under the receiver-operating characteristic curve of 89% for case-level classification. Due to its high specificity at reasonable detection rates, it shows potential for use in triage, where false alerts are considered particularly harmful as they may disrupt the clinical workflow.

Summary: Several techniques for measuring breast volume (BV) are based on examining the breast on magnetic resonance imaging. However, when techniques designed to measure total BV are used to quantify BV changes, for example, after fat grafting, a systematic error is introduced because BV changes lead to contour alterations of the breast. The volume of the altered breast includes not only the injected volume but also tissue previously surrounding the breast. Therefore, the quantitative difference in BV before and after augmentation will differ from the injected volume. Here, we present a new technique to measure BV changes that compensates for this systematic error by defining the boundaries of the breast to immovable osseous pointers. This approach avoids the misinterpretation of tissue included within the expanded boundaries as graft tissue. This new method of analysis may be a reliable tool for assessing BV changes to determine fat graft retention and may be useful for evaluating and comparing available surgical techniques for breast augmentation and reconstruction using fat grafting.