A case of hemorrhage at the junctions of the posterior intercostal arteries-a vital sign?

The authors present the case of a 58-year-old man found hanging from a radiator by his shoelaces. The time of death was approximately 6 h before the body was discovered. An autopsy was performed approximately 24 h after the body was found, which revealed hemorrhages in the thoracic aorta at the junctions of the posterior intercostal arteries. Before autopsy, a routine whole-body CT scan was performed. Histologic examination of the aorta and the posterior intercostal arteries revealed a fresh hemorrhage into the tunica adventitia of the aorta. To our knowledge, there is no case description of such findings in hanged persons in the literature. Conclusion: Hemorrhages into the tunica adventitia of the junction of the posterior costal arteries may occur in association with suicidal hanging. The significance of these hemorrhages as a sign of vitality may be debated.

MRI Extracellular Volume Fraction in Liver Fibrosis-A Comparison of Different Time Points and Blood Pool Measurements.

BACKGROUND: Extracellular volume (ECV) correlates with the degree of liver fibrosis. PURPOSE: To analyze the performance of liver MRI-based ECV evaluations with different blood pool measurements at different time points. STUDY TYPE: Prospective. SAMPLE: 73 consecutive patients (n = 31 females, mean age 56 years) with histopathology-proven liver fibrosis. FIELD STRENGTH/SEQUENCE: 3T acquisition within 90 days of biopsy, including shortened modified look-locker inversion recovery T1 mapping. ASSESSMENT: Polygonal regions of interest were manually drawn in the liver, aorta, vena cava, and in the main, left and right portal vein on four slices before and after Gd-DOTA administration at 5/10/15 minutes. ECV was calculated 1) on one single slice on portal bifurcation level, and 2) averaged over all four slices. STATISTICAL TESTS: Parameters were compared between patients with fibrosis grades F0-2 and F3-F4 with the Mann-Whitney U and fishers exact test. ROC analysis was used to assess the performance of the parameters to predict F3-4 fibrosis. A P-value <0.05 was considered statistically significant. RESULTS: ECV was significantly higher in F3-4 fibrosis (35.4% [33.1%-37.6%], 36.1% [34.2%-37.5%], and 37.0% [34.8%-39.2%] at 5/10/15 minutes) than in patients with F0-2 fibrosis (33.3% [30.8%-34.8%], 33.7% [31.6%-34.7%] and 34.9% [32.2%-36.0%]; AUC = 0.72-0.75). Blood pool T1 relaxation times in the aorta and vena cava were longer on the upper vs. lower slices at 5 minutes, but not at 10/15 minutes. AUC values were similar when measured on a single slice (AUC = 0.69-0.72) or based on blood pool measurements in the cava or portal vein (AUC = 0.63-0.67 and AUC = 0.65-0.70). DATA CONCLUSION: Liver ECV is significantly higher in F3-4 fibrosis compared to F0-2 fibrosis with blood pool measurements performed in the aorta, inferior vena cava, and portal vein at 5, 10, and 15 minutes. However, a smaller variability was observed for blood pool measurements between slices at 15 minutes. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 3.

Diagnostic accuracy of coronary artery stenosis and thrombosis assessment using unenhanced multiplanar 3D post-mortem cardiac magnetic resonance imaging.

BACKGROUND: A 3D sequence was introduced to unenhanced post-mortem cardiac magnetic resonance imaging (PMCMR) to enable multiplanar coronary artery image analysis and to investigate its diagnostic accuracy for the diagnosis of coronary artery stenosis and thrombosis. MATERIALS AND METHODS: N = 200 forensic cases with suspected coronary artery pathology underwent 3 Tesla PMCMR (sequence used: T2 weighted transversal 3D turbo spin echo) before autopsy. Main coronary artery stenosis and thrombosis were assessed in PMCMR by multiplanar image analysis by two observers. Coronary artery histology was determined as the gold standard and compared to PMCMR. Sensitivity, specificity, negative (NPV) and positive predictive values (PPV) with 95% confidence intervals were calculated. RESULTS: For all coronary arteries combined, sensitivity was 75% (PPV 73%) for the diagnosis of stenosis and 72% (PPV 71%) for the diagnosis of thrombosis. Specificity was 92% (NPV 90%) for correct diagnosis of non-existing stenosis and 97% (NPV 97%) for non-existing thrombosis. Sensitivity for correct diagnosis of different degrees of stenosis ranged between 67% and 80% (PPVs 67-82%); specificity ranged between 96% and 99% (NPVs 96-99%). CONCLUSION: Multiplanar PMCMR coronary artery stenosis and thrombosis assessment based on an unenhanced T2 weighted 3D sequence provide moderate sensitivity and high specificity for the diagnosis of coronary artery stenosis and/or thrombosis. Hence, 3D T2w PMCMR cannot reliably detect existing coronary artery stenosis and thrombosis but may be particularly useful for the exclusion of stenosis or thrombosis of the main coronary arteries.

Standards of practice in forensic age estimation with CT of the medial clavicular epiphysis-a systematic review.

The AGFAD (Arbeitsgemeinschaft für Forensische Alterdiagnostik, Study Group on Forensic Age Diagnostics) has published several recommendations regarding both technical aspects of computed tomography (CT) of the medial clavicular epiphysis (MCE) and the process of reading and interpreting the CT images for forensic age estimations (FAE). There are, however, no published recommendations regarding CT scan protocols and no dose reference values for CT of the MCE. The objective of this analysis was to assess adherence to AGFAD recommendations among practitioners of FAE and analyse reported dose-relevant CT scan parameters with the objective of helping to establish evidence-based dose reference values for FAE. A systematic literature search was conducted in PubMed and in Google Scholar with specific MeSH terms to identify original research articles on FAE with CT of the MCE from 1997 to 2022. A total of 48 studies were included. Adherence to AGFAD recommendations among practitioners of FAE is high regarding the use of Schmeling main stages (93%), bone window (79%), ≤ 1 mm CT slices (67%), axial/coronal CT images (65%), and Kellinghaus sub-stages (59%). The reporting of CT technique and CT dose-relevant scan parameters is heterogeneous and often incomplete in the current literature. Considering the success achieved by the AGFAD in creating standards of practice of FAE in living subjects, there is potential for the AGFAD to establish standards for radiation protection in FAE as well.

Influence of Lung Reconstruction Algorithms on Interstitial Lung Pattern Recognition on CT.

Despite current recommendations, there is no recent scientific study comparing the influence of CT reconstruction kernels on lung pattern recognition in interstitial lung disease (ILD).To evaluate the sensitivity of lung (i70) and soft (i30) CT kernel algorithms for the diagnosis of ILD patterns.We retrospectively extracted between 15-25 pattern annotations per case (1 annotation = 15 slices of 1 mm) from 23 subjects resulting in 408 annotation stacks per lung kernel and soft kernel reconstructions. Two subspecialized chest radiologists defined the ground truth in consensus. 4 residents, 2 fellows, and 2 general consultants in radiology with 3 to 13 years of experience in chest imaging performed a blinded readout. In order to account for data clustering, a generalized linear mixed model (GLMM) with random intercept for reader and nested for patient and image and a kernel/experience interaction term was used to analyze the results.The results of the GLMM indicated, that the odds of correct pattern recognition is 12 % lower with lung kernel compared to soft kernel; however, this was not statistically significant (OR 0.88; 95%-CI, 0.73-1.06; p = 0.187). Furthermore, the consultants' odds of correct pattern recognition was 78 % higher than the residents' odds, although this finding did not reach statistical significance either (OR 1.78; 95%-CI, 0.62-5.06; p = 0.283). There was no significant interaction between the two fixed terms kernel and experience. Intra-rater agreement between lung and soft kernel was substantial (κ = 0.63 ±â€Š0.19). The mean inter-rater agreement for lung/soft kernel was κ = 0.37 ±â€Š0.17/κ = 0.38 ±â€Š0.17.There is no significant difference between lung and soft kernel reconstructed CT images for the correct pattern recognition in ILD. There are non-significant trends indicating that the use of soft kernels and a higher level of experience lead to a higher probability of correct pattern identification. · There is no significant difference between lung and soft kernel reconstructed CT images for the correct pattern recognition in interstitial lung disease.. · There are even non-significant tendencies that the use of soft kernels lead to a higher probability of correct pattern identification.. · These results challenge the current recommendations and the routinely performed separate lung kernel reconstructions for lung parenchyma analysis.. CITATION FORMAT: · Klaus JB, Christodoulidis S, Peters AA et al. Influence of Lung Reconstruction Algorithms on Interstitial Lung Pattern Recognition on CT. Fortschr Röntgenstr 2023; 195: 47 - 54.

Performance of an AI based CAD system in solid lung nodule detection on chest phantom radiographs compared to radiology residents and fellow radiologists.

BACKGROUND: Despite the decreasing relevance of chest radiography in lung cancer screening, chest radiography is still frequently applied to assess for lung nodules. The aim of the current study was to determine the accuracy of a commercial AI based CAD system for the detection of artificial lung nodules on chest radiograph phantoms and compare the performance to radiologists in training. METHODS: Sixty-one anthropomorphic lung phantoms were equipped with 140 randomly deployed artificial lung nodules (5, 8, 10, 12 mm). A random generator chose nodule size and distribution before a two-plane chest X-ray (CXR) of each phantom was performed. Seven blinded radiologists in training (2 fellows, 5 residents) with 2 to 5 years of experience in chest imaging read the CXRs on a PACS-workstation independently. Results of the software were recorded separately. McNemar test was used to compare each radiologist's results to the AI-computer-aided-diagnostic (CAD) software in a per-nodule and a per-phantom approach and Fleiss-Kappa was applied for inter-rater and intra-observer agreements. RESULTS: Five out of seven readers showed a significantly higher accuracy than the AI algorithm. The pooled accuracies of the radiologists in a nodule-based and a phantom-based approach were 0.59 and 0.82 respectively, whereas the AI-CAD showed accuracies of 0.47 and 0.67, respectively. Radiologists' average sensitivity for 10 and 12 mm nodules was 0.80 and dropped to 0.66 for 8 mm (P=0.04) and 0.14 for 5 mm nodules (P<0.001). The radiologists and the algorithm both demonstrated a significant higher sensitivity for peripheral compared to central nodules (0.66 vs. 0.48; P=0.004 and 0.64 vs. 0.094; P=0.025, respectively). Inter-rater agreements were moderate among the radiologists and between radiologists and AI-CAD software (K'=0.58±0.13 and 0.51±0.1). Intra-observer agreement was calculated for two readers and was almost perfect for the phantom-based (K'=0.85±0.05; K'=0.80±0.02); and substantial to almost perfect for the nodule-based approach (K'=0.83±0.02; K'=0.78±0.02). CONCLUSIONS: The AI based CAD system as a primary reader acts inferior to radiologists regarding lung nodule detection in chest phantoms. Chest radiography has reasonable accuracy in lung nodule detection if read by a radiologist alone and may be further optimized by an AI based CAD system as a second reader.

A Deep-Learning Diagnostic Support System for the Detection of COVID-19 Using Chest Radiographs: A Multireader Validation Study.

MATERIALS AND METHODS: Five publicly available databases comprising normal CXR, confirmed COVID-19 pneumonia cases, and other pneumonias were used. After the harmonization of the data, the training set included 7966 normal cases, 5451 with other pneumonia, and 258 CXRs with COVID-19 pneumonia, whereas in the testing data set, each category was represented by 100 cases. Eleven blinded radiologists with various levels of expertise independently read the testing data set. The data were analyzed separately with the newly proposed artificial intelligence-based system and by consultant radiologists and residents, with respect to positive predictive value (PPV), sensitivity, and F-score (harmonic mean for PPV and sensitivity). The χ2 test was used to compare the sensitivity, specificity, accuracy, PPV, and F-scores of the readers and the system. RESULTS: The proposed system achieved higher overall diagnostic accuracy (94.3%) than the radiologists (61.4% ± 5.3%). The radiologists reached average sensitivities for normal CXR, other type of pneumonia, and COVID-19 pneumonia of 85.0% ± 12.8%, 60.1% ± 12.2%, and 53.2% ± 11.2%, respectively, which were significantly lower than the results achieved by the algorithm (98.0%, 88.0%, and 97.0%; P < 0.00032). The mean PPVs for all 11 radiologists for the 3 categories were 82.4%, 59.0%, and 59.0% for the healthy, other pneumonia, and COVID-19 pneumonia, respectively, resulting in an F-score of 65.5% ± 12.4%, which was significantly lower than the F-score of the algorithm (94.3% ± 2.0%, P < 0.00001). When other pneumonia and COVID-19 pneumonia cases were pooled, the proposed system reached an accuracy of 95.7% for any pathology and the radiologists, 88.8%. The overall accuracy of consultants did not vary significantly compared with residents (65.0% ± 5.8% vs 67.4% ± 4.2%); however, consultants detected significantly more COVID-19 pneumonia cases (P = 0.008) and less healthy cases (P < 0.00001). CONCLUSIONS: The system showed robust accuracy for COVID-19 pneumonia detection on CXR and surpassed radiologists at various training levels.

Minimum perceivable size difference: how well can radiologists visually detect a change in lung nodule size from CT images?

OBJECTIVE: The purpose of this study was to determine how well radiologists could visually detect a change in lung nodule size on the basis of visual image perception alone. SUBJECTS AND METHODS: Under IRB approval, 109 standard chest CT image series were anonymized and exported from PACS. Nine hundred forty virtual lung nodule pairs (six baseline diameters, six relative volume differences, two nodule types-solid and ground glass-and 14 repeats) were digitally inserted into the chest CT image series (same location, different sizes between the pair). These digitally altered CT image pairs were shown to nine radiologists who were tasked to visually determine which image contained the larger nodule using a two-alternative forced-choice perception experimental design. These data were statistically analyzed using a generalized linear mixed effects model to determine how accurately the radiologists were able to correctly identify the larger nodule. RESULTS: Nominal baseline nodule diameter, relative volume difference, and nodule type were found to be statistically significant factors (p < 0.001) in influencing the radiologists' accuracy. For solid (ground-glass) nodules, the baseline diameter needed to be at least 6.3 mm (13.2 mm) to be able to visually detect a 25% change in volume with 95 ± 1.4% accuracy. Accuracy was lowest for the nodules with the smallest baseline diameters and smallest relative volume differences. Additionally, accuracy was lower for ground-glass nodules compared to solid nodules. CONCLUSIONS: Factors that impacted visual size assessment were baseline nodule diameter, relative volume difference, and solid versus non-solid nodule type, with larger and more solid lesions offering a more precise assessment of change. KEY POINTS: • For solid nodules, radiologists could visually detect a 25% change in volume with 95% accuracy for nodules having greater than 6.3-mm baseline diameter. • For ground-glass nodules, radiologists could visually detect a 25% change in volume with 95% accuracy for nodules having greater than 13.2-mm baseline diameter. • Accuracy in detecting a change in nodule size began to stabilize around 90-100% for nodules with larger baseline diameters (> 8 mm for solid nodules, > 12 mm for ground-glass nodules) and larger relative volume differences (>15% for solid nodules, > 25% for ground-glass nodules).

Clinical Relevance of Troponin T Profile Following Cardiac Surgery.

Background: Peak post-operative cardiac troponin T (cTnT) independently predicts mid- and long-term outcome of cardiac surgery patients. A few studies however have reported two peaks of cTnT over the first 48-72 h following myocardial reperfusion. The aim of the current study was to better understand underlying reasons of these different cTnT profiles and their possible relevance in terms of clinical outcome. Methods: All consecutive adult cardiac surgical procedures performed with an extra-corporeal circulation during a >6 years period were retrospectively evaluated. Patients with a myocardial infarction (MI) < 8 days were excluded. cTnT profile of patients with at least one value ≥1 ng/mL value were categorized according to the time occurrence of the peak value. Univariable and multivariable analysis were performed to identify factors influencing early vs. late increase of cTnT values, and to verify the correlation of early vs. late increase with clinical outcome. Results: Data of 5,146 patients were retrieved from our prospectively managed registry. From 953 with at least one cTnT value ≥1 ng/mL, peak occurred ≤ 6 h (n = 22), >6 to ≤ 12 h (n = 366), >12 to ≤ 18 h (n = 176), >18 to ≤ 24 h (171), >24 h (218). Age (OR: 1.023; CI: 1.016-1.030) and isolated CABG (OR: 1.779; CI: 1.114-2.839) were independent predictors of a late increase of cTnT over a limit of 1 ng/ml (p < 0.05), whereas isolated valve procedures (OR: 0.685; CI: 0.471-0.998) and cross-clamp duration (OR: 0.993; CI: 0.990-0.997) independently predicted an early elevation (p < 0.05). Delayed elevation as opposed to early elevation correlated with a higher rate of post-operative complications including MI (19.8 vs. 7.2%), new renal insufficiency (16.3 vs. 6.7%), MACCE (32.0 vs. 15.5%), or death (7.4 vs. 4.4%). Conclusion: Profile of cTnT elevation following cardiac surgery depends on patients' intrinsic factors, type of surgery and duration of cross-clamp time. Delayed increase is of higher clinically relevance than prompt post-operative elevation.