European Journal of Radiology Open最新文献

Purpose

This study assessed the serial volume changes in multiple shoulder muscles simultaneously following arthroscopic rotator cuff repair (ARCR) by a three-dimensional (3D) modeling-based sectional measurement. These volume changes were correlated with background preoperative factors.

Methods

Four consecutive magnetic resonance imaging scans (preoperatively and postoperatively at 3, 6, and 12 months) of 33 shoulders from 31 patients who underwent arthroscopic rotator cuff repair were examined. We focused on the sectional volume differences of the supraspinatus, infraspinatus, teres minor, and subscapularis between preoperatively and 3 months postoperatively (Dif.pre.3mo) and between 3 and 12 months postoperatively (Dif.3.12mo). The correlation between volume differences and clinical/demographic parameters was determined by a multivariate analysis.

Results

No statistically significant differences were observed for most serial changes in the shoulder muscle volumes. The tear-site muscles (supraspinatus and infraspinatus) showed similar tendencies for volume changes, whereas the non-tear-site muscles (teres minor and subscapularis) differed. A negative correlation was observed between Dif.pre.3mo and Dif.3.12mo for the supraspinatus, infraspinatus, and teres minor. These perioperative volume differences might correlate with tear size and symptom duration in the supraspinatus, as well as with a history of steroid injections and work and sports activity levels in the infraspinatus and teres minor.

Conclusion

The serial volume changes in multiple shoulder muscles after ARCR measured using our 3D sectional approach exhibited different tendencies and clinical implications depending on the primary and non-primary site of tears. Our method may serve as a potential indicator to facilitate muscle recovery and prevent the progression of postoperative muscle atrophy.

Purpose

To demonstrate advantages of spectral dual-layer computed tomography (CT) in diagnosing pulmonary embolism (PE). To compare D-dimer values in patients with PE and concomitant COVID-19 pneumonia to those in patients without PE and COVID-19 pneumonia. To compare D-dimer values in cases of minor versus extensive PE.

Methods

A monocentric retrospective study of 1500 CT pulmonary angiographies (CTPAs). Three groups of 500 consecutive examinations: 1) using conventional multidetector CT (CTC), 2) using spectral dual-layer CT (CTS), and 3) of COVID-19 pneumonia patients using spectral dual-layer CT (COV). Only patients with known D-dimer levels were enrolled in the study.

Results

Prevalence of inconclusive PE findings differed significantly between CTS and CTC (0.8 % vs. 5.4 %, p < 0.001). In all groups, D-dimer levels were significantly higher in PE positive patients than in patients without PE (CTC, 8.04 vs. 3.05 mg/L; CTS, 6.92 vs. 2.57 mg/L; COV, 10.26 vs. 2.72 mg/L, p < 0.001). There were also statistically significant differences in D-dimer values between minor and extensive PE in the groups negative for COVID-19 (CTC, 5.16 vs. 8.98 mg/L; CTS 3.52 vs. 9.27 mg/L, p < 0.001). The lowest recorded D-dimer value for proven PE in patients with COVID-19 pneumonia was 1.19 mg/L.

Conclusion

CTPAs using spectral dual-layer CT reduce the number of inconclusive PE findings. Plasma D-dimer concentration increases with extent of PE. Cut-off value of D-dimer with 100 % sensitivity for patients with COVID-19 pneumonia could be doubled to 1.0 mg/L. This threshold would have saved 110 (22 %) examinations in our cohort.

Conventional T1- and T2-weighted magnetic resonance imaging (MRI) of the pancreas can vary significantly due to factors such as scanner differences and pulse sequence variations. This review explores T1 and T2 mapping techniques, modern MRI methods providing quantitative information about tissue relaxation times. Various T1 and T2 mapping pulse sequences are currently under investigation. Clinical and research applications of T1 and T2 mapping in the pancreas include their correlation with fibrosis, inflammation, and neoplasms. In chronic pancreatitis, T1 mapping and extracellular volume (ECV) quantification demonstrate potential as biomarkers, aiding in early diagnosis and classification. T1 mapping also shows promise in evaluating pancreatic exocrine function and detecting glucose metabolism disorders. T2* mapping is valuable in quantifying pancreatic iron, offering insights into conditions like thalassemia major. However, challenges persist, such as the lack of consensus on optimal sequences and normal values for healthy pancreas relaxometry. Large-scale studies are needed for validation, and improvements in mapping sequences are essential for widespread clinical integration. The future holds potential for mixed qualitative and quantitative models, extending the applications of relaxometry techniques to various pancreatic lesions and enhancing routine MRI protocols for pancreatic pathology diagnosis and prognosis.

Purpose

The present study aimed to compare the computed tomography (CT) and magnetic resonance imaging (MRI) features of solid pseudopapillary neoplasms (SPNs) and pancreatic neuroendocrine neoplasms (pNENs).

Method

Lesion imaging features of 39 patients with SPNs and 127 patients with pNENs were retrospectively extracted from 104 CT and 91 MRI scans.

Results

Compared to pNEN patients, SPN patients were significantly younger (mean age 51.8 yrs versus 32.7 yrs) and more often female (female: male ratio, 5.50:1 versus 1.19:1). Most SPNs and pNENs presented as well-defined lesions with an expansive growth pattern. SPNs more often appeared as round or ovoid lesions, compared to pNENs which showed a lobulated or irregular shape in more than half of cases (p<0.01). A surrounding capsule was detected in the majority of SPNs, but only in a minority of pNENs (<0.01). Hemorrhage occurred non-significantly more often in SPNs (p=0.09). Signal inhomogeneity in T1-fat-saturated (p<0.01) and T2-weighted imaging (p=0.046) as well as cystic degeneration (p<0.01) were more often observed in SPNs. Hyperenhancement in the arterial and portal-venous phase was more common in pNENs (p<0.01). Enlargement of locoregional lymph nodes (p<0.01) and liver metastases (p=0.03) were observed in some pNEN patients, but not in SPN patients. Multivariate logistic regression identified the presence of a capsule (p<0.01), absence of arterial hyperenhancement (p<0.01), and low patient age (p<0.01), as independent predictors for SPN.

Conclusions

The present study provides three key features for differentiating SPNs from pNENs extracted from a large patient cohort: presence of a capsule, absence of arterial hyperenhancement, and low patient age.

Purpose

To determine the value of an algorithm for reducing stair-step artifacts for advanced coronary analyses in sequential mode coronary CT angiography (CCTA).

Methods

Forty patients undergoing sequential mode photon-counting detector CCTA with at least one stair-step artifact were included. Twenty patients (14 males; mean age 57±17years) with 45 segments showing stair-step artifacts and without atherosclerosis were included for CT_FFR analysis. Twenty patients (20 males; mean age 74±13years) with 22 segments showing stair-step artifacts crossing an atherosclerotic plaque were included for quantitative plaque analysis. Artifacts were graded, and CT_FFR and quantitative coronary plaque analyses were performed in standard reconstructions and in those reconstructed with a software (entitled ZeeFree) for artifact reduction.

Results

Stair-step artifacts were significantly reduced in ZeeFree compared to standard reconstructions (p<0.05). In standard reconstructions, CT_FFR was not feasible in 3/45 (7 %) segments but was feasible in all ZeeFree reconstructions. In 9/45 (20 %) segments without atherosclerosis, the ZeeFree algorithm led to a change of CT_FFR values from pathologic in standard to physiologic values in ZeeFree reconstructions. In one segment (1/22, 5 %), quantitative plaque analysis was not feasible in standard but only in ZeeFree reconstruction. The mean overall plaque volume (111±60 mm³), the calcific (77±47 mm³), fibrotic (31±28 mm³), and lipidic (4±3 mm³) plaque components were higher in standard than in ZeeFree reconstructions (overall 75±50 mm³, p<0.001; calcific 51±42 mm³, p<0.001; fibrotic 22±19 mm³, p<0.05; lipidic 3±3 mm³, p=0.055).

Conclusion

Despite the lack of reference standard modalities for CT_FFR and coronary plaque analysis, initial evidence indicates that an algorithm for reducing stair-step artifacts in sequential mode CCTA increases the rate and quality of datasets amenable to advanced coronary artery analysis, hereby potentially improving patient management.

Purpose

This study aimed to investigate differences in cervical lymph node image quality on dual-energy computed tomography (CT) scan with datasets reconstructed using filter back projection (FBP), hybrid iterative reconstruction (IR), and deep learning–based image reconstruction (DLIR) in patients with head and neck cancer.

Method

Seventy patients with head and neck cancer underwent follow-up contrast-enhanced dual-energy CT examinations. All datasets were reconstructed using FBP, hybrid IR with 30 % adaptive statistical IR (ASiR-V), and DLIR with three selectable levels (low, medium, and high) at 2.5- and 0.625-mm slice thicknesses. Herein, signal, image noise, signal-to-noise ratio, and contrast-to-noise ratio of lymph nodes and overall image quality, artifact, and noise of selected regions of interest were evaluated by two radiologists. Next, cervical lymph node sharpness was evaluated using full width at half maximum.

Results

DLIR exhibited significantly reduced noise, ranging from 3.8 % to 35.9 % with improved signal-to-noise ratio (11.5–105.6 %) and contrast-to-noise ratio (10.5–107.5 %) compared with FBP and ASiR-V, for cervical lymph nodes (p < 0.001). Further, 0.625-mm-thick images reconstructed using DLIR-medium and DLIR-high had a lower noise than 2.5-mm-thick images reconstructed using FBP and ASiR-V. The lymph node margins and vessels on DLIR-medium and DLIR-high were sharper than those on FBP and ASiR-V (p < 0.05). Both readers agreed that DLIR had a better image quality than the conventional reconstruction algorithms.

Conclusion

DLIR-medium and -high provided superior cervical lymph node image quality in head and neck CT. Improved image quality affords thin-slice DLIR images for dose-reduction protocols in the future.

Purpose

Shear wave elastography (SWE), an ultrasonographic technique to measure the elasticity of mass lesions to evaluate breast mass. This study aimed to find out the cutoff values identifying breast malignancy using the mean elasticity (E-mean) and elasticity ratio (E-ratio) of breast masses.

Methods

This retrospective study included women underwent SWE and US-guided biopsy of breast masses. During conventional US, the SWE mode was also performed, determining elasticity measurements, E-mean and E-ratio. Histopathological reports were obtained to identify mass status. The optimal and alternative cutoff values for E-mean and E-ratio to determine malignancy were assessed by receiver operating characteristic (ROC) curve analysis and Youden’s index score.

Results

Among 147 benign and 93 malignant masses, the median of E-means were 26.20 (IQR 15.70–56.60) and 141.60 (IQR 119.80–154.60) kPa and the median E-ratios were 3.11 (IQR 1.83–5.23) and 9.24 (IQR 6.76–12.44), respectively. Using Youden’s index, the optimal cutoff values for E-mean and E-ratio were 90.35 and 5.89, with sensitivity of 87.1 % and 82.8 %, specificity of 89.1 % and 83.7 %, positive predictive value (PPV) of 83.5 % and 76.2 %, negative predictive value (NPV) of 91.6 % and 88.5 %, positive likelihood ratio (LR+) of 8.00 and 5.07, and negative likelihood ratio (LR-) of 0.14 and 0.21, respectively.

Conclusion

This study revealed that SWE is useful in predicting malignancy. With the optimal cutoff values of E-mean and E-ratio at 90.35 kPa and 5.89, the sensitivity was nearly 90 % with E-mean and slightly over 80 % with E-ratio, respectively. These findings could be used in conjunction with conventional US.

Purpose

Super-resolution deep-learning-based reconstruction: SR-DLR is a newly developed and clinically available deep-learning-based image reconstruction method that can improve the spatial resolution of CT images. The image quality of the output from non-linear image reconstructions, such as DLR, is known to vary depending on the structure of the object being scanned, and a simple phantom cannot explicitly evaluate the clinical performance of SR-DLR. This study aims to accurately investigate the quality of the images reconstructed by SR-DLR by utilizing a structured phantom that simulates the human anatomy in coronary CT angiography.

Methods

The structural phantom had ribs and vertebrae made of plaster, a left ventricle filled with dilute contrast medium, a coronary artery with simulated stenosis, and an implanted stent graft. By scanning the structured phantom, we evaluated noise and spatial resolution on the images reconstructed with SR-DLR and conventional reconstructions.

Results

The spatial resolution of SR-DLR was higher than conventional reconstructions; the 10 % modulation transfer function of hybrid IR (HIR), DLR, and SR-DLR were 0.792-, 0.976-, and 1.379 cycle/mm, respectively. At the same time, image noise was lowest (HIR: 21.1-, DLR: 19.0-, and SR-DLR: 13.1 HU). SR-DLR could accurately assess coronary artery stenosis and the lumen of the implanted stent graft.

Conclusions

SR-DLR can obtain CT images with high spatial resolution and lower noise without special CT equipments, and will help diagnose coronary artery disease in CCTA and other CT examinations that require high spatial resolution.