Acta radiologica最新文献

Background: Flow-related signal void artifacts can be visualized on the T2-weighted (T2W) three-dimensional sampling perfection with application-optimized contrast (3D-SPACE) sequence. Flow void artifacts in the cerebral aqueduct and the fourth ventricle can provide information about cerebrospinal fluid (CSF) flow dynamics.

Purpose: In this study, we aimed to test the performance of the T2W 3D-SPACE sequence in assessing the CSF flow in the aqueduct and/or fourth ventricle.

Material and methods: A total of 137 patients (age range = 3-89 years) who underwent CSF flow study were included. The amount of signal loss on T2W 3D-SPACE due to flow in the aqueduct and fourth ventricle was assessed and graded using a 4-point scale of 0 (absence of flow void) to 3 (signal void filling the aqueduct and entire fourth ventricle). A correlation was then sought between the quantitative values obtained by phase-contrast magnetic resonance imaging (PC-MRI) and the amount of signal void in the 3D-SPACE sequence.

Results: At the aqueduct level, there was a statistically significant difference in the forward flow velocity and the flow volume among different grades (all P < 0.001). In the grade 3 group, CSF peak systolic flow velocity and mean flow volume were found to be significantly higher than in the other grades (P < 0.001). The mean aqueduct area in the grade 0 group was found to be significantly different from that in the other classes (P < 0.001).

Conclusion: The amount of signal loss in the fourth ventricle observed on T2W 3D-SPACE is correlated with the peak systolic velocity and flow volume measured quantitatively in PC-MRI.

Background: Rapid and accurate measurement of computed tomography (CT) image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) is a clinical challenge.

Purpose: To explore the feasibility of intelligent measurement of chest CT image noise, SNR, and CNR.

Material and methods: A total of 300 chest CT scans were included in the study, which was divided into research dataset, internal test dataset, and external test dataset. Based on the research dataset, automatically segment and measure the average CT values and standard deviation (SD) of CT values for background air and lung field under different thresholds to obtain noise, SNR, and CNR results. Using the results of manual measurements as the reference standard, we determine the optimal threshold with the highest consistency. Using internal and external test datasets, validate the consistency of automated measurements of noise, SNR, and CNR at the optimal CT threshold with reference standards.

Results: With background air set at -900 HU and lung field at -800 HU as thresholds, the automated measurements of noise, SNR, and CNR demonstrate the highest consistency with the reference standards. At the optimal threshold, the noise, SNR, and CNR measured automatically on both the internal (intraclass correlation coefficient [ICC] = 0.85-0.96) and external (ICC = 0.75-0.85) test datasets exhibit high consistency with their respective reference standards.

Conclusion: The method we explored can intelligently measure the noise, SNR, and CNR of chest CT images, exhibits high consistency with radiologists, and offers a novel tool for image quality evaluation and analysis.

Background: Acute pulmonary embolism (PE) is a disease with a serious prognosis and a high probability of death in the emergency department.

Purpose: To investigate the prediction of PE-related mortality and intensive care admission (ICU) of Qanadli (Qscore), Bova, and simplified Pulmonary Embolism Severity Index (sPESI) scores.

Material and methods: This retrospective observational study consisted of all patients diagnosed with acute PE who were imaged under computed tomography pulmonary angiography (CTPA) for a total of 5 years between 1 June 2018 and 1 June 2023. The prediction of radiological and clinical scores for mortality and ICU admission was examined.

Results: A total of 95 patients were analyzed. Patients who died and those who were admitted to the ICU had a significantly higher frequency of being found to have a high-risk (≥1) sPESI score (P = 0.04 and P = 0.016, respectively). For mortality, the sPESI score was found to be significant; the sensitivity and specificity were observed as 54% and 66% (area under the curve [AUC]=0.670, 95% confidence interval [CI]=0.527-0.814; P = 0.020). For ICU admission, the sensitivity and specificity of the Qscore, sPESI, and Bova scores were 35%, 77%, and 58%, and 78%, 65%, and 84% respectively (AUC=0.626, 95% CI=0.511-0.740, P = 0.031; AUC=0.769, 95% CI=0.674-0.865, P < 0.001; and AUC=0.767, 95% CI=0.671-0.862, P < 0.001, respectively).

Conclusion: It was found that the sPESI score was effective at predicting mortality in patients with acute PE. Qscore, sPESI, and Bova scores have been shown to be useful in predicting ICU admission.

Background: The reliability and diagnostic accuracy of commonly used diagnostic imaging modalities in the classification of lumbosacral transitional vertebrae (LSTV) are poorly known, and comparative studies are scarce.

Purpose: To compare the diagnostic performance of conventional radiography (CR), computed tomography (CT), and magnetic resonance imaging (MRI) in classifying LSTVs.

Material and methods: In this retrospective cross-sectional study, a total of 852 patients undergoing lumbar imaging studies using all three modalities were initially assessed for the presence of LSTV using CT scans. In total, 100 patients with LSTV anatomy were identified. Four readers performed blinded and independent evaluations of these 100 patients on each modality, and an experienced fellowship-trained radiologist performed a gold standard read using all three modalities. Inter-reader reliability metrics were analyzed in comparison to the gold standard. Statistical software R (4.2.1) was used for the analyses.

Results: We found superior diagnostic efficacy for CT: the sensitivity, specificity, accuracy, and balanced accuracy were 76%, 93%, 77%, and 84%, respectively. For MRI, the metrics were 54%, 88%, 56%, and 68%, and for CR 32%, 85%, 42%, and 59%, respectively. Inter-reader reliability was found to be good for CT (κ = 0.63-0.71) and fair for both CR (κ = 0.16-0.32) and MRI (κ = 0.24-0.56).

Conclusion: CT had the highest diagnostic performance in all measured metrics with good inter-reader reliability. MRI and CR showed fairly poor sensitivity and accuracy, and thus consideration should be used when classifying LSTVs with these two modalities.

Background: May-Thurner syndrome (MTS) is a continuous pathological change of the left common iliac vein intraluminal wall due to compression between the right common iliac artery and a lumbar vertebra, with clinical signs of compromised venous drainage of the left leg, which eventually leads to development of left-sided deep vein thrombosis (DVT).

Purpose: To analyze the correlation between iliac vessel geometry and probability of DVT in patients with MTS.

Material and methods: This study consists of two age-matched female groups: DVT (n = 21) and control (n = 28). Iliac vein geometry, including left common iliac vein (LCIV) diameter, percentage of stenosis, angle between LCIV and right common iliac vein (RCIV), tilt angle of each CIV with horizontal line, and crossing angle between right common iliac artery (RCIA) and LCIV, were measured on computed tomography venography (CTV) images. The probability of DVT development was assessed using logistic regression.

Results: Comparing the DVT and control groups, the mean LCIV diameter was 2.4 mm and 3.7 mm (P = 0.001), and mean LCIV stenosis was 77.7% and 68.3% (P = 0.001), respectively. After age-adjustment, the odds of left DVT in patients with MTS correlated with LCIV diameter (odds ratio [OR]=0.25, P < 0.001, 95% confidence interval [CI]=0.11-0.54), LCIV stenosis (%) (OR=1.12, P = 0.003, 95% CI=1.04-1.21), LCIV tilt angle (OR=0.95, P < 0.038, 95% CI=0.91-0.99), and angle between two CIVs (OR=1.04, P < 0.039, 95% CI=1.00-1.09).

Conclusion: LCIV diameter and percentage of stenosis, LCIV tilt angle, and CIV angle were independent risk factors for the development of DVT in patients with MTS.

Background: Lymphovascular space invasion (LVSI) is a strong and independent risk factor that increases the probability of endometrial carcinoma (EC) recurrence and reduces the survival rate of patients.

Purpose: To investigate the value of amide proton transfer weighted (APTw) and mDixon-Quant techniques in evaluating EC lymphovascular space invasion (LVSI).

Material and methods: Data of 50 EC patients (18 LVSI+ and 32 LVSI-) confirmed by surgery and pathology were retrospectively analyzed. Preoperative magnetic resonance imaging (MRI) scans included APTw and mDixon-Quant imaging. APT, transverse relaxation rate (R2*), and fat fraction (FF) plots were obtained by postprocessing. The APT, R2*, and FF values of the two groups of cases were measured by two observers.

Results: The agreement between the two observers was good. The mean APT, R2*, and FF values of LVSI+ EC were 2.947% ± 0.399%, 20.605 /s (range = 18.525-27.953), and 2.234% ± 1.047%, respectively, while the parameters of LVSI- EC were 2.628% ± 0.307%, 18.968 /s (range = 16.225-20.544), and 2.103% ± 1.070%, respectively. The APT and R2* values of LVSI+ EC were higher than those of LVSI- EC (P < 0.05). There was no significant difference in FF value between the two groups. The AUC values of APT, R2*, and APT + R2* for LVSI were 0.751, 0.713, and 0.781, respectively (all P > 0.05). APT value was moderately correlated with R2* value (r = 0.528, P < 0.001) and weakly correlated with FF value (r = 0.312, P = 0.027).

Conclusion: APTw and mDixon-Quant techniques could evaluate the LVSI status of EC, and their combined application could improve diagnostic efficiency.

Background: Meniscal ramp lesions are a special type of meniscal injury that affects the periphery of the posterior horn of the medial meniscus and/or its meniscocapsular attachments, strongly associated with anterior cruciate ligament (ACL) tears. Due to their location, these lesions can be missed arthroscopically so it is essential to diagnose them on preoperative magnetic resonance imaging (MRI).

Purpose: To evaluate the accuracy of MRI in detecting meniscal ramp lesions in patients with ACL tears using arthroscopy as the reference standard.

Material and methods: Two musculoskeletal radiologists, blinded to the surgical findings, retrospectively and independently evaluated 106 knee MRI scans for the presence of meniscal ramp lesions in non-consecutive patients who underwent arthroscopic ACL reconstruction between January 2019 and July 2022 by a single surgeon at one institution. Having arthroscopy as reference, the diagnostic sensitivity and specificity as well as the positive and negative predictive values (PPV/NPV) of the MRI scans were calculated. Cohen's kappa coefficient was used to test inter-observer reliability. A P value <0.05 was considered statistically significant.

Results: In the study group of 106 patients (72 men, 34 women; mean age = 33.84 ±13.12 years), 76 had an arthroscopy-confirmed meniscal ramp lesion, while 30 did not. The sensitivity and specificity of MRI for the detection of meniscal ramp lesion were 88% and 87%, respectively. The PPV and NPV were 94% and 74%, respectively. Inter-rater reliability was excellent (k = 0915).

Conclusion: This study demonstrates that MRI can accurately detect meniscal ramp lesions.

Background: Visual evaluation of interstitial lung disease (ILD)-related changes can generate intra- and inter-observer errors. However, recent deep learning (DL) algorithm advances have facilitated accurate lung segmentation, lesion characterization, and quantification.

Purpose: To evaluate the treatment response and long-term course in ILD associated with anti-aminoacyl-tRNA synthetase syndrome (anti-ARS ILD) using a DL algorithm.

Material and methods: Patients with anti-ARS ILD who underwent both pre- and post-initial-treatment computed tomography (CT) (n = 68) were divided into two groups (responders and non-responders) according to forced vital capacity improvement after initial treatment. We also analyzed the CT images of patients for whom long-term follow-up CT (>5 years) was performed after post-treatment CT (n = 43). DL analysis was used to classify CT imaging features into five patterns: normal; ground-glass opacity (GGO); consolidation; fibrotic lesions; and emphysema.

Results: The initial responder group had a larger volume of consolidation. Consolidation and GGO volumes decreased after initial treatment in both groups. However, whole-lung and normal-area volumes increased in the responder group; conversely, there was no significant increase in the non-responder group. At the long-term follow-up, fibrotic lesions significantly increased in both groups. The emphysema pattern increased significantly in both groups after initial treatment and long-term follow-up. Six of 26 (23.1%) responders and 8 of 17 (47.1%) non-responders were judged as having progressive pulmonary fibrosis.

Conclusion: DL-based analysis facilitated the chronological evaluation of anti-ARS ILD. During the long-term follow-up, anti-ARS ILD was associated with chronological progression, regardless of initial treatment efficacy.

Background: SynthesiZed Improved Resolution and Concurrent nOise reductioN (ZIRCON) is a multi-kernel synthesis method that creates a single series of thin-slice computed tomography (CT) images displaying low noise and high spatial resolution, increasing reader efficiency and minimizing partial volume averaging.

Purpose: To compare the diagnostic performance of a single set of ZIRCON images to two routine clinical image series using conventional CT head and bone reconstruction kernels for diagnosing intracranial findings and fractures in patients with trauma or suspected acute neurologic deficit.

Material and methods: In total, 50 patients underwent clinically indicated head CT in the ER (15 normal, 35 abnormal cases). A non-reader neuroradiologist established the reference standard. Three neuroradiologists reviewed two routine clinical series (head and bone kernels) and a single ZIRCON series, detecting intracranial findings or fractures and rating confidence (0-100). Sensitivity, specificity, and jackknife free-response receiver operating characteristic (JAFROC) figure of merit (FOM) were compared (limit of non-inferiority: -0.10).

Results: ZIRCON and conventional images demonstrated comparable performance for fractures (sensitivity: 51.5% vs. 54.5%; specificity: 40.2% vs. 34.2%) and intracranial findings (sensitivity: 88.2% vs. 91.4%; specificity: 77.2% vs. 73.7%).The estimated difference of JAFROC FOM demonstrated ZIRCON non-inferiority for acute pathologies overall (0.003 [95% CI=-0.051-0.057]) and fractures (0.048 [95% CI=-0.050-0.145]) but not for intracranial findings alone (-0.024 [95% CI=-0.100-0.052]).

Conclusion: Thin-slice, low noise, and high spatial resolution images can be created to display intracranial findings and fractures replacing multiple images series in head CT with similar performance. Future studies in more patients and further algorithmic development are warranted.