Acta radiologica最新文献

Background: The accurate evaluation of tumor response after locoregional therapy is crucial for adjusting therapeutic strategy and guiding individualized follow-up.

Purpose: To determine the inter-reader agreement of the LR-TR algorithm for hepatocellular carcinoma treated with locoregional therapy among radiologists with different seniority.

Material and methods: A total of 275 treated observations on 249 MRI scans from 99 patients were retrospectively collected. Three readers of different seniorities (senior, intermediate, and junior with 10, 6, and 2 years of experience in hepatic imaging, respectively) analyzed the presence or absence of features (arterial-phase hyperenhancement and washout) and evaluated LR-TR category.

Results: There were substantial inter-reader agreements for overall LR-TR categorization (kappa = 0.704), LR-TR viable (kappa = 0.715), and LR-TR non-viable (kappa = 0.737), but fair inter-reader agreement for LR-TR equivocal (kappa = 0.231) among three readers. The inter-reader agreement was substantial for arterial-phase hyperenhancement (kappa = 0.725), but moderate for washout (kappa = 0.443) among three readers. The inter-reader agreements between two readers were substantial for overall LR-TR categorization (kappa = 0.734, 0.727, 0.652), LR-TR viable (kappa = 0.719, 0.752, 0.678), and LR-TR non-viable (kappa = 0.758, 0.760, 0.694), which were at the same level as the inter-reader agreements among three readers. In addition, the inter-reader agreements between two readers were substantial for arterial-phase hyperenhancement (kappa = 0.733, 0.766, 0.678), but moderate for washout (kappa = 0.473, 0.422, 0.446), which were at the same level as the inter-reader agreements among three readers.

Conclusion: LR-TR algorithm demonstrated overall substantial inter-reader agreement among radiologists with different seniority.

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: 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: Recent guidelines recommend direct patient observation, pressure monitoring, and sensor devices to prevent extravasation during contrast media (CM) injection. However, it is impractical in terms of time and cost to install sensors for all patients.

Purpose: To identify risk factors for CM extravasations during contrast-enhanced computed tomography (CECT) in a large population and to establish criteria for placing the sensor device on patients.

Material and methods: This retrospective study included 143,556 patients who underwent CECT at our hospital between April 2012 and July 2022. We performed multivariable logistic regression analysis between patients with (n = 350) and randomly selected patients without CM extravasation (n = 350). We investigated the percentage of patients with sensor devices and their sensitivity for detecting extravasation using receiver operating characteristic curve analysis.

Results: The extravasation rate was 0.27%. Multivariable logistic regression analysis showed that the injection rate (adjusted odds ratio [AOR] = 1.61, 95% confidence interval [CI] = 1.33-1.95: P <0.001), catheter gauge (AOR = 3.86, 95% CI = 1.92-7.76; P <0.001), the use of anticancer drugs (AOR = 1.81, 95% CI = 1.32-2.50; P <0.001), and existing catheters (AOR = 1.52, 95% CI = 1.10-2.11; P = 0.009) were significantly associated with extravasation. To achieve a sensitivity of 90%, 80%, 70%, 60%, and 50%, 80%, 65%, 50%, 40%, and 28% of all patients required the placement of a sensor device, respectively.

Conclusion: Sensitivity analysis established criteria for effective placing sensor devices.

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.

Empirical evidence for radiomics predicting the malignant potential and Ki-67 expression in gastrointestinal stromal tumors (GISTs) is lacking. The aim of this review article was to explore the preoperative discriminative performance of radiomics in assessing the malignant potential, mitotic index, and Ki-67 expression levels of GISTs. We systematically searched PubMed, EMBASE, Web of Science, and the Cochrane Library. The search was conducted up to 30 September 2023. Quality assessment was performed using the Radiomics Quality Score (RQS). A total of 35 original studies were included in the analysis. Among them, 26 studies focused on determining malignant potential, three studies on mitotic index discrimination, and six studies on Ki-67 discrimination. In the validation set, the sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) of radiomics in the determination of high malignant potential were 0.74 (95% CI=0.69-0.78), 0.90 (95% CI=0.83-0.94), and 0.81 (95% CI=0.14-0.99), respectively. For moderately to highly malignant potential, the sensitivity, specificity, and AUC were 0.86 (95% CI=0.83-0.88), 0.73 (95% CI=0.67-0.78), and 0.88 (95% CI=0.27-0.99), respectively. Regarding the determination of high mitotic index, the sensitivity, specificity, and AUC of radiomics were 0.86 (95% CI=0.83-0.88), 0.73 (95% CI=0.67-0.78), and 0.88 (95% CI=0.27-0.99), respectively. When determining high Ki-67 expression, the combined sensitivity, specificity, and AUC were 0.74 (95% CI=0.65-0.81), 0.81 (95% CI=0.74-0.86), and 0.84 (95% CI=0.61-0.95), respectively. Radiomics demonstrates promising discriminative performance in the preoperative assessment of malignant potential, mitotic index, and Ki-67 expression levels in GISTs.

Background: Distinguishing between tumor recurrence and pseudoprogression (PsP) in high-grade glioma postoperatively is challenging. This study aims to enhance this differentiation using a combination of intratumoral and peritumoral radiomics.

Purpose: To assess the effectiveness of intratumoral and peritumoral radiomics in improving the differentiation between high-grade glioma recurrence and pseudoprogression after surgery.

Material and methods: A total of 109 cases were randomly divided into training and validation sets, with 1316 features extracted from intratumoral and peritumoral volumes of interest (VOIs) on conventional magnetic resonance imaging (MRI) and apparent diffusion coefficient (ADC) maps. Feature selection was performed using the mRMR algorithm, resulting in intratumoral (100 features), peritumoral (100 features), and combined (200 features) subsets. Optimal features were then selected using PCC and RFE algorithms and modeled using LR, SVM, and LDA classifiers. Diagnostic performance was compared using area under the receiver operating characteristic curve (AUC), evaluated in the validation set. A nomogram was established using radscores from intratumoral, peritumoral, and combined models.

Results: The combined model, utilizing 14 optimal features (8 peritumoral, 6 intratumoral) and LR as the best classifier, outperformed the single intratumoral and peritumoral models. In the training set, the AUC values for the combined model, intratumoral model, and peritumoral model were 0.938, 0.921, and 0.847, respectively; in the validation set, the AUC values were 0.841, 0.755, and 0.705. The nomogram model demonstrated AUCs of 0.960 (training set) and 0.850 (validation set).

Conclusion: The combination of intratumoral and peritumoral radiomics is effective in distinguishing high-grade glioma recurrence from pseudoprogression after surgery.