ACTA Radiologica (Test)

Acta Radiologica, Ahead of Print. <br/>BackgroundVisual 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.PurposeTo 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 MethodsPatients 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.ResultsThe 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.ConclusionDL-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.

Acta Radiologica, Ahead of Print. <br/>BackgroundDistinguishing 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.PurposeTo assess the effectiveness of intratumoral and peritumoral radiomics in improving the differentiation between high-grade glioma recurrence and pseudoprogression after surgery.Material and MethodsA 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.ResultsThe 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).ConclusionThe combination of intratumoral and peritumoral radiomics is effective in distinguishing high-grade glioma recurrence from pseudoprogression after surgery.

Acta Radiologica, Ahead of Print. <br/>BackgroundLymphovascular 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.PurposeTo investigate the value of amide proton transfer weighted (APTw) and mDixon-Quant techniques in evaluating EC lymphovascular space invasion (LVSI).Material and MethodsData 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.ResultsThe 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).ConclusionAPTw and mDixon-Quant techniques could evaluate the LVSI status of EC, and their combined application could improve diagnostic efficiency.

Acta Radiologica, Ahead of Print. <br/>BackgroundRadiomics has become an important tool for distinguishing benign and malignant vertebral compression fractures (VCFs). It is more clinically significant to concentrate on patients who have malignant tumors and differentiate between benign and malignant VCFs.PurposeTo explore the value of multiple machine learning (ML) models based on CT radiomics features for differentiating benign and malignant VCFs in patients with malignant tumors.Material and MethodsThis study retrospectively analyzed 78 patients with malignant tumors accompanied by VCFs, 45 patients with benign VCFs, and 33 patients with malignant VCFs. A total of 140 lesions (86 benign lesions, 54 malignant lesions) were ultimately included in this study. All patients were divided into training sets (n = 98) and validation sets (n = 42) according to the 7:3 ratio. The radiomics features were screened and dimensioned, and multiple radiomics ML models were constructed. The receiver operating characteristic (ROC) curve was performed to assess the diagnostic performance.ResultsFive radiomics features were included in the model. All the ML models built have good diagnostic efficiency, among which the support vector machine (SVM) model performs better. The area under the curve (AUC), sensitivity, specificity, and accuracy in the training set were 0.908, 0.816, 0.883, and 0.857, respectively, while those in the validation set were 0.911, 0.647, 0.92, and 0.81, respectively.ConclusionA variety of ML models built based on CT radiomics features have good value for differentiating benign and malignant VCFs in malignant tumor patients, and the SVM model has a better performance.

Acta Radiologica, Ahead of Print. <br/>BackgroundMyocardial fibrosis is often detected in patients with hypertrophic cardiomyopathy (HCM), which causes left ventricular (LV) dysfunction and tachyarrhythmias.PurposeTo evaluate the potential value of a machine learning (ML) approach that uses radiomic features from late gadolinium enhancement (LGE) and cine images for the prediction of ventricular tachyarrhythmia (VT) in patients with HCM.Material and MethodsHyperenhancing areas of LV myocardium on LGE images were manually segmented, and the segmentation was propagated to corresponding areas on cine images. Radiomic features were extracted using the PyRadiomics library. The least absolute shrinkage and selection operator (LASSO) method was employed for radiomic feature selection. Our model development employed the TabPFN algorithm, an adapted Prior-Data Fitted Network design. Model performance was evaluated graphically and numerically over five-repeat fivefold cross-validation. SHapley Additive exPlanations (SHAP) were employed to determine the relative importance of selected radiomic features.ResultsOur cohort consisted of 60 patients with HCM (73.3% male; median age = 51.5 years), among whom 17 had documented VT during the follow-up. A total of 1612 radiomic features were extracted for each patient. The LASSO algorithm led to a final selection of 18 radiomic features. The model achieved a mean area under the receiver operating characteristic curve of 0.877, demonstrating good discrimination, and a mean Brier score of 0.119, demonstrating good calibration.ConclusionRadiomics-based ML models are promising for predicting VT in patients with HCM during the follow-up period. Developing predictive models as clinically useful decision-making tools may significantly improve risk assessment and prognosis.

Acta Radiologica, Ahead of Print. <br/>BackgroundTemporal bone pneumatization (TBP) is influenced by age, sex, and race, and it seems to progress rapidly to puberty. However, the extent of TBP in childhood remains unclear.PurposeTo investigate the progression of TBP in children aged 1–18 years via three-dimensional (3D) reconstruction of high-resolution computed tomography (CT) images.Material and MethodsA total of 432 temporal bones of 216 individuals aged 1–18 years with well-pneumatized mastoid antra on both sides were included in this retrospective work. We created 18 age groups, each with six boys and six girls. Surface rendering of air density was performed using −290 HU to obtain TBP. Statistical analysis employed SPSS version 24.0 software (IBM Corp., Armonk, NY, USA).ResultsThe linear regression equations that considered age and volume for all cases (ya), male (ym) and female (yf) were ya = 384.42x + 1790.40, R2 = 0.425; ym = 431.54x + 1440.9, R2 = 0.501; and yf = 337.26 x + 2140.5, R2 = 0.355. Both male and female individuals showed an increase in the average value of pneumatization until the age of 17, and the values ​​of pneumatization at specific ages for boys and girls showed differences. The mean male and female TBP levels differed significantly at 3, 11, and 18 years of age (P < 0.05).ConclusionTBP in boys was greater than that of girls at adolescence. It was possible to identify the specific periods of significant variation in the degree of pneumatization of temporal bone.

Acta Radiologica, Ahead of Print. <br/>BackgroundThe O-RADS scoring has been proposed to standardize the reporting of adnexal lesions using magnetic resonance imaging (MRI).PurposeTo assess intra- and inter-observer agreement of the O-RADS scoring using non-dynamic MRI and its agreement with pathologic diagnosis, and to provide the pitfalls in the scoring based on discordant ratings.Material and MethodsAdnexal lesions that were diagnosed using non-dynamic MRI at two centers were scored using O-RADS. Intra- and inter-observer agreements were assessed using kappa statistics. Cross-tabulations were made for intra- and inter-observer ratings and for O-RADS scores and pathological findings.ResultsIntra- and inter-observer agreements were assessed for 404 lesions in 339 patients who were admitted to center 1. Intra-observer agreement was almost perfect (97.8%, kappa = 0.963) and inter-observer agreement was substantial (83.2%, kappa = 0.730). The combined data from center 1 and center 2 included 496 patients; of them, 295 (59.5%) were operated. There was no borderline or malignant pathology for the lesions with O-RADS 1 or 2. Of those with an O-RADS score of 3, 3 (4.1%) lesions were borderline and none were malignant. The O-RADS scoring in discriminating borderline/malignant lesions from benign lesions was outstanding (area under the ROC curve 0.950, 95% CI = 0.923–0.971). Sensitivity, specificity, positive, and negative predictive values of O-RADS 4/5 lesions for borderline/malignant lesions were 96.2%, 87.1%, 72.8%, and 98.4%, respectively.ConclusionThe O-RADS scoring using non-dynamic MRI is a reproducible method and has good discrimination for borderline/malignant lesions. Potential factors that may lead to discordant ratings are provided here.

Acta Radiologica, Ahead of Print. <br/>BackgroundPharmacological inhibition of aryl hydrocarbon receptor (AhR) activation after ischemia alleviates cerebral ischemia/reperfusion (IR) injury.PurposeTo investigate whether AhR antagonist administration after reperfusion was also effective in attenuating cerebral IR injury.Material and MethodsA total of 24 Sprague–Dawley rats were divided into the sham-operated group (no IR), control group (IR), and 6,2′,4′-trimethoxyflavone (TMF) group (IR + TMF administration), with 10 rats assigned to each group. Cerebral IR injury was induced by 60 min of middle cerebral artery occlusion followed by reperfusion. TMF (5 mg/kg) was used as the AhR antagonist and was administered intraperitoneally immediately after reperfusion. Cerebral IR injury was observed using magnetic resonance imaging (MRI) and neurobehavioral assessments at baseline, immediately after ischemia, and at 3 days after ischemia.ResultsOn MRI, the TMF group showed no significant differences in relative apparent diffusion coefficient (ADC), T2, and fractional anisotropy (FA) values; midline shift value; and infarct volume. In terms of neurobehavioral function, factors such as grip strength, contralateral forelimb use, time to touch, and time to remove adhesive tape from the forepaw, were also not significantly different between the control and TMF groups.ConclusionThis study demonstrated that AhR treatment after reperfusion had no noticeable effect on reducing cerebral IR injury in rats.

Acta Radiologica, Ahead of Print. <br/>BackgroundThe neurophysiological mechanisms underlying manifestations of bulbar paralysis in acute thyrotoxic myopathy (ATM) and the afflicted brain areas are unclear.PurposeWe used resting-state functional magnetic resonance imaging (rs-fMRI) to evaluate the regional brain activities in patients with ATM.Material and MethodsIn total, 16 patients with ATM, 16 patients with hyperthyroidism without ATM, and 16 healthy controls underwent functional MRI scans. By calculating the fractional amplitude of low-frequency fluctuation (fALFF), regional homogeneity (ReHo), and functional connectivity (FC), we assessed variations in resting-state cerebral activity. The correlation between the resting-state functional indexes and clinical assessments was also explored.ResultsCompared to the hyperthyroid patients, patients with ATM had stronger ReHo in the left precentral gyrus, reduced ReHo in the left orbitofrontal gyrus (OFG), and decreased FC in the left precentral gyri, left superior frontal gyrus (SFG), and left middle frontal gyrus (MFG). Patients with ATM showed reduced fALFF and ReHo in the right SFG and decreased ReHo in the bilateral supplementary motor area (SMA). A significantly decreased FC in the left SFG and left MFG, right precentral gyrus, and the orbital part of the right interior frontal gyrus was observed in patients with ATM compared to healthy controls. Additionally, fALFF and ReHo values were positively correlated with serum thyroid-related hormones and antibodies.ConclusionThe findings of rs-fMRI demonstrate that particular brain regions’ functional activity was aberrant in individuals with ATM, especially in SFG area. This finding may help with better understanding of underlying pathophysiology of patients with ATM.

Acta Radiologica, Ahead of Print. <br/>