ACTA Radiologica (Test)

Acta Radiologica, Ahead of Print. <br/>BackgroundDual-layer spectral-detector computed tomography (DLCT) may have the potential to evaluate gastric wall thickening.PurposeTo evaluate the efficacy of DLCT quantitative parameters in differentiating between benign and malignant thickening of the gastric wall.Material and MethodsA total of 58 patients with “gastric wall thickening” who underwent multi-phase abdominal enhanced DLCT scans were included in this study. Of these patients, 33 were malignant and 25 were benign. Parameters such as iodine concentration (IC), effective atomic number (Zeff), and attenuation of the lesions were measured during the arterial phase (AP) and venous phase (VP). Binary logistic regression was employed to calculate the combined prediction probabilities. The accuracy of the DLCT parameters was assessed using receiver operating characteristic (ROC) curves.ResultsThe values of IC, nIC, Zeff, normalized Zeff, and attenuation in the AP and VP were significantly higher (all P < 0.05) in the malignant group compared to the benign group. The ROC curves revealed that the IC, Zeff, and attenuation in the VP exhibited high diagnostic performance, with area under the ROC curve (AUC) values of 0.864, 0.862, and 0.840, respectively. The new combination of these three factors and gastric wall thickness had an AUC of 0.884, and the sensitivity and specificity were determined to be 81.8% and 92.0%, respectively.ConclusionSpectral CT parameters, particularly the combination of gastric wall thickness, attenuation, IC, and Zeff in VP, have value in distinguishing between benign and malignant gastric wall thickening.

Acta Radiologica, Ahead of Print. <br/>BackgroundApproximately half of all patients with hepatocellular carcinoma (HCC) develop cachexia during the course of the disease. It is important to be able to predict which patients will develop cachexia at an early stage.PurposeTo develop and validate a nomogram based on the magnetic resonance imaging (MRI) features of HCC and body composition for potentially predicting cachexia in patients with HCC.Material and MethodsA retrospective two-center study recruited the pretreatment clinical and MRI data of 411 patients with HCC undergoing abdominal MRI. The data were divided into three cohorts for development, internal validation, and external validation. Patients were followed up for six months after the MRI scan to record each patient's weight to diagnose cachexia. Logistic regression analyses were performed to identify independent variables associated with cachexia in the development cohort used to build the nomogram.ResultsThe multivariable analysis suggested that the MRI parameters of tumor size > 5 cm (P = 0.001), intratumoral artery (P = 0.004), skeletal muscle index (P < 0.001), and subcutaneous fat area (P = 0.004) were independent predictors of cachexia in patients with HCC. The nomogram derived from these parameters in predicting cachexia reached an area under receiver operating characteristic curve of 0.819, 0.783, and 0.814 in the development, and internal and external validation cohorts, respectively.ConclusionThe proposed multivariable nomogram suggested good performance in predicting the risk of cachexia in HCC patients.

Acta Radiologica, Ahead of Print. <br/>Radiographic measurements play a crucial role in evaluating the alignment of distal radius fractures (DRFs). Various manual methods have been used to perform the measurements, but they are susceptible to inaccuracies. Recently, computer-aided methods have become available. This review explores the methods commonly used to assess DRFs. The review introduces the different measurement techniques, discusses the sources of measurement errors and measurement reliability, and provides a recommendation for their use. Radiographic measurements used in the evaluation of DRFs are not reliable. Standardizing the measurement techniques is crucial to address this and automated image analysis could help improve accuracy and reliability.

Acta Radiologica, Ahead of Print. <br/>BackgroundStudies report that Lisfranc injury is more common than thought. Several imaging methods for assessing the stability of Lisfranc injury have been described but many are impossible to standardize and not accurate enough.PurposeTo present a three-dimensional (3D) method for analyzing the changes in the joint space width of the midfoot joint and the joints of the medial part of the Lisfranc complex in healthy individuals.Material and MethodsNon-weightbearing and weightbearing cone-beam computed tomography (CBCT) images of 11 healthy feet were acquired and analyzed with 3D software. The mean range of joint space width changes of each joint was computed from the changes in individual image pairs.Results3D analysis software was used to analyze the medial part of the Lisfranc complex. In this sample of healthy feet, the changes in the joint spaces in the medial part of Lisfranc complex, calculated with 3D analysis software, was less than 0.6 mm. The distance between bones increased or decreased, depending on which part of the joint surface the measurements were taken.ConclusionIn this study, we present a 3D analysis method to evaluate midfoot joint space width changes. Our analysis revealed that in healthy feet there are only minimal changes in the joint space width between weightbearing and non-weightbearing indicating minimal movement of the midtarsal joints. The 3D analysis of weightbearing CBCT data provides a promising tool for analyzing the small midfoot joints in a variety of conditions.

Acta Radiologica, Ahead of Print. <br/>BackgroundThe optimal primary debulking surgery outcome of serous ovarian carcinoma (SOC) is greatly affected by primary ovarian neoplasm or metastatic lesion close to the rectum.PurposeTo study the risk factors affecting postoperative residual primary ovarian neoplasm or metastatic lesion close to the rectum of SOC.Material and MethodsThe clinical and MRI data of 164 patients with SOC eligible from institution A (training and test groups) and 36 patients with SOC eligible from institution B (external validation group) were collected and retrospectively analyzed. The clinical data included age, serum carbohydrate antigen 125 (CA-125), human epididymis protein 4, and neutrophil-to-lymphocyte ratio (NLR). Magnetic resonance imaging (MRI) data included ovarian mass distribution, maximum diameter of ovarian mass, ovarian mass features, degree of rectal invasion of the primary ovarian neoplasm or metastatic lesion, and amount of ascites. A model was established using multivariate logistic regression.ResultsBy univariate and multivariate logistic regressions, CA-125 (P = 0.024, odds ratio [OR] = 3.798, 95% confidence interval [CI] = 1.24–13.32), NLR (P = 0.037, OR = 3.543, 95% CI = 1.13–12.72), and degree of rectal invasion of the primary ovarian neoplasm or metastatic lesion (P < 0.001, OR = 37.723, 95% CI = 7.46–266.88) were screened as independent predictors. The area under the curve values of the model in the training, test, and external validation groups were 0.860, 0.764, and 0.778, respectively.ConclusionThe clinical-radiological model based on T1-weighted dual-echo MRI can be used non-invasively to predict postoperative residual ovarian neoplasm or metastasis close to SOC in the rectum.

Acta Radiologica, Ahead of Print. <br/>BackgroundThe capsular ligaments at the hip joint work in synchrony with the acetabulum and femoral head for articular stability. There is a lack of understanding about ischiofemoral ligament (ISFL) anatomy and function.PurposeTo assess the insertion of the ISFL in non-arthritic adult hips.Material and MethodsA retrospective analysis was performed in 72 patients who underwent magnetic resonance arthrogram (MRA) for the assessment of hip pain. The distribution of the ISFL components, the thickness, and the insertion site were assessed by concomitantly using the axial oblique, coronal, and sagittal MRA images.ResultsTwo insertions of the ISFL anterior to the center of the femoral head were identified in 71 (99%) hips: (i) predominant anterior merging with the iliofemoral ligament as continuation of zona orbicularis, observed in all hips; and (ii) anterolateral junction of femoral neck and greater trochanter. Two ISFL parts (proximal and distal) were identified in 70 (97%) of the 72 studied hips. The proximal part was always thinner (mean 2.6 ± 0.7 mm) and originated from the ischium at the acetabular rim. The distal part was a continuation of the zona orbicularis, and the mean thickness was 6.7 ± 1.6 mm. Both parts merged as they coursed over the superior portion of the femoral head.ConclusionThe predominant insertion of the ischiofemoral ligament is a merging to the iliofemoral ligament anteriorly. Surgical procedures such as hip arthroscopy involving the ISFL will affect the function of the iliofemoral ligament, and vice versa.

Acta Radiologica, Ahead of Print. <br/>BackgroundThe fatty infiltration and atrophy in the muscle after a rotator cuff (RC) tear are important in surgical decision-making and are linked to poor clinical outcomes after rotator cuff repair. An accurate and reliable quantitative method should be developed to assess the entire RC muscles.PurposeTo develop a fully automated approach based on a deep neural network to segment RC muscles from clinical magnetic resonance imaging (MRI) scans.Material and MethodsIn total, 94 shoulder MRI scans (mean age = 62.3 years) were utilized for the training and internal validation datasets, while an additional 20 MRI scans (mean age = 62.6 years) were collected from another institution for external validation. An orthopedic surgeon and a radiologist manually segmented muscles and bones as reference masks. Segmentation performance was evaluated using the Dice score, sensitivities, precision, and percent difference in muscle volume (%). In addition, the segmentation performance was assessed based on sex, age, and the presence of a RC tendon tear.ResultsThe average Dice score, sensitivities, precision, and percentage difference in muscle volume of the developed algorithm were 0.920, 0.933, 0.912, and 4.58%, respectively, in external validation. There was no difference in the prediction of shoulder muscles, with the exception of teres minor, where significant prediction errors were observed (0.831, 0.854, 0.835, and 10.88%, respectively). The segmentation performance of the algorithm was generally unaffected by age, sex, and the presence of RC tears.ConclusionWe developed a fully automated deep neural network for RC muscle and bone segmentation with excellent performance from clinical MRI scans.

Acta Radiologica, Ahead of Print. <br/>BackgroundThe impact of excluding intrahepatic segmental vessels from regions of interest (ROIs) on liver stiffness measurement (LSM) via magnetic resonance elastography (MRE) remains uncertain.PurposeTo determine the effect of excluding intrahepatic segmental vessels from ROIs on LSM obtained from MRE.Material and MethodsThis retrospective analysis included 95 participants who underwent successful two-dimensional gradient recalled-echo MRE before hepatic tumor resection (n = 49) or living liver donation (n = 46). The conventional LSM was determined by manually drawing ROIs on the elastogram within the 95% confidence region, staying 1 cm within the liver capsule and excluding large hilar vessels, the gallbladder, hepatic lesions, and artifacts. In addition, the modified LSM was determined by excluding intrahepatic segmental vessels. LSMs obtained by the two methods were compared with paired sample signed-rank test. Diagnostic performance for advanced fibrosis was calculated and compared using McNemar's test and Delong's test. The stage of hepatic fibrosis was assessed using surgical specimens by the METAVIR system.ResultsThe modified LSM was larger than the conventional LSM (2.4 kPa vs. 2.2 kPa in reader 1; 2.7 kPa vs. 2.4 kPa in reader 2; P < 0.001). The modified LSM showed superior sensitivity (0.841 vs. 0.659 in reader 1; 0.864 vs. 0.705 in reader 2; P < 0.05) and area under the curve (0.901 vs. 0.820 in reader 1; 0.912 vs. 0.843 in reader 2; P < 0.05) for detecting advanced fibrosis (≥F3) than conventional LSM.ConclusionThe exclusion of intrahepatic segmental vessels from ROIs in MRE affected the LSM and enhanced diagnostic performance for advanced fibrosis.

Acta Radiologica, Ahead of Print. <br/>Spinal bone lesions encompass a wide array of pathologies, spanning from benign abnormalities to aggressive malignancies, such as diffusely localized metastases. Early detection and accurate differentiation of the underlying diseases is crucial for every patient's clinical treatment and outcome, with radiological imaging being a core element in the diagnostic pathway. Across numerous pathologies and imaging techniques, deep learning (DL) models are progressively considered a valuable resource in the clinical setting. This review describes not only the diagnostic performance of these models and the differing approaches in the field of spinal bone malignancy recognition, but also the lack of standardized methodology and reporting that we believe is currently hampering this newly founded area of research. In line with their established and reliable role in lesion detection, this publication focuses on both computed tomography and magnetic resonance imaging, as well as various derivative modalities (i.e. SPECT). After conducting a systematic literature search and subsequent analysis for applicability and quality using a modified QUADAS-2 scoring system, we confirmed that most of the 14 identified studies were plagued by major limitations, such as insufficient reporting of model statistics and data acquisition, a lacking external validation dataset, and potentially biased annotation. Although we experienced these limitations, we nonetheless conclude that the potential of these methods shines through in the presented results. These findings underline the need for more stringent quality controls in DL studies, as well as model development to afford increased insight and progress in this promising novel field.

Acta Radiologica, Ahead of Print. <br/>BackgroundThe best settings of deep learning image reconstruction (DLIR) algorithm for abdominal low-kiloelectron volt (keV) virtual monoenergetic imaging (VMI) have not been determined.PurposeTo determine the optimal settings of the DLIR algorithm for abdominal low-keV VMI.Material and MethodsThe portal-venous phase computed tomography (CT) scans of 109 participants with 152 lesions were reconstructed into four image series: VMI at 50 keV using adaptive statistical iterative reconstruction (Asir-V) at 50% blending (AV-50); and VMI at 40 keV using AV-50 and DLIR at medium (DLIR-M) and high strength (DLIR-H). The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of nine anatomical sites were calculated. Noise power spectrum (NPS) using homogenous region of liver, and edge rise slope (ERS) at five edges were measured. Five radiologists rated image quality and diagnostic acceptability, and evaluated the lesion conspicuity.ResultsThe SNR and CNR values, and noise and noise peak in NPS measurements, were significantly lower in DLIR images than AV-50 images in all anatomical sites (all P < 0.001). The ERS values were significantly higher in 40-keV images than 50-keV images at all edges (all P < 0.001). The differences of the peak and average spatial frequency among the four reconstruction algorithms were significant but relatively small. The 40-keV images were rated higher with DLIR-M than DLIR-H for diagnostic acceptance (P < 0.001) and lesion conspicuity (P = 0.010).ConclusionDLIR provides lower noise, higher sharpness, and more natural texture to allow 40 keV to be a new standard for routine VMI reconstruction for the abdomen and DLIR-M gains higher diagnostic acceptance and lesion conspicuity rating than DLIR-H.