European Journal of Radiology最新文献

Purpose

To construct a nomogram for predicting lymphovascular invasion (LVI) in N0 stage non-small cell lung cancer (NSCLC) using dual-energy computed tomography (DECT) findings combined with clinical findings.

Methods

We retrospectively recruited 135 patients with N0 stage NSCLC from two hospitals underwent DECT before surgery and were divided into development cohort (n = 107) and validation cohort (n = 28). The clinical findings (baseline characteristics, biochemical markers, serum tumor markers and Immunohistochemical markers), DECT-derived parameters (iodine concentration [IC], effective atomic number [Eff-Z] and normalized iodine concentration [NIC], iodine enhancement [IE] and NIC ratio [NICr]) and Fractal dimension (FD) were collected and measured. A nomogram was constructed using significant findings to predict LVI in N0 stage NSCLC and was externally validated.

Results

Multivariable analysis revealed that lymphocyte count (LYMPH, odds ratio [OR]: 3.71, P=0.014), IC in arterial phase (ICa, OR: 1.25, P=0.021), NIC in venous phase (NICv, OR: 587.12, P=0.009) and FD (OR: 0.01, P=0.033) were independent significant factors for predicting LVI in N0 stage NSCLC, and were used to construct a nomogram. The nomogram exhibited robust predictive capabilities in both the development and validation cohort, with AUCs of 0.819 (95 % CI: 72.6–90.4) and 0.844 (95 % CI: 68.2–95.8), respectively.

The calibration plots showed excellent agreement between the predicted probabilities and the actual rates of positive LVI, on external validation.

Conclusions

Combination of clinical and DECT imaging findings could aid in predicting LVI in N0 stage NSCLC using significant findings of LYMPH, ICa, NICv and FD.

Purpose

To create a simple model using standard BI-RADS® descriptors from pre-treatment B-mode ultrasound (US) combined with clinicopathological tumor features, and to assess the potential of the model to predict the presence of residual tumor after neoadjuvant chemotherapy (NAC) in breast cancer (BC) patients.

Method

245 female BC patients receiving NAC between January 2017 and December 2019 were included in this retrospective study. Two breast imaging fellows independently evaluated representative B-mode tumor images from baseline US. Additional clinicopathological tumor features were retrieved. The dataset was split into 170 training and 83 validation cases. Logistic regression was used in the training set to identify independent predictors of residual disease post NAC and to create a model, whose performance was evaluated by ROC curve analysis in the validation set. The reference standard was postoperative histology to determine the absence (pathological complete response, pCR) or presence (non-pCR) of residual invasive tumor in the breast or axillary lymph nodes.

Results

100 patients (40.8%) achieved pCR. Logistic regression demonstrated that tumor size, microlobulated margin, spiculated margin, the presence of calcifications, the presence of edema, HER2-positive molecular subtype, and triple-negative molecular subtype were independent predictors of residual disease. A model using these parameters demonstrated an area under the ROC curve of 0.873 in the training and 0.720 in the validation set for the prediction of residual tumor post NAC.

Conclusions

A simple model combining standard BI-RADS® descriptors from pre-treatment B-mode breast US with clinicopathological tumor features predicts the presence of residual disease after NAC.

Background

Usual interstitial pneumonia (UIP) cases without honeycombing (possible UIP) included various CT features and was often difficult to diagnose.

Purpose

This study aimed to classify the cases with possible UIP on CT features using cluster analysis and evaluate the features of subsets of participants and the correlation of prognosis.

Materials and Methods

The study included 85 patients with possible UIP in the 2011 idiopathic pulmonary fibrosis (IPF) guideline with radiological diagnosis. All cases underwent surgical biopsies and were diagnosed by multidisciplinary discussion (MDD) from the nationwide registry in Japan. The readers evaluated pulmonary opacity, nodules, cysts, and predominant distribution which were reclassified by IPF guidelines in 2018. Additionally, cases were classified into four groups by cluster analysis based on CT findings. The differences in survival among IPF classification and the clusters were evaluated.

Results

Cases were diagnosed as IPF (n = 55), NSIP (n = 4), unclassifiable (n = 23), and others (n = 3) by MDD. Cluster analysis revealed 4 clusters by CT features (n = 47, 16, 19 and 3, respectively). Cluster 1 had fewer lesions overall. Cluster 2 have many pure ground-glass opacities and ground-glass opacities with reticulation. Cluster 3 had many reticular opacities and nodules with few lower predominant distributions. Cluster 4 was characterized by peribronchovascular consolidation.The mean survival time of cluster 1 (4518 days) was significantly better than cluster 2, 3, and 4 (1843, 2196, and 1814 days, respectively) (p = 0.03).

Conclusion

In conclusion, UIP without honeycombing included various CT patterns and MDD diagnoses. Significangly differences in prognosis were observed among clusters classified by CT findings.

Purpose

Intraplaque haemorrhage (IPH) is a well-known risk factor for faster plaque progression (volume increase); however, its etiology is unclear. We aimed at determining what other local plaque- and systemic factors contribute to plaque progression and to the development and progression of IPH.

Methods

We examined 98 asymptomatic participants with carotid plaque using serial multi-contrast magnetic resonance imaging. We measured the percent of wall volume (%WV=100 x [wall volume] / [total vessel volume]) and measured IPH and calcification volumes. We used generalized estimating equations-based regression to analyze predictors of %WV change and new IPH while accounting for covariates (sex, age and statin use), and multiple non-independent observations per participant.

Results

Total follow-up was 1.8 ± 0.8 years on average. The presence of IPH (β: 0.6 %/y, p = 0.033) and calcification (β: 1.2 %/y, p = 0.028) were each associated with faster plaque progression. New IPH, detected on a subsequent scan in 4 % of arteries that did not initially have IPH, was associated with larger calcification (odds ratio [OR]: 2.6 per 1-SD increase, p = 0.038) and higher pulse pressure (OR: 2.3 per 1-SD increase, p = 0.016). Larger calcification was associated with greater increases in pulse pressure (β: 1.4 mm Hg/y per 1-SD increase, p = 0.040).

Conclusions

IPH and calcification are each independently associated with faster plaque progression. The association of carotid calcification to increased pulse pressure and new IPH development suggests a possible mechanism by which calcification drives IPH development and plaque progression.

Purpose

Radiation induced changes in bone such as radiation osteitis are commonly identified on magnetic resonance imaging (MRI) in patients who receive radiotherapy for soft tissue sarcoma (STS) management. This study proposes a novel MRI scoring system to assess osseous lesions and predict potential for malignancy based on MRI score in STS patients who received radiotherapy.

Methods

The MRI score consisted of 3 parameters: morphology, signal intensity, and progression. Interobserver reliability between MRI scores were analyzed with Cohen’s kappa coefficient. Receiver operating curve (ROC) analysis was performed to determine a predictive MRI score for malignancy.

Results

156 MRI’s from 30 STS patients who received radiotherapy were retrospectively reviewed. Two (6.7 %) patients developed regional osseous metastasis identified on MRI. The kappa coefficient of the scoring system was 0.785 demonstrating substantial interobserver agreement (p < 0.001). ROC analysis demonstrated that the optimal cut-off value for malignant lesion on MRI was 5.5 (area under the curve 0.998; p < 0.001).

Conclusions

This novel MRI scoring system recommends lesions with a score of six and above to be biopsied to distinguish if malignancy is present. We believe this scoring system can be utilized by multidisciplinary care teams to guide clinical recommendations for patients with STS and MRI findings concerning for malignancy versus radiation induced changes.

Objectives

To explore the value of high-resolution MR vessel wall imaging (HR-VWI) based plaque characteristics combined with cardiovascular health (CVH) metrics in the risk evaluation of ischemic stroke attributed to middle cerebral artery (MCA) atherosclerotic stenosis.

Methods

Retrospective analysis of 209 participants with middle cerebral atherosclerosis, 146 patients with high signal in the MCA area on DWI were included in the symptomatic group, and 63 patients were included in the asymptomatic group. The degree of stenosis, enhancement ratio, plaque burden, remodeling index, and intraplaque hemorrhage were measured and compared between groups. Seven CVH metrics and other clinical data were obtained. The association between these factors and ischemic stroke was investigated by univariate and multivariate analysis.

Results

The degree of stenosis [OR, 1.036 (95 % CI, 1.014–1.058); P = 0.001], plaque burden [OR, 0.958 (95 % CI, 0.928–0.989); P = 0.009], intraplaque hemorrhage [OR, 3.530 (95 % CI, 1.233–10.110); P = 0.019], physical activity [OR, 4.321 (95 % CI, 1.526–12.231); P = 0.006], and diet [OR, 8.986 (95 % CI, 2.747–29.401); P < 0.001] were the independent characteristics associated with the occurrence of ischemic stroke. ROC curve showed that the combination of plaque characteristics, diet, and physical activity achieved the highest AUC of 0.828 (95 % CI 0.770–0.877; P < 0.001), with sensitivity and specificity being 86.30 % and 66.67 %, respectively.

Conclusion

Plaque characteristics combined with CVH metrics may identify high-risk populations for ischemic stroke and offer novel insights into risk evaluation and stratification.

Purpose

To benchmark image quality and corresponding radiation doses for acute abdominal CT examination across different laboratories and CT manufacturers.

Method

An anthropomorphic phantom was scanned once with local abdominal CT protocols at 40 CT scanners, from four vendors, in thirty-three sites. Quantitative image quality was evaluated by CNR and SNR in the liver and kidney parenchyma. Qualitative image quality was assessed by visual grading analysis performed by three experienced radiologists using a five-point Likert scale to score thirteen image quality criteria. The CTDI_vol was recorded for each scan. Pearson’s correlation coefficient was calculated for the continuous variables, and the intraclass correlation coefficient was used to investigate interrater reliability between the radiologists.

Results

CTDI_vol ranged from 3.5 to 12 mGy (median 5.3 mGy, third quartile 6.7 mGy). SNR in liver parenchyma ranged from 4.4 to 14.4 (median 8.5), and CNR ranged from 2.7 to 11.2 (median 6.1). A weak correlation was found between CTDI_vol and CNR (r = 0.270, p = 0.092). Variations in CNR across scanners at the same dose level CTDI_vol were observed. No significant difference in CTDI_vol or CNR was found based on scanner installation year. The oldest scanners had a 15 % higher median CTDI_vol and a 12 % lower median CNR. The ICC showed acceptable agreement for all dose groups: low (ICC=0.889), medium (ICC=0.767), high (ICC=0.847), and in low (ICC=0.803) and medium (ICC=0.811) CNR groups.

Conclusion

There was large variation in radiation dose and image quality across the different CT scanners. Interestingly, the weak correlation between CTDI_vol and CNR indicates that higher doses do not consistently improve CNR, indicating a need for systematic assessment and optimization of image quality and radiation doses for the abdominal CT examination.

Background and purpose

Radiological features on magnetic resonance imaging (MRI) were attributed to oligodendroglioma, although the diagnostic accuracy in a real-world clinical setting remains partially elusive. This study investigated the accuracy and robustness of tumor heterogeneity and tumor border delineation on T2-weighted MRI to distinguish oligodendroglioma from astrocytoma.

Materials and methods

Eight readers from three different specialties (radiology, neurology, neurosurgery) with varying levels of experience blindly rated 79 T2-weighted MR images of patients with either oligodendroglioma or astrocytoma. After the first reading session, all readers were re-invited for a second reading session within three weeks. Diagnostic accuracy, including area under the receiver operator characteristics curve (AUC), and intra-observer variability and inter-observer variability were used as outcome measures.

Results

Pooled sensitivity and specificity to distinguish oligodendroglioma from astrocytoma for the use of tumor heterogeneity were 59.9 % respectively 74.5 %, and 85.7 % respectively 40.1 % for tumor border. A second reading session did not result in a significant change in sensitivity or specificity for tumor heterogeneity (P = 0.752 and P = 0.733, respectively) or tumor border (P = 0.309 and P = 0.271, respectively). An AUC of 0.825 was achieved with regard to predicting oligodendroglial origin of gliomas. Intra-observer agreement ranged from moderate to very good for tumor heterogeneity (kappa-value 0.43–0.87) and tumor border (0.40–0.84). A moderate inter-oberserver agreement was achieved for tumor heterogeneity and tumor border (kappa-value of 0.50 and 0.45, respectively).

Conclusion

This study demonstrates that tumor heterogeneity and tumor borders on T2-weighted MRI could be used with moderate Finter-observer agreement to non-invasively distinguish oligodendroglioma from astrocytoma.

Purpose

To investigate whether reducing the volume of intravenous iodinated contrast material injected during brain computed tomography (CT) provides reliable and accurate imaging without compromising diagnostic accuracy.

Methods

This prospective study enrolled patients undergoing enhanced brain CT at a single tertiary hospital. Subjects who agreed to participate received a reduced dose of 60 ml contrast. The images were compared to an age and gender-matched control group who received the conventional 80 cc dose.

Neuroradiologists assessed image quality and interpretation using a 5-point Likert scale with six specific domains. Based on ICC, inter-rater reliability was high at 0.873. Multiple linear regression predicted overall diagnostic accuracy based on contrast dose, age, and gender. Visual Grading Characteristics (VGC) analysis was also performed to quantify regional brain enhancement differences between the two contrast groups.

Results

The study included 47 patients in the 60 cc group and 55 in the 80 cc control group. The results showed the 80 cc group had significantly higher enhancement ratings compared to 60 cc for all six structures assessed. The differences between groups ranged from −0.241 to −0.433 (p < 0.001) on the 5-point scale.The VGC analysis confirmed significantly greater brain parenchymal enhancement in the 80 cc group compared to the 60 cc group.

Conclusion

The findings indicate that reducing the intravenous iodinated contrast material volume during brain CT from 80 cc to 60 cc leads to a statistically significant reduction in image quality and diagnostic accuracy. Further research with larger cohorts is needed to confirm these findings and assess the clinical impact of these differences.