Efficacy of Lung Ultrasound vs Chest X-Ray in Detecting Lung Consolidation and Edema in Premature Infants in the NICU.

BACKGROUND The incidence of lung diseases in premature newborns is significantly higher than in full-term newborns due to their underdeveloped lungs. Ultrasound and X-ray are commonly-used bedside examinations in neonatology. This study primarily compares the efficacy of chest X-ray (CXR) and lung ultrasound (LUS) images in evaluating lung consolidation and edema in premature newborns at Neonatal Intensive Care Units (NICU). MATERIAL AND METHODS A retrospective analysis was conducted on LUS and CXR examination results, along with clinical records of premature newborns admitted to our hospital's NICU from November 1, 2019, to December 31, 2021. CXR and LUS scans were performed on the same newborn within a day. We evaluated the consolidations and edema by interpreting the CXR and LUS images, then compared the findings. RESULTS Out of 75 cases, 34 showed lung consolidations on LUS (45%), while only 14 exhibited consolidations on CXR (19%). The detection rate of consolidations by LUS was significantly higher compared to CXR (34/75 vs 14/75, P<0.001). Differences were observed between the 2 bedside examinations in identifying consolidations, with some cases seen only on LUS. CXR struggled to accurately assess the severity of lung edema visible on LUS, showing significant disparity in detecting interstitial edema (53/75 vs 21/75, P<0.001). CONCLUSIONS LUS outperforms chest CXR for bedside assessment of lung consolidation and edema in premature newborns.

Diagnostic performance of dual-energy CT in detecting bone marrow edema in lower limb joint injuries: a meta-analysis.

OBJECTIVE: We aimed to evaluate the diagnostic performance of dual-energy computed tomography (DECT) in detecting bone marrow edema (BME) in patients with lower limb joint injuries. METHODS: A thorough literature search was conducted across the PubMed, Embase, and Web of Science databases to identify relevant studies up to April 2024. Studies examining the diagnostic performance of DECT in detecting BME in lower limb joint injuries patients were included. Sensitivity and specificity were evaluated using the inverse variance method and transformed via the Freeman-Tukey double arcsine transformation. Furthermore, the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool was utilized to evaluate the methodological quality of the included studies. RESULTS: This meta-analysis included 17 articles involving 625 patients. The pooled sensitivity, specificity, and AUC for DECT in detecting BME in lower limb joint injuries patients were 0.82 (95 % CI: 0.76-0.87), 0.95 (95 % CI: 0.92-0.97), and 0.95 (95 % CI: 0.93-0.97), respectively. The pooled sensitivity of DECT for detecting BME in knee, hip, and ankle joint injuries was 0.80, 0.84, and 0.80, with no significant difference among these joints (P = 0.55). The pooled specificity for knee, hip, and ankle injuries was 0.95, 0.97, and 0.89. Specificity differed significantly among the joints (P < 0.01), with the highest specificity in hip injuries. CONCLUSIONS: Our meta-analysis indicates that DECT demonstrates high diagnostic performance in detecting BME in patients with lower limb joint injuries, with the highest specificity observed in hip joint injuries. To validate these findings, further larger prospective studies are necessary.

Visualising myocardial injury after noncardiac surgery: a case series using postoperative cardiovascular MRI.

Myocardial injury after noncardiac surgery (MINS) and perioperative myocardial injury are associated with increased morbidity and mortality. Both are diagnosed by a perioperative increase in troponin, yet there is controversy if MINS is a genuine myocardial insult. We applied postoperative cardiovascular magnetic resonance T2 mapping techniques to visualise acute myocardial injury (i.e. oedema) in six patients with multiple cardiovascular risk factors who underwent aortic surgery. The burden of myocardial oedema was substantially higher in four patients with elevated troponin qualifying for MINS, compared with patients without MINS. The data and images suggest that MINS represents genuine myocardial injury.

Peritumoral edema enhances MRI-based deep learning radiomic model for axillary lymph node metastasis burden prediction in breast cancer.

To investigate whether peritumoral edema (PE) could enhance deep learning radiomic (DLR) model in predicting axillary lymph node metastasis (ALNM) burden in breast cancer. Invasive breast cancer patients with preoperative MRI were retrospectively enrolled and categorized into low (< 2 lymph nodes involved (LNs+)) and high (≥ 2 LNs+) burden groups based on surgical pathology. PE was evaluated on T2WI, and intra- and peri-tumoral radiomic features were extracted from MRI-visible tumors in DCE-MRI. Deep learning models were developed for LN burden prediction in the training cohort and validated in an independent cohort. The incremental value of PE was evaluated through receiver operating characteristic (ROC) analysis, confirming the improvement in the area under the curve (AUC) using the Delong test. This was complemented by net reclassification improvement (NRI) and integrated discrimination improvement (IDI) metrics. The deep learning combined model, incorporating PE with selected radiomic features, demonstrated significantly higher AUC values compared to the MRI model and the DLR model in the training cohort (n = 177) (AUC: 0.953 vs. 0.849 and 0.867, p < 0.05) and the validation cohort (n = 111) (AUC: 0.963 vs. 0.883 and 0.882, p < 0.05). The complementary analysis demonstrated that PE significantly enhances the prediction performance of the DLR model (Categorical NRI: 0.551, p < 0.001; IDI = 0.343, p < 0.001). These findings were confirmed in the validation cohort (Categorical NRI: 0.539, p < 0.001; IDI = 0.387, p < 0.001). PE improved preoperative ALNM burden prediction of DLR model, facilitating personalized axillary management in breast cancer patients.

Bone marrow edema detection for diagnostic support of axial spondyloarthritis using MRI.

PURPOSE: This study proposes a process for detecting slices with bone marrow edema (BME), a typical finding of axSpA, using MRI scans as the input. This process does not require manual input of ROIs and provides the results of the judgment of the presence or absence of BME on a slice and the location of edema as the rationale for the judgment. METHODS: First, the signal intensity of the MRI scans of the sacroiliac joint was normalized to reduce the variation in signal values between scans. Next, slices containing synovial joints were extracted using a slice selection network. Finally, the BME slice detection network determines the presence or absence of the BME in each slice and outputs the location of the BME. RESULTS: The proposed method was applied to 86 MRI scans collected from 15 hospitals in Japan. The results showed that the average absolute error of the slice selection process was 1.49 slices for the misalignment between the upper and lower slices of the synovial joint range. The accuracy, sensitivity, and specificity of the BME slice detection network were 0.905, 0.532, and 0.974, respectively. CONCLUSION: This paper proposes a process to detect the slice with BME and its location as the rationale of the judgment from an MRI scan and shows its effectiveness using 86 MRI scans. In the future, we plan to develop a process for detecting other findings such as bone erosion from MR scans, followed by the development of a diagnostic support system.

Reflectance confocal microscopy for the early diagnosis of herpes zoster.

For herpes zoster (HZ) infection, early diagnosis and treatment are important in order to shorten the course of the disease and reduce sequelae, however, there is a lack of non-invasive diagnostic methods. Reflectance confocal microscopy (RCM) is a non-invasive technique often used to diagnose dyspigmented dermatosis, skin tumours, human papillomavirus infectious dermatosis, etc. To evaluate the clinical value of RCM for the early diagnosis of HZ. We collected RCM images from 30 HZ patients with typical vesicles in order to analyse their features. We then utilized RCM to analyse early lesions of another 12 HZ patients, who presented with localized erythema or papules, but not typical vesicles. In addition, we recruited one patient with HZ and observed the lesions over 14 days also using RCM. RCM images showed that the typical lesions of HZ mainly involved oedema of the spinous layer, intraepidermal blister formation, ballooning multinucleated giant (BMG) cells, and dermal papillary oedema. Among them, BMG cells were of specific diagnostic value. Early lesions of HZ patients without typical vesicles showed BMG cells under RCM. A few BMG cells were observed during the early stage of HZ. However, the number of BMG cells increased significantly as typical clustered blisters gradually appeared in the lesions. With the regression of the lesions, the number of BMG cells decreased gradually. RCM, with the advantages of being non-invasive, rapid, and convenient, has an important role in monitoring the evolution of HZ.

Role of oedema and shrinkage patterns for prediction of response to neoadjuvant chemotherapy and survival outcomes in luminal breast cancer.

AIMS: To explore the independent and additional value of oedema and shrinkage patterns for predicting the disease-free survival (DFS) and neoadjuvant chemotherapy (NAC) response in luminal breast cancer (BC). MATERIALS AND METHODS: Patients with luminal BC who underwent NAC were enrolled in this study from 2017 to 2022. Traditional MRI features include BI-RADS-based MRI descriptors, tumor size, and ADC values, while emerging MRI features include oedema and shrinkage patterns, all of which were evaluated before, early, and after NAC. The changes in features during NAC were also evaluated. The value of features was evaluated through univariate, multivariate analyses. RESULTS: A total of 258 patients were enrolled in this study, of which 77 responded to NAC. Diffuse oedema, stable or increased oedema during early NAC were adverse predictors for treatment response, while a greater reduction in tumor size and increase in ADC value were favorable predictors (all P<0.05). Furthermore, 20 of 60 patients who were followed up experienced recurrence. Diffuse oedema, pre-pectoral or subcutaneous oedema, and non-concentric shrinkage patterns after NAC were risk factors for DFS, whereas a greater increase in ADC value was a protective factor. Incorporating oedema and shrinkage patterns into traditional MRI features improved the predictive performance for treatment response (AUC from 0.76-0.78 to 0.80-0.83) and DFS (C-index from 0.67-69 to 0.75-0.80). CONCLUSIONS: Oedema is an unfavorable predictor for treatment response and survival outcomes, while shrinkage patterns contribute more to the prognostic value, both of which could offer supplementary benefits for clinical outcomes in luminal BC.

A near-infrared fluorescent probe for imaging peroxynitrite levels in paw edema mice and drug evaluation.

A near-infrared fluorescent probe (TX-P) for detecting peroxynitrite is constructed. The probe has a near-infrared emission (725 nm), large Stokes shift (125 nm) and excellent sensitivity and selectivity. In addition, TX-P can be used to visualize ONOO- in living cells, image ONOO- in paw edema mice and evaluate anti-inflammatory drugs.

W-DRAG: A joint framework of WGAN with data random augmentation optimized for generative networks for bone marrow edema detection in dual energy CT.

Dual-energy computed tomography (CT) is an excellent substitute for identifying bone marrow edema in magnetic resonance imaging. However, it is rarely used in practice owing to its low contrast. To overcome this problem, we constructed a framework based on deep learning techniques to screen for diseases using axial bone images and to identify the local positions of bone lesions. To address the limited availability of labeled samples, we developed a new generative adversarial network (GAN) that extends expressions beyond conventional augmentation (CA) methods based on geometric transformations. We theoretically and experimentally determined that combining the concepts of data augmentation optimized for GAN training (DAG) and Wasserstein GAN yields a considerably stable generation of synthetic images and effectively aligns their distribution with that of real images, thereby achieving a high degree of similarity. The classification model was trained using real and synthetic samples. Consequently, the GAN technique used in the diagnostic test had an improved F1 score of approximately 7.8% compared with CA. The final F1 score was 80.24%, and the recall and precision were 84.3% and 88.7%, respectively. The results obtained using the augmented samples outperformed those obtained using pure real samples without augmentation. In addition, we adopted explainable AI techniques that leverage a class activation map (CAM) and principal component analysis to facilitate visual analysis of the network's results. The framework was designed to suggest an attention map and scattering plot to visually explain the disease predictions of the network.

Undiagnosed Intra-articular Synovial Hemangioma: A Rare Cause of Knee Pain and Swelling.

INTRODUCTION: Synovial hemangioma is a benign soft-tissue tumor of vascular origin. Hemangioma only accounts for 1% of all bone lesions and is mostly an incidental finding among the primary skeleton tumors. A delay in diagnosis results in joint degeneration and osteoarthritic damage because of infiltrating tumor growth. CASE PRESENTATION: We presented a rare case of an intra-articular synovial hemangioma in a 13- year-old pediatric patient who was asymptomatic for 5 years. She attended orthopedics OPD at AIIMS, Mangalagiri. Surgical excision of the mass and partial synovectomy was done. Synovial hemangioma came out to be the diagnosis following a histologic study. CONCLUSION: As radiography has limited diagnostic ability, synovial hemangiomas are difficult and challenging to identify on an outpatient basis. Histological examination and magnetic resonance imaging are extremely helpful. To minimize the hemarthrosis risks, early complete excision can be used as the best treatment modality.

Maxillary sinus opacification after surgery in asymptomatic patients: Transient swelling of the sinus mucosa or graft dispersion into the maxillary sinus. A radiographic report of three cases after a follow-up period of at least 5 years.

Maxillary sinus grafting is a predictable regenerative technique to facilitate maxillary posterior implant placement when there is insufficient vertical bone height inferior to the maxillary sinuses to allow placement of implants of adequate dimensions. It enables an increase in vertical bone height, which makes implant placement easier. Maxillary sinus mucosal membrane perforation is one of the most common intraoperative complications during maxillary sinus grafting and may result in extrusion of graft material into the sinus. When this occurs, the mucociliary function of the maxillary sinus may expel the extruded graft material through its natural ostium, though graft particles may remain in the sinus or possibly occlude the natural ostium. After grafting, transient maxillary sinus mucosal oedema may occur. A postoperative CBCT scan may reveal varying degrees of sinus opacification, namely partial, subtotal or total. Although it is always possible to identify graft material, which may enter the sinus as a result of membrane perforation that might not even be visible to the implantologist during the surgical procedure, it is challenging to assess whether sinus opacification is due to mucosal thickening or mucus accumulation. The aim of the present case series was to offer a pragmatic approach to managing asymptomatic patients whose CBCT scans demonstrated partial, subtotal or total maxillary sinus opacification with bone graft particles that seemed to have been extruded into the sinus.

Diagnostic performance of unenhanced electrocardiogram-gated cardiac CT for detecting myocardial edema.

To assess the diagnostic performance of unenhanced electrocardiogram (ECG)-gated cardiac computed tomography (CT) for detecting myocardial edema, using MRI T2 mapping as the reference standard. This retrospective study protocol was approved by our institutional review board, which waived the requirement for written informed consent. Between December 2017 to February 2019, consecutive patients who had undergone T2 mapping for myocardial tissue characterization were identified. We excluded patients who did not undergo unenhanced ECG-gated cardiac CT within 3 months from MRI T2 mapping or who had poor CT image quality. All patients underwent unenhanced ECG-gated cardiac CT with an axial scan using a third-generation, 320 × 0.5 mm detector-row CT unit. Two radiologists together drew regions of interest (ROIs) in the interventricular septum on the unenhanced ECG-gated cardiac CT images. Using T2 mapping as the reference standard, the diagnostic performance of unenhanced cardiac CT for detecting myocardial edema was evaluated by using the area under the receiver operating characteristic curve with sensitivity and specificity. Youden index was used to find an optimal sensitivity-specificity cutoff point. A cardiovascular radiologist independently performed the measurements, and interobserver reliability was assessed using intraclass correlation coefficients for CT value measurements. A P value of <.05 was considered statistically significant. We included 257 patients who had undergone MRI T2 mapping. Of the 257 patients, 35 patients underwent unenhanced ECG-gated cardiac CT. One patient was excluded from the study because of poor CT image quality. Finally, 34 patients (23 men; age 64.7 ±â€…14.6 years) comprised our study group. Using T2 mapping, we identified myocardial edema in 19 patients. Mean CT and T2 values for 34 patients were 46.3 ±â€…2.7 Hounsfield unit and 49.0 ±â€…4.9 ms, respectively. Mean CT values moderately correlated with mean T2 values (Rho = -0.41; P < .05). Mean CT values provided a sensitivity of 63.2% and a specificity of 93.3% for detecting myocardial edema, with a cutoff value of ≤45.0 Hounsfield unit (area under the receiver operating characteristic curve = 0.77; P < .01). Inter-observer reproducibility in measuring mean CT values was excellent (intraclass correlation coefficient = 0.93; [95% confidence interval: 0.86, 0.96]). Myocardial edema could be detected by CT value of myocardium in unenhanced ECG-gated cardiac CT.

Orbital Mass Identified With Point-of-Care Ultrasound in a Child Presenting With Eyelid Swelling.

ABSTRACT: Point-of-care ultrasound was used in a child presenting to the emergency department with progressively worsening left eyelid swelling. The early use of ultrasound was helpful in detecting a soft tissue mass that is exhibiting pressure effect on the eyeball. Point-of-care ultrasound helped expedite advanced imaging and consultation with the specialist. The patient eventually had a biopsy and was diagnosed with idiopathic orbital inflammation.

Classification of breast edema on T2-weighted imaging for predicting sentinel lymph node metastasis and biological behavior in breast cancer.

OBJECTIVE: To determine whether preoperative classification of breast edema on T2-weighted imaging (T2WI) is useful for predicting sentinel lymph node (SLN) metastasis and biological behavior in patients with early-stage breast cancer. METHODS: This retrospective study involved 341 women with breast cancer who underwent breast MRI from January 2019 to March 2022. Breast edema was scored on a scale of 1-4 on T2WI (1, no edema; 2, peritumoral edema; 3, prepectoral edema; and 4, subcutaneous edema). A logistic regression model was employed for univariate and multivariate analyses. A clinicopathological model was established using independent influencing factors identified in the multivariate analyses, excluding breast edema score (BES). Subsequently, BES was incorporated into this model to establish a combined BES model. The AUC and Delong test were used to examine the additional predictive value of the BES. RESULTS: Logistic regression analysis showed that breast edema was an independent risk factor for SLN metastasis. The combined BES model significantly improved the predictive performance of SLN metastasis compared with the clinicopathological model alone (AUC, 0.77 vs. 0.71; p=0.005). In addition, the BES was significantly positively correlated with the tumor diameter (p<0.001), histologic grade (p=0.001), Ki-67 index (p<0.001), and non-luminal subtypes (p<0.001). CONCLUSION: The BES on T2WI is useful for predicting SLN metastasis. A higher grade of breast edema is associated with breast cancer aggressiveness and increases the probability of SLN metastasis.

Detection and quantitation of venous leg edema with the edema ruler and ultrasound.

Objective: Lower extremity edema is characteristic of C3 chronic venous disease. We developed a new clinical and duplex ultrasound (DUS) methodology for the detection and quantification of leg edema and prospectively evaluated its usefulness. Methods: Forty-seven venous patients (94 legs) were evaluated for ankle edema using an Edema RulerTM and DUS using a modified Suehiro grading scale. Results: Interobserver reliability for the use of the Edema RulerTM was 0.985 (p < .001) and 0.883 (p < .001) for the Modified Suehiro Grade. The Edema RulerTM had stronger significant correlations with Edema rVCSS (0.842; p < .001) compared to DUS: (0.474;p < .001) with Edema rVCSS. There were significant differences between the edema pitting depth in CEAP classification of C1 and C2 compared to C3, C4a, and C4c. DUS analysis only had significant differences between CEAP classification C2 and C4a. Conclusions: The Edema RulerTM provides a quantitative measurement of lower extremity edema with high reliability which can be easily integrated into clinical practice. While both methods had good inter-observer reliability, the Edema RulerTM had stronger correlations to Edema rVCSS and showed significant differences in pitting depths between lower CEAP scores (C1-2) compared to higher CEAP scores (C3-4c).

Probability of Occult Ankle Fracture Based on Radiograph-Measured Swelling.

INTRODUCTION: Pediatric ankle injuries are a common presentation in the emergency department (ED). A quarter of pediatric ankle fractures show no radiographic evidence of a fracture. Physicians often correlate non-weight bearing and tenderness with an occult fracture. We present this study to predict the probability of an occult fracture using radiographic soft-tissue swelling on initial ED radiographs. METHODS: This is a retrospective study at a Level 1 pediatric trauma center from 2021 to 22. Soft-tissue swelling between the lateral malleolus and skin was measured on radiographs, and weight-bearing status was documented. Statistical analysis was conducted using Stata software. DISCUSSION: The study period involved 32 patients with an occult fracture, with 8 (25%) diagnosed with a fracture on follow-up radiographs. The probability of an occult fracture was calculated as a function of the ankle swelling in millimeters (mm) using a computer-generated predictive model. False-negative and false-positive rates were plotted as a function of the degree of ankle swelling. CONCLUSION: Magnitude of ankle soft-tissue swelling as measured on initial ED radiographs is predictive of an occult fracture. Although weight-bearing status was not a sign of occult fracture, it improves the predictive accuracy of soft-tissue swelling.

Value of radiomics-based automatic grading of muscle edema in polymyositis/dermatomyositis based on MRI fat-suppressed T2-weighted images.

BACKGROUND: The precise and objective assessment of thigh muscle edema is pivotal in diagnosing and monitoring the treatment of dermatomyositis (DM) and polymyositis (PM). PURPOSE: Radiomic features are extracted from fat-suppressed (FS) T2-weighted (T2W) magnetic resonance imaging (MRI) of thigh muscles to enable automatic grading of muscle edema in cases of polymyositis and dermatomyositis. MATERIAL AND METHODS: A total of 241 MR images were analyzed and classified into five levels using the Stramare criteria. The correlation between muscle edema grading and T2-mapping values was assessed using Spearman's correlation. The dataset was divided into a 7:3 ratio of training (168 samples) and testing (73 samples). Thigh muscle boundaries in FS T2W images were manually delineated with 3D-Slicer. Radiomics features were extracted using Python 3.7, applying Z-score normalization, Pearson correlation analysis, and recursive feature elimination for reduction. A Naive Bayes classifier was trained, and diagnostic performance was evaluated using receiver operating characteristic (ROC) curves and comparing sensitivity and specificity with senior doctors. RESULTS: A total of 1198 radiomics parameters were extracted and reduced to 18 features for Naive Bayes modeling. In the testing set, the model achieved an area under the ROC curve of 0.97, sensitivity of 0.85, specificity of 0.98, and accuracy of 0.91. The Naive Bayes classifier demonstrated grading performance comparable to senior doctors. A significant correlation (r = 0.82, P <0.05) was observed between Stramare edema grading and T2-mapping values. CONCLUSION: The Naive Bayes model, utilizing radiomics features extracted from thigh FS T2W images, accurately assesses the severity of muscle edema in cases of PM/DM.

Intratumoral and Peritumoral Edema Radiomics Based on Fat-Suppressed T2- Weighted Imaging for Preoperative Prediction of Triple-Negative Breast Cancer.

AIM: Our aim was to explore the feasibility of using radiomics data derived from intratumoral and peritumoral edema on fat-suppressed T2-weighted imaging (T2 FS) to distinguish triple-negative breast cancer (TNBC) from non-triple-negative breast cancer (non-TNBC). METHODS: This retrospective study enrolled 174 breast cancer patients. According to the MRI examination time, patients before 2021 were divided into training (n = 119) or internal test (n = 30) cohorts at a ratio of 8:2. Patients from 2022 were included in the external test cohort (n = 25). Four regions of interest for each lesion were defined: intratumoral regions, peritumoral edema regions, regions with a combination of intratumoral and peritumoral edema, and regions with a combination of intratumoral and 5-mm peritumoral. Four radiomic signatures were built using the least absolute shrinkage and selection operator (LASSO) method after selecting features. Furthermore, a radio mic-radiological model was constructed using a combination of intratumoral and peritumoral edema regions along with clinical-radiologic features. Area under the receiver operating characteristic curve (AUC) calculations, decision curve analysis, and calibration curve analysis were performed to assess the performance of each model. RESULTS: The radiomic-radiological model showed the highest AUC values of 0.906 (0.788-1.000) and 82.5 (0.622-0.947) in both the internal and external test sets, respectively. The radiology-radiomic model exhibited excellent predictive performance, as evidenced by the calibration curves and decision curve analysis. CONCLUSION: The ensemble model based on T2 FS-based radiomic features of intratumoral and peritumoral edema, along with radiological factors, performed better in distinguishing TNBC from non-TNBC than a single model. We explored the possibility of developing explainable models to support the clinical decision-making process.