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 To evaluate the incremental diagnostic value of combining free prostate-specific antigen density (FPSAD) with Prostate Imaging Reporting and Data System version 2.1 (PI-RADS v2.1) for clinically significant prostate cancer (csPCa,defined as Gleason score≥3+4) in the diagnostic gray zone (tPSA 4-10 ng/mL). This retrospective study analyzed 137 patients (75 with csPCa and 62 with non-clinically significant prostate cancer (ncsPCa) who underwent transperineal prostate biopsy at Xiangtan Central Hospital between January 2022 and January 2024. PI-RADS v2.1 scores were assigned based on magnetic resonance (MR) imaging, and prostate volume (PV) and FPSAD were calculated. Statistical analyses included chi-square/Fisher's exact tests for categorical variables and independent -tests for continuous variables. Logistic regression identified independent predictors of csPCa, and a nomogram model was developed. Model performance was evaluated using calibration curves and receiver operating characteristic (ROC) analysis.  Significant differences were observed in FPSAD, PI-RADS v2.1 scores, and free PSA (fPSA) between the csPCa and ncsPCa groups ( < 0.01). FPSAD (OR = 1.95, 95% CI: 1.22-2.22, < 0.01) and PI-RADS v2.1 scores (OR = 2.41, 95% CI: 1.57-3.70, < 0.01) were independent predictors of csPCa. The combined FPSAD and PI-RADS v2.1 model demonstrated superior diagnostic performance (AUC =0.829) compared to FPSAD alone (AUC = 0.69) or PI-RADS v2.1 alone (AUC = 0.773) ( < 0.01), with 91% sensitivity and 32% fewer unnecessary biopsies than PI-RADS≥3 criteria. In PI-RADS 3 subgroup (n=41), FPSAD correctly reclassified 13/18 (72.2%) indeterminate cases.  For Asian men with tPSA 4-10 ng/mL, the FPSAD+PI-RADS algorithm (cutoffs: >0.017 and ≥4) provides 15-20% higher accuracy than either marker alone, while reducing biopsies by 25%. This approach is particularly valuable for PI-RADS 3 cases, where it resolved >65% of diagnostic uncertainties in our cohort.

The role of chest computed tomography (CT) in distinguishing the causative pathogens of pulmonary infections in patients with hematological malignancies (HM) is unclear. The aim of our study was to compare and assess the clinical characteristics, radiologic features and potential differential diagnostic value of CT in HM patients and other different immune statuses patients with pulmonary infections. Patients were divided into immunocompetent (105 cases) and immunocompromised groups (99 cases) according to immune status. Immunocompromised patients included the HM group (63 cases) and the non-HM group (42 cases). The basic clinical data and CT findings were collected and statistically analyzed. Regarding the pathogen distribution, viral, and mixed infections were more common in the immunocompromised group than the immunocompetent (p < 0.01), but viral infections were more common in the HM group than in the non-HM group (p=0.013). Immunocompromised patients had more diverse CT findings and more serious lesions (mostly graded 2-4) than immunocompetent patients. The most common CT findings in HM patients were consolidation and ground-glass opacities (GGO), which were also found in the non-HM group. The overall diagnostic accuracy of CT was lower in immunocompromised patients than in immunocompetent patients (25.7% vs 50.5%, p< 0.01). CT had better diagnostic efficacy for fungi and in HM patients. CT diagnosis is less efficient in distinguishing the causative pathogens of HM patients. However, CT can help distinguish fungal pneumonia and pneumonia in HM patients. Our study might facilitate clinical decision-making in fungal pneumonia and pneumonia in HM patients.

Systemic volume changes during acute lung injury (ALI) are closely related to lung injury severity, disease progression, and treatment methods. Twenty-one goats were divided into control, mild injury, and severe injury groups via oleic acid injection. Carotid ultrasound measured carotid diameter and corrected flow time (FTc), while cardiac ultrasound assessed aortic and pulmonary artery velocity–time integral (VTI). Post-euthanasia at 6 h, lung wet-to-dry (W/D) ratio and pathological scores were analyzed. Statistical trends, correlations between ultrasound parameters and lung injury markers, and diagnostic performance via ROC analysis were evaluated. The severe injury group had significantly higher lung W/D ratios and pathological scores than the mild injury group. Carotid ultrasound showed a progressive decrease in carotid diameter and FTc post-injury, with FTc significantly lower in the severe injury group at 6-h. FTc was negatively correlated with lung W/D ratio and pathological scores. Cardiac ultrasound indicated a decreasing trend in aortic and pulmonary artery VTI post-injury, with pulmonary artery VTI significantly lower in the severe injury group at all times and negatively correlated with lung W/D ratio and pathological scores. ROC analysis showed that pulmonary artery VTI had the highest area under the curve (AUC), with values greater than 0.8 at all time points. The combined use of pulmonary artery VTI and carotid FTc had AUC values greater than 0.85 at all time points, peaking at 6-h (AUC = 0.951). In conclusion, pulmonary artery VTI is an excellent indicator for evaluating ALI severity post-injury, and the combination of pulmonary artery VTI and carotid FTc shows strong diagnostic performance for assessing ALI severity.

Lower respiratory tract infections are associated with high morbidity and mortality and significant clinical harm. Due to the limited ability of traditional pathogen detection methods, anti-infective therapy is mostly empirical. Therefore, it is difficult to adopt targeted drug therapy. In recent years, metagenomic next-generation sequencing (mNGS) technology has provided a promising means for pathogen-specific diagnosis and updated the diagnostic strategy for lower respiratory tract infections. This article reviews the diagnostic value of mNGS for lower respiratory tract infections, the impact of different sampling methods on the detection efficiency of mNGS, and current technical difficulties in the clinical application of mNGS.

Sonography is a beneficial imaging modality for detecting elbow fractures in children, considering the lack of radiation exposure and time efficiency. This systematic review aims to determine the diagnostic value and clinical applicability of sonography and each sonographic finding in detecting pediatric elbow fractures. Pubmed, Scopus, and WOS databases were searched for related original articles until February 25, 2023, and data related to diagnostic performance were extracted. We used the Bivariate model and hierarchic summary receiver operating characteristic (HSROC) approach to calculate pooled diagnostic values. Cochrane Q test and I-squared were performed to evaluate heterogeneity. We assessed heterogeneity with meta-regression. Eight studies were included, which involved a total number of 880 patients. According to meta-analysis, sonography demonstrated a pooled sensitivity of 97% (91–99%) and specificity of 90% (80–95%), positive likelihood ratio(LR+) of 9.82 (4.59–20.97), and negative likelihood ratio (LR–) of 0.03 (0.01–0.10). For the sonographic posterior fat pad sign as a sole diagnostic sign, we calculated a Pooled Sensitivity of 80% (70–88%), Specificity of 97% (87–99%), LR+ of 28.8 (6–139.3), and LR– of 0.2 (0.13–0.31). Also, lipohemarthrosis demonstrated a pooled sensitivity of 80% (70–88%), specificity of 97% (87–99%), LR+ of 28.8 (6–139.3), and LR– of 0.2 (0.13–0.31). The sensitivity of detecting fractures with cortical line disruption was significantly higher in studies that utilized a comprehensive technique compared to a conventional technique. Sonography is a valuable diagnostic tool for the assessment of pediatric elbow injuries, and it can be capable of confirmation or exclusion of the diagnosis.

Background Invasive pulmonary fungal infections (IPFIs) pose significant diagnostic challenges, particularly in immunocompromised patients. Accurate and timely diagnosis is crucial to improve outcomes. While metagenomic next-generation sequencing (mNGS) is widely utilized, it is expensive and affected by host DNA interference. Targeted next-generation sequencing (tNGS) offers a cost-effective and efficient alternative for fungal pathogen detection. Methods We developed the Fi-tNGS assay, a targeted next-generation sequencing method, specifically designed to detect 64 fungal species. Analytical performance was validated by assessing its limit of detection (LoD), reproducibility, and resistance to host DNA interference. Subsequently, a prospective clinical study was conducted, enrolling 104 patients with suspected IPFIs. Clinical diagnostic performance was evaluated by comparing Fi-tNGS, mNGS, and conventional microbial culture against a comprehensive diagnostic standard. Results Fi-tNGS detected 109 pathogens, compared to 110 for mNGS and 77 for culture. The sensitivity and specificity of tNGS were 89.7% and 94.2%, respectively, outperforming culture (65.8% sensitivity, 100% specificity). Combining culture with tNGS or mNGS significantly improved sensitivity to 94.8% and 94.0%, respectively. These findings demonstrate the added diagnostic value of NGS methods for IPFIs. Conclusions tNGS provides accurate and efficient fungal pathogen detection, with sensitivity comparable to mNGS and superior to culture. Its cost-effectiveness and shorter turnaround time highlight its potential as a practical tool for the rapid and precise diagnosis of IPFIs in clinical settings.

PurposeTo compare the incremental diagnostic value of amyloid-PET and CSF (Aβ42, tau, and phospho-tau) in AD diagnosis in patients with mild cognitive impairment (MCI) or mild dementia, in order to improve the definition of diagnostic algorithm.MethodsTwo independent dementia experts provided etiological diagnosis and relative diagnostic confidence in 71 patients on 3 rounds, based on (1) clinical, neuropsychological, and structural MRI information alone; (2) adding one biomarker (CSF amyloid and tau levels or amyloid-PET with a balanced randomized design); and (3) adding the other biomarker.ResultsAmong patients with a pre-biomarker diagnosis of AD, negative PET induced significantly more diagnostic changes than amyloid-negative CSF at both rounds 2 (CSF 67%, PET 100%, P = 0.028) and 3 (CSF 0%; PET 78%, P < 0.001); PET induced a diagnostic confidence increase significantly higher than CSF on both rounds 2 and 3.ConclusionsAmyloid-PET should be prioritized over CSF biomarkers in the diagnostic workup of patients investigated for suspected AD, as it provides greater changes in diagnosis and diagnostic confidence.Trial registrationEudraCT no.: 2014-005389-31

ABSTRACT Background The “insular knife‐cut” sign is a sharp demarcation between hyperintense insular lesions on fluid‐attenuated inversion recovery axial images and the basal ganglia, detected on brain MRI. This sign has been associated with herpes simplex virus encephalitis (HSVE); however, its specificity remains unknown. We assessed the frequency and specificity of the insular knife‐cut sign in a real‐life cohort of patients with suspected HSVE. Methods We retrospectively identified patients admitted for suspected HSVE over the past 10 years at three Neurology Units in Italy. Inclusion criteria were cerebrospinal fluid (CSF) tested for HSV‐1/2 PCR and acute brain MRI available. Results A total of 188 patients were included: HSVE, 44; alternative diagnoses, 144 (autoimmune encephalitis, 51; infectious encephalitis, 22; other acute encephalopathies, 71). The insular knife‐cut sign was present on the initial brain MRI in 23/44 (52.3%) HSVE patients and 1/144 (0.7%) patients with alternative diagnoses (p < 0.001). The specificity and sensitivity of the sign were 99.3% (95% CI, 96–100) and 52% (95% CI, 38–66), respectively. In eight HSVE patients, the insular knife‐cut sign appeared on subsequent MRIs obtained acutely, raising the sensitivity to 70.5% (95% CI, 56–82). On multivariate regression, the insular knife‐cut sign was the strongest independent predictor (odds ratio [95% CI]) of HSVE (68.9 [11.42–415.54]), followed by temporal pole involvement (8.44 [2.06–34.6]), and CSF pleocytosis (6 [1.7–21.18]). Conclusions In patients with suspected encephalitis, the insular knife‐cut sign on MRI strongly predicts a diagnosis of HSVE. Its detection should prompt consideration of HSVE, even when other diagnostic tests are equivocal/unavailable.

Objective To clarify the efficacy of artificial intelligence (AI)-assisted imaging in the diagnosis of developmental dysplasia of the hip (DDH) through a meta-analysis. Methods Relevant literature on AI for early DDH diagnosis was searched in PubMed, Web of Science, Embase, and The Cochrane Library databases until April 4, 2024. The Quality Assessment of Diagnostic Accuracy Studies tool was used to assess the quality of included studies. Revman5.4 and StataSE-64 software were used to calculate the combined sensitivity, specificity, AUC value, and DOC value of AI-assisted imaging for DDH diagnosis. Results The meta-analysis included 13 studies (6 prospective and 7 retrospective) with 28 AI models and a total of 10,673 samples. The summary sensitivity, specificity, AUC value, and DOC value were 99.0% (95% CI: 97.0-100.0%), 94.0% (95% CI: 89.0–96.0%), 99.0% (95% CI: 98.0-100.0%), and 1342 (95% CI: 469–3842), respectively. Conclusion AI-assisted imaging demonstrates high diagnostic efficacy for DDH detection, improving the accuracy of early DDH imaging examination. More prospective studies are needed to further confirm the value of AI-assisted imaging for early DDH diagnosis.

To evaluate the diagnostic value of magnetic resonance imaging (MRI) radiomics in distinguishing high-grade meningiomas (HGM) from low-grade meningiomas (LGM). A systematic search was conducted in PubMed, EMbase, Web of Science, and The Cochrane Library databases up to December 31, 2023. Two researchers independently screened studies, extracted data, and assessed risk of bias and quality of included studies as well. Meta-analysis was performed using Stata 14 software to calculate pooled sensitivity (SEN), specificity (SPE), positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the curve (AUC). A total of 21 studies with 2253 patients were included (607 HGM, 1646 LGM). Meta-analysis showed an overall SEN of 0.82 (95% CI 0.74–0.88) and SPE of 0.85 (95% CI 0.81–0.89). The PLR and NLR were 5.64 (95% CI 4.17–7.64) and 0.21 (95% CI 0.14–0.31), respectively, with a pooled DOR of 26.66 (95% CI 14.42–49.27) and an AUC of 0.91 (95% CI 0.88–0.93), indicating high diagnostic accuracy. Although additional research is required to validate suitable techniques, MRI radiomics shows strong potential as an accurate tool for meningioma grading. Standardizing radiomics application could enhance diagnostic precision and clinical decision-making for meningioma grading in the future. Trial Registration : CRD42024500086.