Diagnostic and interventional radiology最新文献

Purpose: To evaluate magnetic resonance imaging (MRI)-targeted biopsy (MRI-TB) performance in detecting clinically significant prostate cancer (csPCa) with a Prostate Imaging Reporting and Data System (PI-RADS) score of ≥3 peripheral zone (PZ) lesions using multiparametric MRI (mpMRI)-histopathology correlation.

Methods: This retrospective study included 141 patients with 187 PZ lesions who underwent mpMRI followed by both MRI-TB and transrectal ultrasound-guided systematic biopsy (SB) between December 2021 and December 2024. All mpMRI scans were evaluated by a board-certified experienced radiologist in accordance with the PI-RADS version 2.1 criteria. The csPCa detection rates of SB, MRI-TB, and combined biopsy (CB) were compared. Statistical analyses included McNemar's test, Fisher's exact test, and the Mann-Whitney U test. A P value <0.05 was considered statistically significant.

Results: Among the 141 patients (187 PI-RADS ≥3 PZ lesions), patients with csPCa exhibited significantly higher prostate-specific antigen (PSA) levels (15.3 vs. 8.2 ng/mL; P = 0.02), lower prostate volume (52.4 vs. 78.6 mL; P < 0.001), and three-fold higher PSA density (PSAD) (0.30 vs. 0.10 ng/mL/mL; P < 0.001) than non-csPCa cases. Notably, PSAD > 0.15 ng/mL/mL occurred in 78% of patients with csPCa vs. 18% in non-csPCa cases (P < 0.001). Moreover, MRI-TB detected significantly more csPCa than SB (17.7% vs. 10.7% of lesions; P < 0.001), with maximal advantage in PI-RADS 4 lesions (20.7% vs. 10.9%; P = 0.004). By contrast, CB did not significantly increase csPCa detection over MRI-TB alone (19.8% vs. 17.7%; P = 0.125). Chronic prostatitis (CP) (34.0% of benign cases) confounded PI-RADS specificity.

Conclusion: For csPCa detection in PI-RADS ≥3 PZ lesions, particularly PI-RADS 4, MRI-TB outperforms SB. For PI-RADS 5, SB and MRI-TB showed equivalent efficacy. However, MRI-TB alone suffices for PI-RADS ≥4 lesions or PSAD >0.15 ng/mL/mL, whereas CB remains preferable for PI-RADS 3. The high CP prevalence underscores the need for adjunctive biomarkers to improve specificity.

Clinical significance: MRI-TB optimizes csPCa detection for PI-RADS ≥4 PZ lesions, reducing reliance on SBs. A PSAD threshold >0.15 ng/mL/mL effectively stratifies biopsy necessity, and high CP prevalence (34% of benign cases) underscores the need for adjunct biomarkers to improve specificity in PI-RADS 3-4 lesions.

Purpose: Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with limited treatment options and poorer overall survival than other subtypes. Neoadjuvant chemotherapy (NACT) is often used to reduce tumor size and improve surgical outcomes. However, predicting patients' response to NACT remains challenging, and non-responding patients risk unnecessary chemotoxicity. This study aimed to develop a deep learning-based artificial intelligence (AI) model using pre-treatment magnetic resonance imaging (MRI) to predict pathological complete response (pCR) in patients with TNBC undergoing NACT.

Methods: This retrospective, double-centered study included 49 lesions from 43 patients with TNBC. Data from MRI, including T2-weighted, T1-weighted, and diffusion-weighted imaging, were segmented and processed to train a residual convolutional neural network model.

Results: The AI model achieved an accuracy of 0.82 and an area under the receiver operating characteristic curve of 0.75 in differentiating pCR from non-pCR cases. The model's performance was validated through intra- and inter-reader agreement metrics, with Dice similarity coefficients ranging from 0.821 to 0.915.

Conclusion: Our results demonstrate that AI models can effectively predict NACT responses in patients with TNBC using only pre-treatment MRI data.

Clinical significance: This proof-of-concept study supports the potential for AI-based tools to aid clinical decision-making and reduce the risks associated with ineffective therapies. Future research with larger datasets and additional imaging modalities is needed to improve model generalizability and clinical applicability.

Purpose: This study aims to present our institutional experience with the use of percutaneous balloon-expandable biodegradable magnesium biliary stents (MBS) in the treatment of benign, refractory anastomotic strictures (AS), where initial percutaneous or endoscopic approaches fail or are ineffective, after liver transplantation (LT).

Methods: In this retrospective single-center study, 13 patients with clinically refractory AS who underwent MBS placement between July 2021 and August 2024 were evaluated. Statistical analyses included Kaplan-Meier survival analysis for patency and Spearman's correlation for recurrence risk. Primary outcomes included stricture recurrence and time to reintervention during follow-up.

Results: The median age of patients was 35 years [interquartile range (IQR): 22-48], and 11 were male (85%). Living donor LT was performed in 12 (92%). The MBS were placed at a median of 8 months post-transplant (IQR: 5-44), with a technical success in all cases (100%). Before MBS placement, patients underwent a median of one endoscopic retrograde cholangiopancreatography (IQR: 0-3) and three percutaneous transhepatic biliary drainage procedures (IQR: 1-8). The median follow-up was 25 months (IQR: 15-33). The MBS patency rates were 93%, 85%, and 67% at 6, 12, and 24 months, respectively. Stricture recurrence occurred at a median of 30 months post-placement (95% confidence interval: 23.6-36.3). A moderate positive correlation was observed between the number of pre-stent interventions and recurrence risk (rho: 0.582, P = 0.023). Post-procedural complications (cholangitis) occurred in 1 patient.

Conclusion: Balloon-expandable biodegradable MBS may provide a safe and effective treatment for refractory AS following LT. Early placement of MBS, particularly after fewer prior interventions, appears to be associated with improved patency and longer stricture-free survival.

Clinical significance: Early use of biodegradable magnesium stents after LT may reduce the need for multiple interventions and improve long-term biliary patency.

Purpose: In this study, we aimed to characterize the role of magnetic resonance imaging (MRI) in making a specific diagnosis of inflammatory hand arthritis (IHA), particularly in early stages or ambiguous cases.

Methods: Patients aged ≥18 years with suspicious IHA in at least one joint were enrolled in this single-center prospective study. Three Tesla MRI (3T-MRI) with a fine-tuned protocol was utilized, whereby differential diagnoses were made by radiologists according to the predominant involvement of synovium or synovioentheseal complex (SEC) and/or specific degenerative findings. Physical examination, laboratory findings, treatment response, and already-established classification criteria were used to reach the final diagnostic groups: psoriatic arthritis (PsA), rheumatoid arthritis (RA), erosive osteoarthritis or calcium pyrophosphate dihydrate deposition disease (EOA/CPPD), and arthritis with distal interphalangeal joint (DIPJ) involvement (ADIPI) not otherwise classified into any group. Statistical analyses mainly included pairwise comparisons of MRI findings across diagnostic groups.

Results: Of 80 patients enrolled, 57 [42 women; mean age, 54 years (range, 28-79 years)] constituted the final group with eventual clinical diagnoses of 11 PsA, 14 RA, 11 EOA/CPPD, and 21 ADIPI. MRI revealed no difference between the PsA and ADIPI groups, except for nailbed enthesitis (P = 0.048, effect size: 0.416). A comparison between PsA and RA revealed that enthesitis, excluding pulley enthesitis, was more frequently observed in PsA (P = 0.033, effect size: 0.497). Periarticular soft tissue edema was also more common in PsA than RA (P = 0.042, effect size: 0.461). When the ADIPI and PsA groups were combined, enthesitis and periarticular soft tissue edema were more common than in other groups (P < 0.001).

Conclusion: SEC inflammation and periarticular edema on MRI strongly predict PsA, especially in patients with DIPJ arthritis who do not meet rheumatological classification criteria.

Clinical significance: 3T-MRI with a fine-tuned protocol enables a more accurate differential diagnosis of hand inflammatory arthritis, potentially guiding earlier and more targeted interventions.

Purpose: Small cell lung cancer (SCLC) is an aggressive disease with diverse phenotypes that reflect the heterogeneous expression of tumor-related genes. Recent studies have shown that neuroendocrine (NE) transcription factors may be used to classify SCLC tumors with distinct therapeutic responses. The liver is a common site of metastatic disease in SCLC and can drive a poor prognosis. Here, we present a computational approach to detect and characterize metastatic SCLC (mSCLC) liver lesions and their associated NE-related phenotype as a method to improve patient management.

Methods: This study utilized computed tomography scans of patients with hepatic lesions from two data sources for segmentation and classification of liver disease: (1) a public dataset from patients of various cancer types (segmentation; n = 131) and (2) an institutional cohort of patients with SCLC (segmentation and classification; n = 86). We developed deep learning segmentation algorithms and compared their performance for automatically detecting liver lesions, evaluating the results with and without the inclusion of the SCLC cohort. Following segmentation in the SCLC cohort, radiomic features were extracted from the detected lesions, and least absolute shrinkage and selection operator regression was utilized to select features from a training cohort (80/20 split). Subsequently, we trained radiomics-based machine learning classifiers to stratify patients based on their NE tumor profile, defined as expression levels of a preselected gene set derived from bulk RNA sequencing or circulating free DNA chromatin immunoprecipitation sequencing.

Results: Our liver lesion detection tool achieved lesion-based sensitivities of 66%-83% for the two datasets. In patients with mSCLC, the radiomics-based NE phenotype classifier distinguished patients as positive or negative for harboring NE-like liver metastasis phenotype with an area under the receiver operating characteristic curve of 0.73 and an F1 score of 0.88 in the testing cohort.

Conclusion: We demonstrate the potential of utilizing artificial intelligence (AI)-based platforms as clinical decision support systems, which could help clinicians determine treatment options for patients with SCLC based on their associated molecular tumor profile.

Clinical significance: Targeted therapy requires accurate molecular characterization of disease, which imaging and AI may aid in determining.

Purpose: Orbital lymphomas share overlapping clinical and radiological features with immunoglobulin G4-related orbital disease (IgG4-ROD) and granulomatous orbital diseases, which may lead to diagnostic delays. This study aims to evaluate the added diagnostic value of the transverse relaxation time (T2) signal ratio when combined with apparent diffusion coefficient (ADC) measurements in distinguishing orbital lymphoma from inflammatory mimickers.

Methods: In this retrospective study, two blinded radiologists independently measured T2 signal ratios (lesion to cerebral cortex), ADC values, and ADC ratios on pretreatment orbital magnetic resonance imaging scans of 58 patients (21 lymphomas, 21 IgG4-ROD, 16 granulomatous inflammation). Measurements were performed on axial images at the lesion's maximal diameter. Regions of interest were manually drawn to cover the entire lesion, avoiding necrosis and edges. Diagnostic performance was assessed using receiver operating characteristic curve analysis, with optimal cut-off values determined by Youden's index. The ADC ratio (≤1) and T2 signal ratio (>0.88) were combined using OR (either positive) and AND (both positive) rules. Interobserver agreement was evaluated using intraclass correlation coefficients (ICC).

Results: All measurements showed statistically significant differences between the two cohorts. Reviewer 1's ADC ratio measurements demonstrated excellent diagnostic performance, with an area under the curve (AUC) of 0.920 (85.7% sensitivity and 86.5% specificity at the optimal cut-off of ≤1). In comparison, T2 signal ratios showed moderate diagnostic value (AUC: 0.726; 80.95% sensitivity and 64.86% specificity at a cut-off >0.88). The combination of both parameters significantly improved diagnostic accuracy: the OR rule (ADC ≤1 or T2 >0.88) increased sensitivity to 95.2%, whereas the AND rule (ADC ≤1 and T2 >0.88) increased specificity to 94.6%. Interobserver reliability was excellent, with ICC values ranging from 0.969 to 0.985.

Conclusion: Although diffusion imaging remains the primary discriminator for orbital lymphoma, the T2 signal ratio considerably enhances diagnostic confidence, particularly in borderline ADC cases.

Clinical significance: Incorporating T2 signal ratio measurements adds minimal workflow burden in routine clinical practice and provides a practical tool for differentiating lymphoma from IgG4-ROD and granulomatous inflammatory mimics.

Purpose: This study aimed to compare the effect of establishing an inferior vena cava filter (IVCF) retrieval program (IVCFRP) on the IVCF retrieval rates in trauma and non-trauma patients.

Methods: This was an institutional review board-approved retrospective study. IVCF retrieval in trauma and non-trauma patients was compared before and after the establishment of an IVCFRP in a single Level I Trauma Center. The IVCFRP at our institution was established in April 2020. All patients who underwent IVCF placement between January 2016 and March 2020 were compared with patients who had an IVCF placed between April 2020 and June 2024. A medical record review included the collection of demographic information, indication for IVCF insertion and retrieval, date of IVCF insertion and retrieval, IVCF retrieval rate, clinical outcomes, and complications. The patients were stratified into trauma and non-trauma groups. Univariate analyses were performed with a P value of <0.05 considered statistically significant.

Results: A total of 164 patients underwent IVCF placement between January 2016 and June 2024. Fifty-two IVCFs were implanted before and 112 after the establishment of the IVCFRP. The overall rate of IVCF retrieval was significantly higher following the establishment of an IVCFRP (33.3% vs. 51%, P = 0.047). In non-trauma patients, the retrieval rate was significantly higher after the establishment of an IVCFRP (37.5% vs. 61.3%, P = 0.03). The retrieval rate in trauma patients (22.2% vs. 21.4%) was not significantly changed by the establishment of an IVCFRP. Clinical outcomes and complications were similar between groups.

Conclusion: IVCF retrieval rates significantly improved after the establishment of an IVCFRP. This increase in IVCF retrieval rate was driven by an increase in filter retrievals in the non-trauma patient population. The rate of IVCF retrieval in trauma patients was not affected by the implementation of an IVCFRP. Special considerations and changes in practice may need to be established to improve IVCF retrieval rates in trauma patients.

Clinical significance: Implementation of a structured IVCFRP significantly improved retrieval rates in non-trauma patients but did not yield similar results in trauma patients, highlighting the need for alternative strategies in this population.