Clinical Imaging最新文献

Purpose

Favorable clinical outcomes have been reported with the adjunct use of beta-blockers in cancer treatment, hypothetically secondary to their anti-angiogenic/anti-proliferative effects. Hereby, we investigate whether there is synergy between beta-blockers and TACE in the treatment of HCC.

Methods

36 HCC patients on beta-blockers (mean dose of 48 mg daily) at the time of first-line treatment with TACE at our institution were retrospectively identified out of a cohort of 221 patients between 2008 and 2019. Using propensity scoring, a matched cohort of 36 patients not exposed to beta-blockers was generated based on age, gender, ethnicity, etiology of liver disease, BCLC, child Pugh score, PS/ECOG, cirrhosis, largest mass treated, type of TACE and treated liver segments. Tumor response was assessed at 1st and 2nd post-TACE imaging timepoints (1.4 and 4.1 months on average respectively). Variables were compared using chi-square test and Student's t-test. Kaplan-Meier transplant-free survival plots were generated using IBM® SPSS® software. Cox regression analysis was used to evaluate survival predictors. A p values < 0.05 was considered significant.

Results

Comparing the control and beta-blocker cohorts, there were no differences in baseline characteristics, post-TACE imaging timepoints, tumor response or transplant free survival (p > 0.05). Tumor size was found to be a predictor of survival when the two cohorts were combined (p = 0.03).

Conclusion

Transplant-free survival and HCC response to first-line TACE treatment were similar in the control and beta-blocker groups. Large tumor sizes were associated with higher mortality in combined analysis of the cohorts.

Objective

AI adoption requires perceived value by end-users. AI-enabled opportunistic CT screening (OS) detects incidental clinically meaningful imaging risk markers on CT for potential preventative health benefit. This investigation assesses radiologists' perspectives on AI and OS.

Methods

An online survey was distributed to 7500 practicing radiologists among ACR membership of which 4619 opened the emails. Familiarity with and views of AI applications were queried and tabulated, as well as knowledge of OS and inducements and impediments to use.

Results

Respondent (n = 211) demographics: mean age 55 years, 73 % male, 91 % diagnostic radiologists, 46 % in private practice. 68 % reported using AI in practice, while 52 % were only somewhat familiar with AI. 70 % viewed AI positively though only 46 % reported AI's overall accuracy met expectations. 57 % were unfamiliar with OS, with 52 % of those familiar having a positive opinion. Patient perceptions were the most commonly reported (25 %) inducement for OS use. Provider (44 %) and patient (40 %) costs were the most common impediments. Respondents reported that osteoporosis/osteopenia (81 %), fatty liver (78 %), and atherosclerotic cardiovascular disease risk (76 %) could be well assessed by OS. Most indicated OS output requires radiologist oversight/signoff and should be included in a separate “screening” section in the Radiology report. 28 % indicated willingness to spend 1–3 min reviewing AI-generated output while 18 % would not spend any time. Society guidelines/recommendations were most likely to impact OS implementation.

Discussion

Radiologists' perspectives on AI and OS provide practical insights on AI implementation. Increasing end-user familiarity with AI-enabled applications and development of society guidelines/recommendations are likely essential prerequisites for Radiology AI adoption.

Large Language Models (LLM) like ChatGPT-4 hold significant promise in medical application, especially in the field of radiology. While previous studies have shown the promise of ChatGTP-4 in textual-based scenarios, its performance on image-based response remains suboptimal. This study investigates the impact of prompt engineering on ChatGPT-4's accuracy on the 2022 American College of Radiology In Training Test Questions for Diagnostic Radiology Residents that include textual and visual-based questions. Four personas were created, each with unique prompts, and evaluated using ChatGPT-4. Results indicate that encouraging prompts and those disclaiming responsibility led to higher overall accuracy (number of questions answered correctly) compared to other personas. Personas that threaten the LLM with legal action or mounting clinical responsibility were not only found to score less, but also refrain of answering questions at a higher rate. These findings highlight the importance of prompt context in optimizing LLM responses and the need for further research to integrate AI responsibly into medical practice.

Purpose

To characterize brain MR imaging findings in a cohort of 58 patients with ECD and to evaluate relationship between these findings and the BRAF^V600E pathogenic variant.

Methods

ECD patients of any gender and ethnicity, aged 2–80 years, with biopsy-confirmed ECD were eligible to enroll in this study. Two radiologists experienced in evaluating ECD CNS disease activity reviewed MRI studies. Any disagreements were resolved by a third reader. Frequencies of observed lesions were reported. The association between the distribution of CNS lesions and the BRAF^V600Epathogenic variant was evaluated using Fisher's exact test and odd ratio.

Results

The brain MRI of all 58 patients with ECD revealed some form of CNS lesions, most likely due to ECD. Cortical lesions were noted in 27/58 (46.6 %) patients, cerebellar lesions in 15/58 (25.9 %) patients, brain stem lesions in 17/58 cases (29.3 %), and pituitary lesions in 10/58 (17.2 %) patients. Premature cortical atrophy was observed in 8/58 (13.8 %) patients. BRAF^V600E pathogenic variant was significantly associated with cerebellar lesions (p = 0.016) and bilateral brain stem lesions (p = 0.043). A trend toward significance was noted for cerebral atrophy (p = 0.053).

Conclusion

The study provides valuable insights into the brain MRI findings in ECD and their association with the BRAF^V600E pathogenic variant, particularly its association in cases with bilateral lesions. We are expanding our understanding of how ECD affects cerebral structures. Knowledge of MRI CNS lesion patterns and their association with mutations such as the BRAF variant is helpful for both prognosis and clinical management.

Purpose

Succinate dehydrogenase (SDH)-deficient renal cell carcinoma (RCC) is a newly defined, rare subtype of renal cancer, associated with pathogenic variations in the Succinate Dehydrogenase Subunit B (SDHB) gene. Our aim is to investigate the imaging findings of SDHB-associated renal tumors, utilizing cross-sectional and FDG-PET imaging in patients with pathogenic variations in SDHB gene, to facilitate accurate tumor characterization.

Methods

Twenty SDH-deficient tumors from 16 patients with pathogenic variations in SDHB gene were retrospectively evaluated using cross-sectional and FDG-PET imaging. Clinical findings such as demographics, family history, extra-renal findings and metastases were recorded. Tumor imaging characteristics on CT/MRI included were laterality, size, homogeneity, morphology, margins, internal content, T1/T2 signal intensity, enhancement features, and restricted diffusion.

Results

Sixteen patients (median age 31 years, IQR 19–41, 8 males) were identified with 68.8 % of patients having a known family history of SDHB variation. 81.3 % of lesions were solitary and majority were solid (86.7 % on CT, 87.5 % on MRI) with well-defined margins in >62.5 % of lesions, without evidence of internal fat, calcifications, or vascular invasion. 100 % of lesions demonstrated restricted diffusion and avid enhancement, with degree >75 % for most lesions on CT and MRI. On FDG-PET, all renal masses showed increased radiotracer uptake. 43.8 % of patients demonstrated extra-renal manifestations and 43.8 % had distant metastasis.

Conclusion

SDHB-associated RCC is predominantly noted in young patients with no gender predilection. On imaging, SDH-deficient RCC are frequently unilateral, solitary, and solid with well-defined margins demonstrating avid enhancement with variability in enhancement pattern and showing restricted diffusion.

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.

Purpose

This study aimed to systematically assess the quality and performance of computed tomography (CT) radiomics studies in predicting brain metastasis (BM) among patients with lung cancer.

Methods

The PubMed, Embase and Web of Science were searched for studies predicting BM in patients with lung cancer using CT-based radiomics features. Information regarding patients, imaging, and radiomics analysis was extracted from eligible studies. We assessed the quality of included studies using the Radiomics Quality Scoring (RQS) tool and the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). A meta-analysis of studies regarding the prediction of BM in patients with lung cancer was performed.

Results

Thirteen studies were identified, with sample sizes ranging from 75 to 602. The mean RQS of the studies was 12 (range 9–16), and the corresponding percentage of the score was 33.55 % (range 25.00–44.44 %). Four studies (30.8 %) were considered as low risk of bias, while the remaining nine studies (69.2 %) were considered to have unclear risks. The meta-analysis included twelve studies. The pooled sensitivity, specificity and Area Under the Curve (AUC) value with 95 % confidence intervals were 0.75 [0.69, 0.80], 0.76 [0.68, 0.82], and 0.81 [0.77–0.84], respectively.

Conclusion

CT radiomics-based models show promising results as a non-invasive method to predict BM in lung cancer patients. However, multicenter and prospective studies are warranted to enhance the stability and acceptance of radiomics.

Purpose

MRI-based VI-RADS score aids in differentiating MIBC and NMIBC, but the experience's impact remains unexplored. We aimed to determine the effect of accumulating experience in the diagnostic performance of VI-RADS.

Methods

In our previously published series 71 primary bladder cancer patients who underwent multiparametric MRI before the transurethral resection were analyzed. The radiologist who assessed the VI-RADS scores at the time the study was performed, re-evaluated all cases after 3 years, in a blinded fashion. During these three years, more than 300 additional bladder MRIs were performed for VI-RADS assessment. The diagnostic performances of the initial and subsequent VI-RADS analyses were compared. Moreover, VIRADS results obtained by a newly trained abdominal radiologist was also compared with experienced radiologist's results. For this study, VI-RADS ≥3 was accepted for predicting MIBC.

Results

Overall 71 patients [62 (87.3 %) males, 67.4 ± 10.2 years] who underwent bladder MRI before TURBT were included. Histopathology revealed MIBC in 16 (26.2 %) cases.

The initial MRI analysis revealed VI-RADS score ≥ 3 in 36 (50.7 %) cases. The sensitivity and specificity for depicting MIBC were 75 % and 56.4 % respectively. The subsequent MRI analysis revealed VI-RADS score ≥ 3 in 23 (32.4 %) cases. The sensitivity and specificity were 93.8 % and 85.5 % respectively. The MRI analysis performed by the recently trained abdominal radiologist revealed VI-RADS score ≥ 3 in 24 (33.8 %) cases. The sensitivity and specificity were 87.5 % and 56.4 % respectively.

Conclusion

The diagnostic performance of VI-RADS for the interpretation of bladder MRI can improve over time by increasing the experience of the urogenital radiologist.

The “hot cross bun” sign is a rare radiologic sign seen on magnetic resonance imaging that can help direct the diagnosis of the cerebellar subtype of multiple system atrophy. It indicates damage to the transverse pontocerebellar fibers and can be seen in other pathologies including spinocerebellar ataxia.

The name for this radiologic sign was coined in 1998, likening the cruciform hyperintensity on imaging to the English spiced bun marked with a cross and historically eaten on the Christian religious holiday Good Friday.