Radiologia Medica最新文献

Patients who have heart failure with preserved ejection fraction (HFpEF) have signs and symptoms of heart failure, yet their ejection fraction remains greater than or equal to 50 percent. Understanding the underlying cause of HFpEF is crucial for accurate diagnosis and effective treatment. This condition can be caused by multiple factors, including ischemic or nonischemic myocardial diseases. HFpEF is often associated with diastolic dysfunction. Cardiac magnetic resonance (CMR) allows for a precise examination of the functional and structural alterations associated with HFpEF through the measurement of volumes and mass, the assessment of systolic and diastolic function, and the analysis of tissue characteristics. We will discuss CMR imaging indicators that are specific to patients with HFpEF and their relation to the disease. These markers can be acquired through both established and emerging methods.

Purpose: To evaluate the efficacy of US-guided vacuum-assisted biopsy (US-VAB) in radiologic-pathologic (rad-path) discordance in women with suspicious breast lesions.

Methods: Two thousand three hundred and sixty patients with 2385 BI-RADS category 4 and 5 lesions underwent percutaneous US-guided CNB. Thirty-six lesions were classified as discordant benign and underwent second-line US-VAB. A 14-gauge needle was utilized for CNB and 10-gauge for US-VAB. Final pathology was the reference standard for women who underwent surgery, imaging follow-up in other cases. Rates of malignancy for US-VAB and subsequent surgery were evaluated. Lesions with upgrade and no upgrade to second-line VAB were compared in terms of patient's age, lesion type and characteristics, size and BI-RADS category. Positive predictive value (PPV), negative predictive value (NPV) for BI-RADS categories and diagnostic performance for second-line US-VAB were calculated. p value < 0.05 was considered statistically significant (t-test, Mann-Whitney, χ²).

Results: US-VAB identified 10 B2, 9 B3 and 17 B5 lesions with upgrade to malignancy of 47.2% (17/36). There were 8 invasive no special type, 7 ductal in situ, 1 invasive lobular carcinoma and 1 angiosarcoma, and their distribution among BI-RADS categories was: 2/2 in BI-RADS 5 (100%), 12/18 in BI-RADS 4C (67%) and 3/16 in BI-RADS 4B lesions (19%) (p = 0.006). Of the remaining 19 lesions, 6 underwent surgery and 2 were upgraded to ductal carcinoma in situ; 13 underwent radiological follow-up and one resulted malignant. False-negative rate for US-VAB was 15.8% (3/19) with final upgrade to malignancy of 55% (20/36). The univariate analysis revealed mass shape (p = 0.008) and BI-RADS categories (p = 0.006) to be associated with upgrade to malignancy. Sensitivity, specificity, PPV, NPV and accuracy for US-VAB were 85, 100, 100, 84 and 92%, respectively.

Conclusions: US-VAB identified almost 50% of cancers missed by CNB, avoiding surgical biopsies and validating as an effective mini-invasive approach in rad-path discordance.

Purpose: This study aimed to determine the accuracy of detecting ischemic core volume using computed tomography perfusion (CTP) in patients with suspected acute ischemic stroke compared to diffusion-weighted magnetic resonance imaging (DW-MRI) as the reference standard.

Methods: This retrospective monocentric study included patients who underwent CTP and DW-MRI for suspected acute ischemic stroke. The ischemic core size was measured at DW-MRI. The detectability threshold volume was defined as the lowest volume detected by each method. Clinical data on revascularization therapy, along with the clinical decision that influenced the choice, were collected. Volumes of the ischemic cores were compared using the Mann-Whitney U test.

Results: Of 83 patients who underwent CTP, 52 patients (median age 73 years, IQR 63-80, 36 men) also had DW-MRI and were included, with a total of 70 ischemic cores. Regarding ischemic cores, only 18/70 (26%) were detected by both CTP and DW-MRI, while 52/70 (74%) were detected only by DW-MRI. The median volume of the 52 ischemic cores undetected on CTP (0.6 mL, IQR 0.2-1.3 mL) was significantly lower (p < 0.001) than that of the 18 ischemic cores detected on CTP (14.2 mL, IQR 7.0-18.4 mL). The smallest ischemic core detected on CTP had a volume of 5.0 mL. Among the 20 patients with undetected ischemic core on CTP, only 10% (2/20) received thrombolysis treatment.

Conclusions: CTP maps failed in detecting ischemic cores smaller than 5 mL. DW-MRI remains essential for suspected small ischemic brain lesions to guide a correct treatment decision-making.

Purpose: Evaluate the agreement between bone age assessments conducted by two distinct machine learning system and standard Greulich and Pyle method.

Materials and methods: Carpal radiographs of 225 patients (mean age 8 years and 10 months, SD = 3 years and 1 month) were retrospectively analysed at two separate institutions (October 2018 and May 2022) by both expert radiologists and radiologists in training as well as by two distinct AI software programmes, 16-bit AI^tm and BoneXpert® in a blinded manner.

Results: The bone age range estimated by the 16-bit AI^tm system in our sample varied between 1 year and 1 month and 15 years and 8 months (mean bone age 9 years and 5 months SD = 3 years and 3 months). BoneXpert® estimated bone age ranged between 8 months and 15 years and 7 months (mean bone age 8 years and 11 months SD = 3 years and 3 months). The average bone age estimated by the Greulich and Pyle method was between 11 months and 14 years, 9 months (mean bone age 8 years and 4 months SD = 3 years and 3 months). Radiologists' assessments using the Greulich and Pyle method were significantly correlated (Pearson's r > 0.80, p < 0.001). There was no statistical difference between BoneXpert® and 16-bit AI^tm (mean difference = - 0.19, 95%CI = (- 0.45; 0.08)), and the agreement between two measurements varies between - 3.45 (95%CI = (- 3.95; - 3.03) and 3.07 (95%CI - 3.03; 3.57).

Conclusions: Both AI methods and GP provide correlated results, although the measurements made by AI were closer to each other compared to the GP method.

Introduction: While thermal ablation is now a standard treatment option for oligometastatic colorectal cancer patients, selecting those who will benefit most from locoregional therapies remains challenging. This proof-of-concept study is the first to assess the feasibility of routine testing of ctDNA before and after thermal ablation with curative intent, analyzed by next-generation sequencing (NGS) and methylation specific digital droplet PCR (ddPCR). Our prospective study primary objective was to assess the prognostic value of ctDNA before thermal ablation.

Methods: This single-center prospective study from November 2021 to June 2022 included colorectal cancer patients referred for curative-intent thermal ablation. Cell-free DNA was tested at different time points by next-generation sequencing and detection of WIF1 and NPY genes hypermethylation using ddPCR. The ctDNA was considered positive if either a tumor mutation or hypermethylation was detected; recurrence-free survival was used as the primary endpoint.

Results: The study enrolled 15 patients, and a total of 60 samples were analyzed. The median follow-up after ablation was 316 days, and median recurrence-free survival was 250 days. CtDNA was positive for 33% of the samples collected during the first 24 h. The hazard ratio for progression according to the presence of baseline circulating tumor DNA was estimated at 0.14 (CI 95%: 0.03-0.65, p = 0.019). The dynamics are provided, and patients with no recurrence were all negative at H24 for ctDNA.

Discussion: This study shows the feasibility of routine testing of ctDNA before and after thermal ablation with curative intent. We report that circulating tumor DNA is detectable in patients with low tumor burden using 2 techniques. This study emphasizes the potential of ctDNA for discerning patients who are likely to benefit from thermal ablation from those who may not, which could shape future referrals. The dynamics of ctDNA before and after ablation shed light on the need for further research and larger studies.

Purpose: To evaluate a deep learning-based pipeline using a Dense-UNet architecture for the assessment of acute intracranial hemorrhage (ICH) on non-contrast computed tomography (NCCT) head scans after traumatic brain injury (TBI).

Materials and methods: This retrospective study was conducted using a prototype algorithm that evaluated 502 NCCT head scans with ICH in context of TBI. Four board-certified radiologists evaluated in consensus the CT scans to establish the standard of reference for hemorrhage presence and type of ICH. Consequently, all CT scans were independently analyzed by the algorithm and a board-certified radiologist to assess the presence and type of ICH. Additionally, the time to diagnosis was measured for both methods.

Results: A total of 405/502 patients presented ICH classified in the following types: intraparenchymal (n = 172); intraventricular (n = 26); subarachnoid (n = 163); subdural (n = 178); and epidural (n = 15). The algorithm showed high diagnostic accuracy (91.24%) for the assessment of ICH with a sensitivity of 90.37% and specificity of 94.85%. To distinguish the different ICH types, the algorithm had a sensitivity of 93.47% and a specificity of 99.79%, with an accuracy of 98.54%. To detect midline shift, the algorithm had a sensitivity of 100%. In terms of processing time, the algorithm was significantly faster compared to the radiologist's time to first diagnosis (15.37 ± 1.85 vs 277 ± 14 s, p < 0.001).

Conclusion: A novel deep learning algorithm can provide high diagnostic accuracy for the identification and classification of ICH from unenhanced CT scans, combined with short processing times. This has the potential to assist and improve radiologists' ICH assessment in NCCT scans, especially in emergency scenarios, when time efficiency is needed.

Purpose: To evaluate if background parenchymal enhancement (BPE) on contrast-enhanced mammography (CEM), graded according to the 2022 CEM-dedicated Breast Imaging Reporting and Data System (BI-RADS) lexicon, is associated with breast density, menopausal status, and age.

Methods: This bicentric retrospective analysis included CEM examinations performed for the work-up of suspicious mammographic findings. Three readers independently and blindly evaluated BPE on recombined CEM images and breast density on low-energy CEM images. Inter-reader reliability was estimated using Fleiss κ. Multivariable binary logistic regression was performed, dichotomising breast density and BPE as low (a/b BI-RADS categories, minimal/mild BPE) and high (c/d BI-RADS categories, moderate/marked BPE).

Results: A total of 200 women (median age 56.8 years, interquartile range 50.5-65.6, 140/200 in menopause) were included. Breast density was classified as a in 27/200 patients (13.5%), as b in 110/200 (55.0%), as c in 52/200 (26.0%), and as d in 11/200 (5.5%), with moderate inter-reader reliability (κ = 0.536; 95% confidence interval [CI] 0.482-0.590). BPE was minimal in 95/200 patients (47.5%), mild in 64/200 (32.0%), moderate in 25/200 (12.5%), marked in 16/200 (8.0%), with substantial inter-reader reliability (κ = 0.634; 95% CI 0.581-0.686). At multivariable logistic regression, premenopausal status and breast density were significant positive predictors of high BPE, with adjusted odds ratios of 6.120 (95% CI 1.847-20.281, p = 0.003) and 2.416 (95% CI 1.095-5.332, p = 0.029) respectively.

Conclusion: BPE on CEM is associated with well-established breast cancer risk factors, being higher in women with higher breast density and premenopausal status.