European Radiology Experimental最新文献

Background: Extensive glioblastoma infiltration justifies a 15-mm margin around the gross tumor volume (GTV) to define the radiotherapy clinical target volume (CTV). Amide proton transfer (APT)-weighted imaging could enable visualization of tumor infiltration, allowing more accurate GTV delineation. We quantified the impact of integrating APT-weighted imaging into GTV delineation of glioblastoma and compared two APT-weighted quantification methods-magnetization transfer ratio asymmetry (MTR_asym) and Lorentzian difference (LD) analysis-for target delineation.

Methods: Nine glioblastoma patients underwent an extended imaging protocol prior to radiotherapy, yielding APT-weighted MTR_asym and LD maps. From both maps, biological tumor volumes were generated (BTV_MTRasym and BTV_LD) and added to the conventional GTV to generate biological GTVs (GTV_bio,MTRasym and GTV_bio,LD). Wilcoxon signed-rank tests were performed for comparisons.

Results: The GTV_bio,MTRasym and GTV_bio,LD were significantly larger than the conventional GTV (p ≤ 0.022), with a median volume increase of 9.3% and 2.1%, respectively. The GTV_bio,MTRasym and GTV_bio,LD were significantly smaller than the CTV (p = 0.004), with a median volume reduction of 72.1% and 70.9%, respectively. There was no significant volume difference between the BTV_MTRasym and BTV_LD (p = 0.074). In three patients, BTV_MTRasym delineation was affected by elevated signals at the brain periphery due to residual motion artifacts; this elevation was absent on the APT-weighted LD maps.

Conclusion: Larger biological GTVs compared to the conventional GTV highlight the potential of APT-weighted imaging for radiotherapy target delineation of glioblastoma. APT-weighted LD mapping may be advantageous for target delineation as it may be more robust against motion artifacts.

Relevance statement: The introduction of APT-weighted imaging may, ultimately, enhance visualization of tumor infiltration and eliminate the need for the substantial 15-mm safety margin for target delineation of glioblastoma. This could reduce the risk of radiation toxicity while still effectively irradiating the tumor.

Trial registration: NCT05970757 (ClinicalTrials.gov).

Key points: Integration of APT-weighted imaging into target delineation for radiotherapy is feasible. The integration of APT-weighted imaging yields larger GTVs in glioblastoma. APT-weighted LD mapping may be more robust against motion artifacts than APT-weighted MTR_asym.

Background: Breast cancer (BC) is the most common malignancy in women and the second cause of cancer death. In recent years, there has been a strong development in artificial intelligence (AI) applications in medical imaging for several tasks. Our aim was to evaluate the potential of transfer learning with convolutional neural networks (CNNs) in discriminating suspicious breast lesions on ultrasound images.

Methods: Transfer learning performances of five different CNNs (Inception V3, Xception, Densenet121, VGG 16, and ResNet50) were evaluated on a public and on an institutional dataset (526 and 392 images, respectively), customizing the top layers for the specific task. Institutional images were contoured by an expert radiologist and processed to feed the CNNs for training and testing. Postimaging biopsies were used as a reference standard for classification. The area under the receiver operating curve (AUROC) was used to assess diagnostic performance.

Results: Networks performed very well on the public dataset (AUROC 0.938-0.996). The direct generalization to the institutional dataset resulted in lower performances (max AUROC 0.676); however, when tested on BI-RADS 3 and BI-RADS 5 only, results were improved (max AUROC 0.792). Good results were achieved on the institutional dataset (AUROC 0.759-0.818) and, when selecting a threshold of 2% for classification, a sensitivity of 0.983 was obtained for three of five CNNs, with the potential to spare biopsy in 15.3%-18.6% of patients.

Conclusion: In conclusion, transfer learning with CNNs may achieve high sensitivity and might be used as a support tool in managing suspicious breast lesions on ultrasound images.

Relevance statement: Transfer learning is a powerful technique to exploit the performances of well-trained CNNs for image classification. In a clinical scenario, it might be useful for the management of suspicious breast lesions on breast ultrasound, potentially sparing biopsy in a non-negligible number of patients.

Key points: Properly trained CNNs with transfer learning are highly effective in differentiating benign and malignant lesions on breast ultrasound. Setting clinical thresholds increased sensitivity. CNNs might be useful as support tools in managing suspicious lesions on breast ultrasound.

Background: This pilot prospective study aimed to evaluate ultrasound-guided cryoablation of breast cancer (BC) by assessing: (i) technical efficacy as the presence of necrosis in surgical specimens and rate of complete tumor ablation; (ii) safety as incidence and severity of complications; and (iii) patients' satisfaction using a dedicated questionnaire. In addition, (iv) we tested the capability of magnetic resonance imaging (MRI) or contrast-enhanced mammography (CEM) to predict cryoablation efficacy.

Methods: From 07/2022 to 01/2023, we enrolled 20 patients with early-stage BC scheduled for breast surgery. Ten of them, with a cryo-feasible cancer location, were sent to cryoablation (cryo-group) and ten to routine surgical practice (control group). Both groups underwent surgery and were asked to answer a satisfaction questionnaire.

Results: Of eleven patients screened for cryoablation, only one refused to be treated at another hospital (acceptance rate 10/11, 91%). Surgery was quadrantectomy in 19 cases and mastectomy in 1. In the cryo-group, the procedure was completed and steatonecrosis was observed in 10/10 cases, with complete tumor ablation in nine of them. The post-procedural status was evaluated with MRI in five patients, with CEM in four patients, and with ultrasound in one patient who refused MRI and CEM. MRI or CEM correctly predicted complete cryoablation in eight patients and incomplete cryoablation in one patient. Patients in both groups did not have serious complications and responded positively to satisfaction questionnaires.

Conclusion: Ultrasound-guided cryoablation of early-stage BC is well accepted by patients, effective, and safe. MRI and CEM were able to predict the procedure's technical efficacy.

Trial registration: https://clinicaltrials.gov/study/NCT05727813 updated February 14, 2023.

Relevance statement: Our pilot study showed that ultrasound-guided cryoablation is a promising nonsurgical alternative for treating early-stage BC.

Key points: Ultrasound-guided cryoablation was effective and safe in early BC patients. The procedure was well-tolerated, with low morbidity and high patient satisfaction. MRI and CEM predicted cryoablation efficacy, in accordance with histopathologic findings. Cryoablation can be considered a potential alternative to surgery in selected patients.

Background: To prospectively evaluate ultrasound backscatter coefficients (BSCs) of the supraspinatus and infraspinatus muscles and compare with Goutallier classification on magnetic resonance imaging (MRI).

Methods: Fifty-six participants had shoulder MRI exams and ultrasound exams of the supraspinatus and infraspinatus muscles. Goutallier MRI grades were determined and BSCs were measured. Group means were compared and the strength of relationships between the measures were determined. Using binarized Goutallier groups (0-2 versus 3-4), areas under the receiver operating characteristic curves (AUROCs) were calculated. The nearest integer cutoff value was determined using Youden's index.

Results: BSC values were significantly different among most Goutallier grades for the supraspinatus and infraspinatus muscles (both p < 0.001). Strong correlations were found between the BSC values and Goutallier grades for the supraspinatus (τ_b = 0.72, p < 0.001) and infraspinatus (τ_b = 0.79, p < 0.001) muscles. BSC showed excellent performance for classification of the binarized groups (0-2 versus 3-4) for both supraspinatus (AUROC = 0.98, p < 0.0001) and infraspinatus (AUROC = 0.98, p < 0.0001) muscles. Using a cutoff BSC value of -17 dB, sensitivity, specificity, and accuracy for severe fatty infiltration were 87.0%, 90.0%, and 87.5% for the supraspinatus muscle, and 93.6%, 87.5%, and 92.7% for the infraspinatus muscle.

Conclusion: BSC can be applied to the rotator cuff muscles for assessment of fatty infiltration. For both the supraspinatus and infraspinatus muscles, BSC values significantly increased with higher Goutallier grades and showed strong performance in distinguishing low versus high Goutallier grades.

Relevance statement: Fatty infiltration of the rotator cuff muscles can be quantified using BSC values, which are higher with increasing Goutallier grades.

Key points: Ultrasound BSC measurements are reliable for the quantification of muscle fatty infiltration. BCS values increased with higher Goutallier MRI grades. BCS values demonstrated high performance for distinguishing muscle fatty infiltration groups.

Background: Coronary computed tomography angiography (CCTA) offers non-invasive diagnostics of the coronary arteries. Vessel evaluation requires the administration of intravenous contrast. The purpose of this study was to evaluate the utility of gadolinium-based contrast agent (GBCA) as an alternative to iodinated contrast for CCTA on a first-generation clinical dual-source photon-counting-detector (PCD)-CT system.

Methods: A dynamic circulating phantom containing a three-dimensional-printed model of the thoracic aorta and the coronary arteries were used to evaluate injection protocols using gadopentetate dimeglumine at 50%, 100%, 150%, and 200% of the maximum approved clinical dose (0.3 mmol/kg). Virtual monoenergetic image (VMI) reconstructions ranging from 40 keV to 100 keV with 5 keV increments were generated on a PCD-CT. Contrast-to-noise ratio (CNR) was calculated from attenuations measured in the aorta and coronary arteries and noise measured in the background tissue. Attenuation of at least 350 HU was deemed as diagnostic.

Results: The highest coronary attenuation (441 ± 23 HU, mean ± standard deviation) and CNR (29.5 ± 1.5) was achieved at 40 keV and at the highest GBCA dose (200%). There was a systematic decline of attenuation and CNR with higher keV reconstructions and lower GBCA doses. Only reconstructions at 40 and 45 keV at 200% and 40 keV at 150% GBCA dose demonstrated sufficient attenuation above 350 HU.

Conclusion: Current PCD-CT protocols and settings are unsuitable for the use of GBCA for CCTA at clinically approved doses. Future advances to the PCD-CT system including a 4-threshold mode, as well as multi-material decomposition may add new opportunities for k-edge imaging of GBCA.

Relevance statement: Patients allergic to iodine-based contrast media and the future of multicontrast CT examinations would benefit greatly from alternative contrast media, but the utility of GBCA for coronary photon-counting-dector-CT angiography remains limited without further optimization of protocols and scanner settings.

Key points: GBCA-enhanced coronary PCD-CT angiography is not feasible at clinically approved doses. GBCAs have potential applications for the visualization of larger vessels, such as the aorta, on PCD-CT angiography. Higher GBCA doses and lower keV reconstructions achieved higher attenuation values and CNR.

Background: Dual-energy subtraction (DES) imaging is critical in contrast-enhanced mammography (CEM), as the recombination of low-energy (LE) and high-energy (HE) images produces contrast enhancement while reducing anatomical noise. The study's purpose was to compare the performance of the DES algorithm among three different CEM systems using a commercial phantom.

Methods: A CIRS Model 022 phantom, designed for CEM, was acquired using all available automatic exposure modes (AECs) with three CEM systems from three different manufacturers (CEM1, CEM2, and CEM3). Three studies were acquired for each system/AEC mode to measure both radiation dose and image quality metrics, including estimation of measurement error. The mean glandular dose (MGD) calculated over the three acquisitions was used as the dosimetry index, while contrast-to-noise ratio (CNR) was obtained from LE and HE images and DES images and used as an image quality metric.

Results: On average, the CNR of LE images of CEM1 was 2.3 times higher than that of CEM2 and 2.7 times higher than that of CEM3. For HE images, the CNR of CEM1 was 2.7 and 3.5 times higher than that of CEM2 and CEM3, respectively. The CNR remained predominantly higher for CEM1 even when measured from DES images, followed by CEM2 and then CEM3. CEM1 delivered the lowest MGD (2.34 ± 0.03 mGy), followed by CEM3 (2.53 ± 0.02 mGy) in default AEC mode, and CEM2 (3.50 ± 0.05 mGy). The doses of CEM2 and CEM3 increased by 49.6% and 8.0% compared with CEM1, respectively.

Conclusion: One system outperformed others in DES algorithms, providing higher CNR at lower doses.

Relevance statement: This phantom study highlighted the variability in performance among the DES algorithms used by different CEM systems, showing that these differences can be translated in terms of variations in contrast enhancement and radiation dose.

Key points: DES images, obtained by recombining LE and HE images, have a major role in CEM. Differences in radiation dose among CEM systems were between 8.0% and 49.6%. One DES algorithm achieved superior technical performance, providing higher CNR values at a lower radiation dose.

Background: The use of two-dimensional (2D) ultrasound for guiding radiofrequency ablation (RFA) of benign thyroid nodules presents limitations, including the inability to monitor the entire treatment volume and operator dependency in electrode positioning. We compared three-dimensional (3D)-guided RFA using a matrix ultrasound transducer with conventional 2D-ultrasound guidance in an anthropomorphic thyroid nodule phantom incorporated additionally with temperature-sensitive albumin.

Methods: Twenty-four phantoms with 48 nodules were constructed and ablated by an experienced radiologist using either 2D- or 3D-ultrasound guidance. Postablation T2-weighted magnetic resonance imaging scans were acquired to determine the final ablation temperature distribution in the phantoms. These were used to analyze ablation parameters, such as the nodule ablation percentage. Further, additional procedure parameters, such as dominant/non-dominant hand use, were recorded.

Results: Nonsignificant trends towards lower ablated volumes for both within (74.4 ± 9.1% (median ± interquartile range) versus 78.8 ± 11.8%) and outside of the nodule (0.35 ± 0.18 mL versus 0.45 ± 0.46 mL), along with lower variances in performance, were noted for the 3D-guided ablation. For the total ablation percentage, 2D-guided dominant hand ablation performed better than 2D-guided non-dominant hand ablation (81.0% versus 73.2%, p = 0.045), while there was no significant effect in the hand comparison for 3D-guided ablation.

Conclusion: 3D-ultrasound-guided RFA showed no significantly different results compared to 2D guidance, while 3D ultrasound showed a reduced variance in RFA. A significant reduction in operator-ablating hand dependence was observed when using 3D guidance. Further research into the use of 3D ultrasound for RFA is warranted.

Relevance statement: Using 3D ultrasound for thyroid nodule RFA could improve the clinical outcome. A platform that creates 3D data could be used for thyroid diagnosis, therapy planning, and navigational tools.

Key points: Twenty-four in-house-developed thyroid nodule phantoms with 48 nodules were constructed. RFA was performed under 2D- or 3D-ultrasound guidance. 3D- and 2D ultrasound-guided RFAs showed comparable performance. Real-time dual-plane imaging may offer an improved overview of the ablation zone and aid electrode positioning. Dominant and non-dominant hand 3D-ultrasound-guided RFA outcomes were comparable.

Background: Non-specific interstitial pneumonia (NSIP) is an interstitial lung disease that can result in end-stage fibrosis. We investigated the influence of body composition and pulmonary fat attenuation volume (CTpfav) on overall survival (OS) in NSIP patients.

Methods: In this retrospective single-center study, 71 NSIP patients with a median age of 65 years (interquartile range 21.5), 39 females (55%), who had a computed tomography from August 2009 to February 2018, were included, of whom 38 (54%) died during follow-up. Body composition analysis was performed using an open-source nnU-Net-based framework. Features were combined into: Sarcopenia (muscle/bone); Fat (total adipose tissue/bone); Myosteatosis (inter-/intra-muscular adipose tissue/total adipose tissue); Mediastinal (mediastinal adipose tissue/bone); and Pulmonary fat index (CTpfav/lung volume). Kaplan-Meier analysis with a log-rank test and multivariate Cox regression were used for survival analyses.

Results: Patients with a higher (> median) Sarcopenia and lower (< median) Mediastinal Fat index had a significantly better survival probability (2-year survival rate: 83% versus 71% for high versus low Sarcopenia index, p = 0.023; 83% versus 72% for low versus high Mediastinal fat index, p = 0.006). In univariate analysis, individuals with a higher Pulmonary fat index exhibited significantly worse survival probability (2-year survival rate: 61% versus 94% for high versus low, p = 0.003). Additionally, it was an independent risk predictor for death (hazard ratio 2.37, 95% confidence interval 1.03-5.48, p = 0.043).

Conclusion: Fully automated body composition analysis offers interesting perspectives in patients with NSIP. Pulmonary fat index was an independent predictor of OS.

Relevance statement: The Pulmonary fat index is an independent predictor of OS in patients with NSIP and demonstrates the potential of fully automated, deep-learning-driven body composition analysis as a biomarker for prognosis estimation.

Key points: This is the first study assessing the potential of CT-based body composition analysis in patients with non-specific interstitial pneumonia (NSIP). A single-center analysis of 71 patients with board-certified diagnosis of NSIP is presented Indices related to muscle, mediastinal fat, and pulmonary fat attenuation volume were significantly associated with survival at univariate analysis. CT pulmonary fat attenuation volume, normalized by lung volume, resulted as an independent predictor for death.