European Radiology Experimental最新文献

Background: We compared ultra-high resolution (UHR), standard resolution (SR), and virtual non-calcium (VNCa) reconstruction for coronary artery stenosis evaluation using photon-counting computed tomography (PC-CT).

Methods: One vessel phantom (4-mm diameter) containing solid calcified lesions with 25% and 50% stenoses inside a thorax phantom with motion simulation underwent PC-CT using UHR (0.2-mm slice thickness) and SR (0.6-mm slice thickness) at heart rates of 60 beats per minute (bpm), 80 bpm, and 100 bpm. A paired t-test or Wilcoxon test with Bonferroni correction was used.

Results: For 50% stenosis, differences in percent mean diameter stenosis between UHR and SR at 60 bpm (51.0 vs 60.3), 80 bpm (51.7 vs 59.6), and 100 bpm (53.7 vs 59.0) (p ≤ 0.011), as well as between VNCa and SR at 60 bpm (50.6 vs 60.3), 80 bpm (51.5 vs 59.6), and 100 bpm (53.7 vs 59.0) were significant (p ≤ 0.011), while differences between UHR and VNCa at all heart rates (p ≥ 0.327) were not significant. For 25% stenosis, differences between UHR and SR at 60 bpm (28.0 vs 33.7), 80 bpm (28.4 vs 34.3), and VNCa vs SR at 60 bpm (29.1 vs 33.7) were significant (p ≤ 0.015), while differences for UHR vs SR at 100 bpm (29.9 vs 34.0), as well as for VNCa vs SR at 80 bpm (30.7 vs 34.3) and 100 bpm (33.1 vs 34.0) were not significant (p ≥ 0.028).

Conclusion: Stenosis quantification accuracy with PC-CT improved using either UHR acquisition or VNCa reconstruction.

Relevance statement: PC-CT offers to scan with UHR mode and the reconstruction of VNCa images both of them could provide improved coronary stenosis quantification at increased heart rates, allowing a more accurate stenosis grading at low and high heart rates compared to SR.

Key points: Evaluation of coronary stenosis with conventional CT is challenging at high heart rates. PC-CT allows for scanning with ECG-gated UHR and SR modes. UHR and VNCa images were compared in a dynamic phantom. UHR improves stenosis quantification up to 100 bpm. VNCa reconstruction improves stenosis evaluation up to 80 bpm.

Background: Radiomics is not yet used in clinical practice due to concerns regarding its susceptibility to technical factors. We aimed to assess the stability and interscan and interreader reproducibility of myocardial radiomic features between energy-integrating detector computed tomography (EID-CT) and photon-counting detector CT (PCD-CT) in patients undergoing coronary CT angiography (CCTA) on both systems.

Methods: Consecutive patients undergoing clinically indicated CCTA on an EID-CT were prospectively enrolled for a PCD-CT CCTA within 30 days. Virtual monoenergetic images (VMI) at various keV levels and polychromatic images (T3D) were generated for PCD-CT, with image reconstruction parameters standardized between scans. Two readers performed myocardial segmentation and 110 radiomic features were compared intraindividually between EID-CT and PDC-CT series. The agreement of parameters was assessed using the intraclass correlation coefficient and paired t-test for the stability of the parameters.

Results: Eighteen patients (15 males) aged 67.6 ± 9.7 years (mean ± standard deviation) were included. Besides polychromatic PCD-CT reconstructions, 60- and 70-keV VMIs showed the highest feature stability compared to EID-CT (96%, 90%, and 92%, respectively). The interscan reproducibility of features was moderate even in the most favorable comparisons (median ICC 0.50 [interquartile range 0.20-0.60] for T3D; 0.56 [0.33-0.74] for 60 keV; 0.50 [0.36-0.62] for 70 keV). Interreader reproducibility was excellent for the PCD-CT series and good for EID-CT segmentations.

Conclusion: Most myocardial radiomic features remain stable between EID-CT and PCD-CT. While features demonstrated moderate reproducibility between scanners, technological advances associated with PCD-CT may lead to greater reproducibility, potentially expediting future standardization efforts.

Relevance statement: While the use of PCD-CT may facilitate reduced interreader variability in radiomics analysis, the observed interscanner variations in comparison to EID-CT should be taken into account in future research, with efforts being made to minimize their impact in future radiomics studies.

Key points: Most myocardial radiomic features resulted in being stable between EID-CT and PCD-CT on certain VMIs. The reproducibility of parameters between detector technologies was limited. PCD-CT improved interreader reproducibility of myocardial radiomic features.

Background: The complex anatomy of peripheral nerves has been traditionally investigated through histological microsections, with inherent limitations. We aimed to compare three-dimensional (3D) reconstructions of median and ulnar nerves acquired with tomographic high-resolution ultrasound (HRUS) and magnetic resonance microscopy (MRM) and assess their capacity to depict intraneural anatomy.

Methods: Three fresh-frozen human upper extremity specimens were prepared for HRUS imaging by submersion in a water medium. The median and ulnar nerves were pierced with sutures to improve orientation during imaging. Peripheral nerve 3D HRUS scanning was performed on the mid-upper arm using a broadband linear probe (10-22 MHz) equipped with a tomographic 3D HRUS system. Following excision, nerves were cut into 16-mm segments and loaded into the MRM probe of a 9.4-T system (scanning time 27 h). Fascicle and nerve counting was performed to estimate the nerve volume, fascicle volume, fascicle count, and number of interfascicular connections. HRUS reconstructions employed artificial intelligence-based algorithms, while MRM reconstructions were generated using an open-source imaging software 3D slicer.

Results: Compared to MRM, 3D HRUS underestimated nerve volume by up to 22% and volume of all fascicles by up to 11%. Additionally, 3D HRUS depicted 6-60% fewer fascicles compared to MRM and visualized approximately half as many interfascicular connections.

Conclusion: MRM demonstrated a more detailed fascicular depiction compared to 3D HRUS, with a greater capacity for visualizing smaller fascicles. While 3D HRUS reconstructions can offer supplementary data in peripheral nerve assessment, their limitations in depicting interfascicular connections and small fascicles within clusters necessitate cautious interpretation.

Clinical relevance statement: Although 3D HRUS reconstructions can offer supplementary data in peripheral nerve assessment, even in intraoperative settings, their limitations in depicting interfascicular branches and small fascicles within clusters require cautious interpretation.

Key points: 3D HRUS was limited in visualizing nerve interfascicular connections. MRM demonstrated better nerve fascicle depiction than 3D HRUS. MRM depicted more nerve interfascicular connections than 3D HRUS.

Electromagnetic tracking of endovascular instruments has the potential to substantially decrease radiation exposure of patients and personnel. In this study, we evaluated the in vivo accuracy of a vessel-based method to register preoperative computed tomography angiography (CTA) images to physical coordinates using an electromagnetically tracked guidewire. Centerlines of the aortoiliac arteries were extracted from preoperative CTA acquired from five swine. Intravascular positions were obtained from an electromagnetically tracked guidewire. An iterative-closest-point algorithm registered the position data to the preoperative image centerlines. To evaluate the registration accuracy, a guidewire was placed inside the superior mesenteric, left and right renal arteries under fluoroscopic guidance. Position data was acquired with electromagnetic tracking as the guidewire was pulled into the aorta. The resulting measured positions were compared to the corresponding ostia manually identified in the CTA images after applying the registration. The three-dimensional (3D) Euclidean distances were calculated between each corresponding ostial point, and the root mean square (RMS) was calculated for each registration. The median 3D RMS for all registrations was 4.82 mm, with an interquartile range of 3.53-6.14 mm. A vessel-based registration of CTA images to vascular anatomy is possible with acceptable accuracy and encourages further clinical testing. RELEVANCE STATEMENT: This study shows that the centerline algorithm can be used to register preoperative CTA images to vascular anatomy, with the potential to further reduce ionizing radiation exposure during vascular procedures. KEY POINTS: Preoperative images can be used to guide the procedure without ionizing intraoperative imaging. Preoperative imaging can be the only imaging modality used for guidance of vascular procedures. No need to use external fiducial markers to register/match images and spatial anatomy. Acceptable accuracy can be achieved for navigation in a preclinical setting.

Background: We evaluated the role of dual-energy computed tomography (DECT)-based collagen maps in assessing thoracic disc degeneration.

Methods: We performed a retrospective analysis of patients who underwent DECT and magnetic resonance imaging (MRI) of the thoracic spine within a 2-week period from July 2019 to October 2022. Thoracic disc degeneration was classified by three blinded radiologists into three Pfirrmann categories: no/mild (grade 1-2), moderate (grade 3-4), and severe (grade 5). The DECT performance was determined using MRI as a reference standard. Interreader reliability was assessed using intraclass correlation coefficient (ICC). Five-point Likert scales were used to assess diagnostic confidence and image quality.

Results: In total, 612 intervertebral discs across 51 patients aged 68 ± 16 years (mean ± standard deviation), 28 males and 23 females, were assessed. MRI revealed 135 no/mildly degenerated discs (22.1%), 470 moderately degenerated discs (76.8%), and 7 severely degenerated discs (1.1%). DECT collagen maps achieved an overall accuracy of 1,483/1,838 (80.8%) for thoracic disc degeneration. Overall recall (sensitivity) was 331/405 (81.7%) for detecting no/mild degeneration, 1,134/1,410 (80.4%) for moderate degeneration, and 18/21 (85.7%) for severe degeneration. Interrater agreement was good (ICC = 0.89). Assessment of DECT-based collagen maps demonstrated high diagnostic confidence (median 4; interquartile range 3-4) and good image quality (median 4; interquartile range 4-4).

Conclusion: DECT showed an overall 81% accuracy for disc degeneration by visualizing differences in the collagen content of thoracic discs.

Relevance statement: Utilizing DECT-based collagen maps to distinguish various stages of thoracic disc degeneration could be clinically relevant for early detection of disc-related conditions. This approach may be particularly beneficial when MRI is contraindicated.

Key points: A total of 612 intervertebral discs across 51 patients were retrospectively assessed with DECT, using MRI as a reference standard. DECT-based collagen maps allowed thoracic disc degeneration assessment achieving an overall 81% accuracy with good interrater agreement (ICC = 0.89). DECT-based collagen maps could be a good alternative in the case of contraindications to MRI.

Background: Microsatellite instability (MSI) status is a strong predictor of response to immunotherapy of colorectal cancer. Radiogenomic approaches promise the ability to gain insight into the underlying tumor biology using non-invasive routine clinical images. This study investigates the association between tumor morphology and the status of MSI versus microsatellite stability (MSS), validating a novel radiomic signature on an external multicenter cohort.

Methods: Preoperative computed tomography scans with matched MSI status were retrospectively collected for 243 colorectal cancer patients from three hospitals: Seoul National University Hospital (SNUH); Netherlands Cancer Institute (NKI); and Fondazione IRCCS Istituto Nazionale dei Tumori, Milan Italy (INT). Radiologists delineated primary tumors in each scan, from which radiomic features were extracted. Machine learning models trained on SNUH data to identify MSI tumors underwent external validation using NKI and INT images. Performances were compared in terms of area under the receiving operating curve (AUROC).

Results: We identified a radiomic signature comprising seven radiomic features that were predictive of tumors with MSS or MSI (AUROC 0.69, 95% confidence interval [CI] 0.54-0.84, p = 0.018). Integrating radiomic and clinical data into an algorithm improved predictive performance to an AUROC of 0.78 (95% CI 0.60-0.91, p = 0.002) and enhanced the reliability of the predictions.

Conclusion: Differences in the radiomic morphological phenotype between tumors MSS or MSI could be detected using radiogenomic approaches. Future research involving large-scale multicenter prospective studies that combine various diagnostic data is necessary to refine and validate more robust, potentially tumor-agnostic MSI radiogenomic models.

Relevance statement: Noninvasive radiomic signatures derived from computed tomography scans can predict MSI in colorectal cancer, potentially augmenting traditional biopsy-based methods and enhancing personalized treatment strategies.

Key points: Noninvasive CT-based radiomics predicted MSI in colorectal cancer, enhancing stratification. A seven-feature radiomic signature differentiated tumors with MSI from those with MSS in multicenter cohorts. Integrating radiomic and clinical data improved the algorithm's predictive performance.

Background: Magnetic resonance neurography (MRN) is increasingly used as a diagnostic tool for peripheral neuropathies. Quantitative measures enhance MRN interpretation but require nerve segmentation which is time-consuming and error-prone and has not become clinical routine. In this study, we applied neural networks for the automated segmentation of peripheral nerves.

Methods: A neural segmentation network was trained to segment the sciatic nerve and its proximal branches on the MRN scans of the right and left upper leg of 35 healthy individuals, resulting in 70 training examples, via 5-fold cross-validation (CV). The model performance was evaluated on an independent test set of one-sided MRN scans of 60 healthy individuals.

Results: Mean Dice similarity coefficient (DSC) in CV was 0.892 (95% confidence interval [CI]: 0.888-0.897) with a mean Jaccard index (JI) of 0.806 (95% CI: 0.799-0.814) and mean Hausdorff distance (HD) of 2.146 (95% CI: 2.184-2.208). For the independent test set, DSC and JI were lower while HD was higher, with a mean DSC of 0.789 (95% CI: 0.760-0.815), mean JI of 0.672 (95% CI: 0.642-0.699), and mean HD of 2.118 (95% CI: 2.047-2.190).

Conclusion: The deep learning-based segmentation model showed a good performance for the task of nerve segmentation. Future work will focus on extending training data and including individuals with peripheral neuropathies in training to enable advanced peripheral nerve disease characterization.

Relevance statement: The results will serve as a baseline to build upon while developing an automated quantitative MRN feature analysis framework for application in routine reading of MRN examinations.

Key points: Quantitative measures enhance MRN interpretation, requiring complex and challenging nerve segmentation. We present a deep learning-based segmentation model with good performance. Our results may serve as a baseline for clinical automated quantitative MRN segmentation.

Background: The diagnostic value of clinical rotator cuff (RC) tests is controversial, with only sparse evidence available about their anatomical specificity. We prospectively assessed regional RC muscle activation patterns by means of intravoxel incoherent motion (IVIM) diffusion-weighted magnetic resonance imaging (MRI) after the execution of common clinical RC tests.

Methods: Ten healthy subjects (five males, five females) underwent three sessions of diffusion-weighted 3-T shoulder MRI before and after testing the supraspinatus (SSP, Jobe test, session 1), subscapularis (SSC, lift-off test, session 2, at least 1 week later), and infraspinatus muscle (ISP, external rotation test, session 3, another week later). IVIM parameters (perfusion fraction, f; pseudo-diffusion coefficient. D*; and their product, fD*) were measured in regions of interest placed in images of the SSP, SSC, ISP, and deltoid muscle. The Wilcoxon signed-rank test was used for group comparisons; p-values were adjusted using the Bonferroni correction.

Results: After all tests, fD* was significantly increased in the respective target muscles (SSP, SSC, or ISP; p ≤ 0.001). After SSP testing, an additional significant increase of fD* was observed in the deltoid, the SSC, and the ISP muscle (p < 0.001). After the SSC and ISP tests, no significant concomitant increase of any parameter was observed in the other RC muscles.

Conclusion: IVIM revealed varying activation patterns of RC muscles for different clinical RC tests. For SSP testing, coactivation of the deltoid and other RC muscles was observed, implying limited anatomical specificity, while the tests for the SSC and ISP specifically activated their respective target muscle.

Relevance statement: Following clinical RC tests, IVIM MRI revealed that SSP testing led to shoulder muscle coactivation, while the SSC and ISP tests specifically activated the target muscles.

Key points: In this study, intravoxel incoherent motion MRI depicted muscle activation following clinical rotator cuff tests. After supraspinatus testing, coactivation of surrounding shoulder girdle muscles was observed. Subscapularis and infraspinatus tests exhibited isolated activation of their respective target muscles.

Background: We prospectively assessed the reproducibility of a novel low-dose single-volume dynamic computed tomography (CT) myocardial blood flow measurement technique.

Methods: Thirty-four pairs of measurements were made under rest and stress conditions in 13 swine (54.3 ± 12.3 kg). One or two acquisition pairs were acquired in each animal with a 10-min delay between each pair. Contrast (370 mgI/mL; 0.5 mL/kg) and a diluted contrast/saline chaser (0.5 mL/kg; 30:70 contrast/saline) were injected peripherally at 5 mL/s, followed by bolus tracking and acquisition of a single volume scan (100 kVp; 200 mA) with a 320-slice CT scanner. Bolus tracking and single volume scan data were used to derive perfusion in mL/min/g using a first-pass analysis model; the coronary perfusion territories of the left anterior descending (LAD), left circumflex (LCx), and right coronary artery (RCA) were automatically assigned using a previously validated minimum-cost path technique. The reproducibility of CT myocardial perfusion measurement within the LAD, LCx, RCA, and the whole myocardium was assessed via regression analysis. The average CT dose index (CTDI) of perfusion measurement was recorded.

Results: The repeated first (P_myo1) and second (P_myo2) single-volume CT perfusion measurements were related by P_myo2 = 1.01P_myo1 - 0.03(ρ = 0.96; RMSE = 0.08 mL/min/g; RMSE = 0.07 mL/min/g) for the whole myocardium, and by P_reg2 = 0.86P_reg1 + 0.13(ρ = 0.87; RMSE = 0.31 mL/min/g; RMSE = 0.29 mL/min/g) for the LAD, LCx, and RCA perfusion territories. The average CTDI of the single-volume CT perfusion measurement was 10.5 mGy.

Conclusion: The single-volume CT blood flow measurement technique provides reproducible low-dose myocardial perfusion measurement using only bolus tracking data and a single whole-heart volume scan.

Relevance statement: The single-volume CT blood flow measurement technique is a noninvasive tool that reproducibly measures myocardial perfusion and provides coronary CT angiograms, allowing for simultaneous anatomic-physiologic assessment of myocardial ischemia.

Key points: A low-dose single-volume dynamic CT myocardial blood flow measurement technique is reproducible. Motion misregistration artifacts are eliminated using a single-volume CT perfusion technique. This technique enables combined anatomic-physiologic assessment of coronary artery disease.