Objectives: The aim of this study was to quantify and compare fat fraction (FF) and muscle volume between patients with failed and intact rotator cuff (RC) repair as well as a control group with nonsurgical conservative treatment to define FF cutoff values for predicting the outcome of RC repair.
Materials and methods: Patients with full-thickness RC tears who received magnetic resonance imaging (MRI) before and after RC repair including a 2-point Dixon sequence were retrospectively screened. Patients with retear of 1 or more tendons diagnosed on MRI (Sugaya IV-V) were enrolled and matched to patients with intact RC repair (Sugaya I-II) and to a third group with conservatively treated RC tears. Two radiologists evaluated morphological features (Cofield, Patte, and Goutallier), as well as the integrity of the RC after repair (Sugaya). Fat fractions were calculated from the 2-point Dixon sequence, and the RC muscles were segmented semiautomatically to calculate FFs and volume for each muscle. Receiver operator characteristics curves were used to determine FF cutoff values that best predict RC retears.
Results: In total, 136 patients were enrolled, consisting of 3 groups: 41 patients had a failed RC repair (58 ± 7 years, 16 women), 50 patients matched into the intact RC repair group, and 45 patients were matched into the conservative treatment group. Receiver operator characteristics curves showed reliable preoperative FF cutoff values for predicting retears at 6.0% for the supraspinatus muscle (0.83 area under the curve [AUC]), 7.4% for the infraspinatus muscle (AUC 0.82), and 8.3% for the subscapularis muscle (0.94 AUC).
Conclusions: Preoperative quantitative FF calculated from 2-point Dixon MRI can be used to predict the risk of retear after arthroscopic RC repair with cutoff values between 6% and 8.3%.
Objectives: The aim of this study was to investigate potential benefits of ultra-high resolution (UHR) over standard resolution scan mode in ultra-low dose photon-counting detector CT (PCD-CT) of the lung.
Materials and methods: Six cadaveric specimens were examined with 5 dose settings using tin prefiltration, each in UHR (120 × 0.2 mm) and standard mode (144 × 0.4 mm), on a first-generation PCD-CT scanner. Image quality was evaluated quantitatively by noise comparisons in the trachea and both main bronchi. In addition, 16 readers (14 radiologists and 2 internal medicine physicians) independently completed a browser-based pairwise forced-choice comparison task for assessment of subjective image quality. The Kendall rank coefficient ( W ) was calculated to assess interrater agreement, and Pearson's correlation coefficient ( r ) was used to analyze the relationship between noise measurements and image quality rankings.
Results: Across all dose levels, image noise in UHR mode was lower than in standard mode for scan protocols matched by CTDI vol ( P < 0.001). UHR examinations exhibited noise levels comparable to the next higher dose setting in standard mode ( P ≥ 0.275). Subjective ranking of protocols based on 5760 pairwise tests showed high interrater agreement ( W = 0.99; P ≤ 0.001) with UHR images being preferred by readers in the majority of comparisons. Irrespective of scan mode, a substantial indirect correlation was observed between image noise and subjective image quality ranking ( r = -0.97; P ≤ 0.001).
Conclusions: In PCD-CT of the lung, UHR scan mode reduces image noise considerably over standard resolution acquisition. Originating from the smaller detector element size in fan direction, the small pixel effect allows for superior image quality in ultra-low dose examinations with considerable potential for radiation dose reduction.
Objectives: The aim of this study was to compare the detection rate of and reader confidence in 0.55 T knee magnetic resonance imaging (MRI) findings with 3 T knee MRI in patients with acute trauma and knee pain.
Materials and methods: In this prospective study, 0.55 T and 3 T knee MRI of 25 symptomatic patients (11 women; median age, 38 years) with suspected internal derangement of the knee was obtained in 1 setting. On the 0.55 T system, a commercially available deep learning image reconstruction algorithm was used (Deep Resolve Gain and Deep Resolve Sharp; Siemens Healthineers), which was not available on the 3 T system. Two board-certified radiologists reviewed all images independently and graded image quality parameters, noted MRI findings and their respective reporting confidence level for the presence or absence, as well as graded the bone, cartilage, meniscus, ligament, and tendon lesions. Image quality and reader confidence levels were compared ( P < 0.05 = significant), and clinical findings were correlated between 0.55 T and 3 T MRI by calculation of the intraclass correlation coefficient (ICC).
Results: Image quality was rated higher at 3 T compared with 0.55 T studies (each P ≤ 0.017). Agreement between 0.55 T and 3 T MRI for the detection and grading of bone marrow edema and fractures, ligament and tendon lesions, high-grade meniscus and cartilage lesions, Baker cysts, and joint effusions was perfect for both readers. Overall identification and grading of cartilage and meniscal lesions showed good agreement between high- and low-field MRI (each ICC > 0.76), with lower agreement for low-grade cartilage (ICC = 0.77) and meniscus lesions (ICC = 0.49). There was no difference in readers' confidence levels for reporting lesions of bone, ligaments, tendons, Baker cysts, and joint effusions between 0.55 T and 3 T (each P > 0.157). Reader reporting confidence was higher for cartilage and meniscal lesions at 3 T (each P < 0.041).
Conclusions: New-generation 0.55 T knee MRI, with deep learning-aided image reconstruction, allows for reliable detection and grading of joint lesions in symptomatic patients, but it showed limited accuracy and reader confidence for low-grade cartilage and meniscal lesions in comparison with 3 T MRI.
Objectives: The aim of this study was to investigate the prognostic value of 3-dimensional minimal ablative margin (MAM) quantified by intraprocedural versus initial follow-up computed tomography (CT) in predicting local tumor progression (LTP) after colorectal liver metastasis (CLM) thermal ablation.
Materials and methods: This single-institution, patient-clustered, tumor-based retrospective study included patients undergoing microwave and radiofrequency ablation between 2016 and 2021. Patients without intraprocedural and initial follow-up contrast-enhanced CT, residual tumors, or with follow-up less than 1 year without LTP were excluded. Minimal ablative margin was quantified by a biomechanical deformable image registration method with segmentations of CLMs on intraprocedural preablation CT and ablation zones on intraprocedural postablation and initial follow-up CT. Prognostic value of MAM to predict LTP was tested using area under the curve and competing-risk regression model.
Results: A total of 68 patients (mean age ± standard deviation, 57 ± 12 years; 43 men) with 133 CLMs were included. During a median follow-up of 30.3 months, LTP rate was 17% (22/133). The median volume of ablation zone was 27 mL and 16 mL segmented on intraprocedural and initial follow-up CT, respectively ( P < 0.001), with corresponding median MAM of 4.7 mm and 0 mm, respectively ( P < 0.001). The area under the curve was higher for MAM quantified on intraprocedural CT (0.89; 95% confidence interval [CI], 0.83-0.94) compared with initial follow-up CT (0.66; 95% CI, 0.54-0.76) in predicting 1-year LTP ( P < 0.001). An MAM of 0 mm on intraprocedural CT was an independent predictor of LTP with a subdistribution hazards ratio of 11.9 (95% CI, 4.9-28.9; P < 0.001), compared with 2.4 (95% CI, 0.9-6.0; P = 0.07) on initial follow-up CT.
Conclusions: Ablative margin quantified on intraprocedural CT significantly outperformed initial follow-up CT in predicting LTP and should be used for ablation endpoint assessment.
Background and aims: This study aims to compare the performance of first-generation dual-source photon-counting detector computed tomography (PCD-CT) to third-generation dual-source energy-integrating detector (EID-CT) regarding stent imaging in the femoral arterial runoff.
Methods: Continuous extracorporeal perfusion was established in 1 human cadaver using an inguinal and infragenicular access and peristaltic pump. Seven peripheral stents were implanted into both superior femoral arteries by means of percutaneous angioplasty. Radiation dose-equivalent CT angiographies (high-/medium-/low-dose: 10/5/3 mGy) with constant tube voltage of 120 kVp, matching iterative reconstruction algorithm levels, and convolution kernels were used both with PCD-CT and EID-CT. In-stent lumen visibility, luminal and in-stent attenuation as well as contrast-to-noise ratio (CNR) were assessed via region of interest and diameter measurements. Results were compared using analyses of variance and regression analyses.
Results: Maximum in-stent lumen visibility achieved with PCD-CT was 94.48% ± 2.62%. The PCD-CT protocol with the lowest lumen visibility (BV40: 78.93% ± 4.67%) performed equal to the EID-CT protocol with the best lumen visibility (BV59: 79.49% ± 2.64%, P > 0.999). Photon-counting detector CT yielded superior CNR compared with EID-CT regardless of kernel and dose level ( P < 0.001). Maximum CNR was 48.8 ± 17.4 in PCD-CT versus 31.28 ± 5.7 in EID-CT (both BV40, high-dose). The theoretical dose reduction potential of PCD-CT over EID-CT was established at 88% (BV40), 83% (BV48/49), and 73% (BV59/60), respectively. In-stent attenuation was not significantly different from luminal attenuation outside stents in any protocol.
Conclusions: With superior lumen visibility and CNR, PCD-CT allowed for noticeable dose reduction over EID-CT while maintaining image quality in a continuously perfused human cadaveric model.
Purpose: To develop and validate an artificial intelligence algorithm for the positioning assessment of tracheal tubes (TTs) and central venous catheters (CVCs) in supine chest radiographs (SCXRs) by using an algorithm approach allowing for adjustable definitions of intended device positioning.
Materials and methods: Positioning quality of CVCs and TTs is evaluated by spatially correlating the respective tip positions with anatomical structures. For CVC analysis, a configurable region of interest is defined to approximate the expected region of well-positioned CVC tips from segmentations of anatomical landmarks. The CVC/TT information is estimated by introducing a new multitask neural network architecture for jointly performing type/existence classification, course segmentation, and tip detection. Validation data consisted of 589 SCXRs that have been radiologically annotated for inserted TTs/CVCs, including an experts' categorical positioning assessment (reading 1). In-image positions of algorithm-detected TT/CVC tips could be corrected using a validation software tool (reading 2) that finally allowed for localization accuracy quantification. Algorithmic detection of images with misplaced devices (reading 1 as reference standard) was quantified by receiver operating characteristics.
Results: Supine chest radiographs were correctly classified according to inserted TTs/CVCs in 100%/98% of the cases, thereby with high accuracy in also spatially localizing the medical device tips: corrections less than 3 mm in >86% (TTs) and 77% (CVCs) of the cases. Chest radiographs with malpositioned devices were detected with area under the curves of >0.98 (TTs), >0.96 (CVCs with accidental vessel turnover), and >0.93 (also suboptimal CVC insertion length considered). The receiver operating characteristics limitations regarding CVC assessment were mainly caused by limitations of the applied CXR position definitions (region of interest derived from anatomical landmarks), not by algorithmic spatial detection inaccuracies.
Conclusions: The TT and CVC tips were accurately localized in SCXRs by the presented algorithms, but triaging applications for CVC positioning assessment still suffer from the vague definition of optimal CXR positioning. Our algorithm, however, allows for an adjustment of these criteria, theoretically enabling them to meet user-specific or patient subgroups requirements. Besides CVC tip analysis, future work should also include specific course analysis for accidental vessel turnover detection.
Background: Gadolinium-based contrast agents (GBCAs) are applied to enhance magnetic resonance imaging. Gadolinium (Gd), a rare earth metal, is used in a chelated form when administered as GBCA to patients. There is an ongoing scientific debate about the clinical significance of Gd retention in tissues after administration of GBCAs. It is known that bone serves as Gd reservoir, but only sparse information on localization of Gd in bone is available.
Purpose: The aim of this study was to compare Gd tissue concentration and spatial distribution in femoral epiphysis and diaphysis 10 weeks after single-dose injection of linear and macrocyclic GBCAs in a large animal model.
Materials and methods: In this prospective animal study, Swiss-Alpine sheep (n = 36; age range, 4-10 years) received a single injection (0.1 mmol/kg) of macrocyclic (gadobutrol, gadoteridol, and gadoterate meglumine), linear (gadodiamide and gadobenate dimeglumine) GBCAs, or saline. Ten weeks after injection, sheep were killed, and femur heads and shafts were harvested. Gadolinium spatial distribution was determined in 1 sample of each treatment group by laser ablation-inductively coupled plasma-mass spectrometry. All bone specimens were analyzed histopathologically.
Results: Injection of GBCAs in female Swiss-Alpine sheep (n = 36) resulted in Gd localization at the endosteal and periosteal surface and in a subset of GBCAs additionally at the cement lines and the bone cartilage junction. No histopathological alterations were observed in the investigated tissue specimens.
Conclusions: Ten weeks after single injection of a clinically relevant dose in adult sheep, both linear species of GBCA resulted in considerably higher accumulation than macrocyclic GBCAs. Gadolinium deposits were restricted to distinct bone and cartilage compartments, such as in bone linings, cement lines, and bone cartilage junctions. Tissue histology remained unaffected.
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