Detection and severity quantification of pulmonary embolism with 3D CT data using an automated deep learning-based artificial solution.

PURPOSE: The purpose of this study was to propose a deep learning-based approach to detect pulmonary embolism and quantify its severity using the Qanadli score and the right-to-left ventricle diameter (RV/LV) ratio on three-dimensional (3D) computed tomography pulmonary angiography (CTPA) examinations with limited annotations. MATERIALS AND METHODS: Using a database of 3D CTPA examinations of 1268 patients with image-level annotations, and two other public datasets of CTPA examinations from 91 (CAD-PE) and 35 (FUME-PE) patients with pixel-level annotations, a pipeline consisting of: (i), detecting blood clots; (ii), performing PE-positive versus negative classification; (iii), estimating the Qanadli score; and (iv), predicting RV/LV diameter ratio was followed. The method was evaluated on a test set including 378 patients. The performance of PE classification and severity quantification was quantitatively assessed using an area under the curve (AUC) analysis for PE classification and a coefficient of determination (R²) for the Qanadli score and the RV/LV diameter ratio. RESULTS: Quantitative evaluation led to an overall AUC of 0.870 (95% confidence interval [CI]: 0.850-0.900) for PE classification task on the training set and an AUC of 0.852 (95% CI: 0.810-0.890) on the test set. Regression analysis yielded R² value of 0.717 (95% CI: 0.668-0.760) and of 0.723 (95% CI: 0.668-0.766) for the Qanadli score and the RV/LV diameter ratio estimation, respectively on the test set. CONCLUSION: This study shows the feasibility of utilizing AI-based assistance tools in detecting blood clots and estimating PE severity scores with 3D CTPA examinations. This is achieved by leveraging blood clots and cardiac segmentations. Further studies are needed to assess the effectiveness of these tools in clinical practice.

Applicability of Bosniak 2019 for renal mass classification on portal venous phase at the era of spectral CT imaging using rapid kV-switching dual-energy CT.

OBJECTIVES: To evaluate the applicability of Bosniak 2019 criteria on a monophasic portal venous phase using rapid kilovoltage-switching DECT (rsDECT). MATERIALS AND METHODS: One hundred twenty-seven renal masses assessed on rsDECT were included, classified according to Bosniak 2019 classification using MRI as the reference standard. Using the portal venous phase, virtual monochromatic images at 40, 50, and 77 keV; virtual unenhanced (VUE) images; and iodine map images were reconstructed. Changes in attenuation values between VUE and 40 keV, 50 keV, and 77 keV measurements were computed and respectively defined as ∆HU40keV, ∆HU50keV, and ∆HU77keV. The values of ∆HU40keV, ∆HU50keV, and ∆HU77keV thresholds providing the optimal diagnostic performance for the detection of internal enhancement were determined using Youden index. RESULTS: Population study included 25 solid renal masses (25/127, 20%) and 102 cystic renal masses (102/127, 80%). To differentiate solid to cystic masses, the specificity of the predefined 20 HU threshold reached 88% (95%CI: 82, 93) using ∆HU77keV and 21% (95%CI: 15, 28) using ∆HU40keV. The estimated optimal threshold of attenuation change was 19 HU on ∆HU77keV, 69 HU on ∆HU50eV, and 111 HU on ∆HU40eV. The rsDECT classification was highly similar to that of MRI for solid renal masses (23/25, 92%) and for Bosniak 1 masses (62/66, 94%). However, 2 hyperattenuating Bosniak 2 renal masses (2/26, 8%) were classified as solid renal masses on rsDECT. CONCLUSION: DECT is a promising tool for Bosniak classification particularly to differentiate solid from Bosniak I-II cyst. However, known enhancement thresholds must be adapted especially to the energy level of virtual monochromatic reconstructions. CLINICAL STATEMENT: DECT is a promising tool for Bosniak classification; however, known enhancement thresholds must be adapted according to the types of reconstructions used and especially to the energy level of virtual monochromatic reconstructions. KEY POINTS: • To differentiate solid to cystic renal masses, predefined 20 HU threshold had a poor specificity using 40 keV virtual monochromatic images. • Most of Bosniak 1 masses according to MRI were also classified as Bosniak 1 on rapid kV-switching dual-energy CT (rsDECT). • Bosniak 2 hyperattenuating renal cysts mimicked solid lesion on rsDECT.

Glomerular Filtration Rate Measured Based on Iomeprol Clearance Assessed at CT Urography in Living Kidney Donor Candidates.

Background Estimating glomerular filtration rate (GFR) from serum creatinine can be inaccurate, and current procedures for measuring GFR are time-consuming and cumbersome. Purpose To develop a method for measuring GFR based on iomeprol clearance assessed at CT urography in kidney donor candidates and compare this with iohexol clearance (reference standard for measuring GFR). Materials and Methods This cross-sectional retrospective study included data from kidney donor candidates who underwent both iohexol clearance and CT urography between July 2016 and October 2022. CT-measured GFR was calculated as the iomeprol excretion rate in the urinary system between arterial and excretory phases (Hounsfield units times milliliters per minute) divided by a surrogate for serum iomeprol concentration in the aorta at the midpoint (in Hounsfield units). Performance of CT-measured GFR was assessed with use of mean bias (mean difference between CT-measured GFR and iohexol clearance), precision (the distance between quartile 1 and quartile 3 of the bias [quartile 3 minus quartile 1], with a small value indicating high precision), and accuracy (percentage of CT-measured GFR values falling within 10%, 20%, and 30% of iohexol clearance values). Intraobserver agreement was assessed for 30 randomly selected individuals with the Lin concordance correlation coefficient. Results A total of 75 kidney donor candidates were included (mean age, 51 years ± 13 [SD]; 45 female). The CT-measured GFR was unbiased (1.1 mL/min/1.73 m2 [95% CI: -1.9, 4.1]) and highly precise (16.2 mL/min/1.73 m2 [quartiles 1 to 3, -6.6 to 9.6]). The accuracy of CT-measured GFR within 10%, 20%, and 30% was 61.3% (95% CI: 50.3, 72.4), 88.0% (95% CI: 80.7, 95.4), and 100%, respectively. Concordance between CT-based GFR measurements taken 2 months apart was almost perfect (correlation coefficient, 0.99 [95% CI: 0.98, 0.99]). Conclusion In living kidney donors, GFR measured based on iomeprol clearance assessed at CT urography showed good agreement with GFR measured based on iohexol clearance. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Davenport in this issue.

Safety and Efficacy of Percutaneous Liver Microwave Ablation Using a Fully Water-Cooled Choke Ring Antenna: First Multicenter Clinical Report.

INTRODUCTION: The safety and efficacy of a microwave ablation (MWA) system for the liver with novel technologies in field control, antenna cooling through the inner part of the choke ring, and dual temperature monitoring were evaluated in this multicenter retrospective study. MATERIAL AND METHODS: Ablation characteristics and efficacy were assessed on follow-up imaging (computed tomography or magnetic resonance imaging). Safety was evaluated according to CTCAE classification. RESULTS: Eighty-seven liver tumors (65 metastases and 22 hepatocellular carcinomas) measuring 17.8 ± 7.9 mm were treated in 68 patients. Ablation zones measured 35.6 ± 11 mm in longest diameter. The coefficients of variation of the longest and shortest ablation diameters were 30.1% and 26.4%, respectively. The mean sphericity index of the ablation zone was 0.78 ± 0.14. Seventy-one ablations (82%) had a sphericity index above 0.66. At 1 month, all tumors demonstrated complete ablation with margins of 0-5 mm, 5-10 mm, and greater than 10 mm achieved in 22%, 46%, and 31% of tumors, respectively. After a median follow-up of 10 months, local tumor control was achieved in 84.7% of treated tumors after a single ablation and in 86% after one patient received a second ablation. One grade 3 complication (stress ulcer) occurred, but was unrelated to the procedure. Ablation zone size and geometry in this clinical study were in accordance with previously reported in vivo preclinical findings. CONCLUSION: Promising results were reported for this MWA device. The high spherical index, reproducibility, and predictability of the resulting treatment zones translated to a high percentage of adequate safety margins, providing good local control rate.

Detection and quantification of pulmonary embolism with artificial intelligence: The SFR 2022 artificial intelligence data challenge.

PURPOSE: In 2022, the French Society of Radiology together with the French Society of Thoracic Imaging and CentraleSupelec organized their 13th data challenge. The aim was to aid in the diagnosis of pulmonary embolism, by identifying the presence of pulmonary embolism and by estimating the ratio between right and left ventricular (RV/LV) diameters, and an arterial obstruction index (Qanadli's score) using artificial intelligence. MATERIALS AND METHODS: The data challenge was composed of three tasks: the detection of pulmonary embolism, the RV/LV diameter ratio, and Qanadli's score. Sixteen centers all over France participated in the inclusion of the cases. A health data hosting certified web platform was established to facilitate the inclusion process of the anonymized CT examinations in compliance with general data protection regulation. CT pulmonary angiography images were collected. Each center provided the CT examinations with their annotations. A randomization process was established to pool the scans from different centers. Each team was required to have at least a radiologist, a data scientist, and an engineer. Data were provided in three batches to the teams, two for training and one for evaluation. The evaluation of the results was determined to rank the participants on the three tasks. RESULTS: A total of 1268 CT examinations were collected from the 16 centers following the inclusion criteria. The dataset was split into three batches of 310, 580 and 378 C T examinations provided to the participants respectively on September 5, 2022, October 7, 2022 and October 9, 2022. Seventy percent of the data from each center were used for training, and 30% for the evaluation. Seven teams with a total of 48 participants including data scientists, researchers, radiologists and engineering students were registered for participation. The metrics chosen for evaluation included areas under receiver operating characteristic curves, specificity and sensitivity for the classification task, and the coefficient of determination r2 for the regression tasks. The winning team achieved an overall score of 0.784. CONCLUSION: This multicenter study suggests that the use of artificial intelligence for the diagnosis of pulmonary embolism is possible on real data. Moreover, providing quantitative measures is mandatory for the interpretability of the results, and is of great aid to the radiologists especially in emergency settings.

Cognitive change in breast cancer patients up to 2 years after diagnosis.

BACKGROUND: Using the large nationwide French, national, multicenter, prospective cancer and toxicities (CANTO) cohort, we assessed cognitive functioning change after cancer treatments in a subgroup of breast cancer (BC) patients. METHODS: We included patients with newly diagnosed invasive stage I-III BC enrolled in the CANTO substudy focused on cognitive evaluation and healthy control women matched for age and education. Episodic and working memory, executive functions, processing speed, attention, self-report cognitive difficulties (SRCD), fatigue, anxiety and depression were assessed with neuropsychological tests and self-report questionnaires before treatment (baseline) and approximately 1 (year 1) and 2 years (year 2) after diagnosis. We used linear mixed models to study changes in cognition and tested the effect of adjuvant chemotherapy. RESULTS: We studied 276 localized BC patients (62% chemotherapy) compared with 135 healthy controls (HC). After adjustment, patients had lower baseline working memory, processing speed, and attention scores than HC (P ≤ .001), and the difference remained statistically significant over follow-up for working memory and processing speed. Executive function scores were similar between groups at baseline but decreased at year 1 among patients compared with HC (Pchange = .006). This decrease in chemotherapy patients was statistically significant compared with HC scores (Pchange < .001). After adjustment, SRCD were similar between BC patients and HC at baseline but increased in patients after treatment at year 1 (Pchange = .002). CONCLUSIONS: Cognitive difficulties are an important concern in BC patients, starting at diagnosis. Cancer treatments induce executive function decline and SRCD, which decrease over follow-up.

A Comparison of 18F-DCFPyL, 18F-NaF, and 18F-FDG PET/CT in a Prospective Cohort of Men with Metastatic Prostate Cancer.

18F-DCFPyL, 18F-sodium fluoride (18F-NaF), and 18F-FDG PET/CT were compared in a prospective cohort of men with metastatic prostate cancer (PCa). Methods: Sixty-seven men (group 1) with documented metastatic PCa underwent 18F-DCFPyL and 18F-NaF PET/CT and a subgroup of 30 men (group 2) underwent additional imaging with 18F-FDG PET/CT. The tracers were compared for their detection rates, imaging concordance, associations with prostate-specific antigen (PSA), treatment at the time of imaging, and castration status. Results: Overall, 61 men had metastatic disease detected on one or more scans, and 6 men had no disease uptake on any of the PET/CT scans (and were subsequently excluded from the analysis). In group 1, 18F-NaF detected significantly more metastatic lesions than 18F-DCFPyL (median of 3 lesions vs. 2, P = 0.001) even after eliminating benign causes of 18F-NaF uptake. This difference was particularly clear for men receiving treatment (P = 0.005) or who were castration-resistant (P = 0.014). The median percentage of bone lesions that were concordant on 18F-DCFPyL and 18F-NaF was 50%. In group 2, 18F-DCFPyL detected more lesions than 18F-FDG (median of 5 lesions vs. 2, P = 0.0003), regardless of PSA level, castration status, or treatment. The median percentage of lesions that were concordant on 18F-DCFPyL and 18F-FDG was 22.2%. This percentage was slightly higher for castration-resistant than castration-sensitive men (P = 0.048). Conclusion:18F-DCFPyL PET/CT is the most versatile of the 3 PET agents for metastatic PCa; however, 18F-NaF detects more bone metastases. Imaging reveals substantial tumor heterogeneity with only 50% concordance between 18F-DCFPyL and 18F-NaF and 22% concordance for 18F-DCFPyL and 18F-FDG. These findings indicate considerable phenotypic differences among metastatic lesions.

Generalized chest CT and lab curves throughout the course of COVID-19.

A better understanding of temporal relationships between chest CT and labs may provide a reference for disease severity over the disease course. Generalized curves of lung opacity volume and density over time can be used as standardized references from well before symptoms develop to over a month after recovery, when residual lung opacities remain. 739 patients with COVID-19 underwent CT and RT-PCR in an outbreak setting between January 21st and April 12th, 2020. 29 of 739 patients had serial exams (121 CTs and 279 laboratory measurements) over 50 ± 16 days, with an average of 4.2 sequential CTs each. Sequential volumes of total lung, overall opacity and opacity subtypes (ground glass opacity [GGO] and consolidation) were extracted using deep learning and manual segmentation. Generalized temporal curves of CT and laboratory measurements were correlated. Lung opacities appeared 3.4 ± 2.2 days prior to symptom onset. Opacity peaked 1 day after symptom onset. GGO onset was earlier and resolved later than consolidation. Lactate dehydrogenase, and C-reactive protein peaked earlier than procalcitonin and leukopenia. The temporal relationships of quantitative CT features and clinical labs have distinctive patterns and peaks in relation to symptom onset, which may inform early clinical course in patients with mild COVID-19 pneumonia, or may shed light upon chronic lung effects or mechanisms of medical countermeasures in clinical trials.

Comparison of Smartphone Augmented Reality, Smartglasses Augmented Reality, and 3D CBCT-guided Fluoroscopy Navigation for Percutaneous Needle Insertion: A Phantom Study.

PURPOSE: To compare needle placement performance using an augmented reality (AR) navigation platform implemented on smartphone or smartglasses devices to that of CBCT-guided fluoroscopy in a phantom. MATERIALS AND METHODS: An AR application was developed to display a planned percutaneous needle trajectory on the smartphone (iPhone7) and smartglasses (HoloLens1) devices in real time. Two AR-guided needle placement systems and CBCT-guided fluoroscopy with navigation software (XperGuide, Philips) were compared using an anthropomorphic phantom (CIRS, Norfolk, VA). Six interventional radiologists each performed 18 independent needle placements using smartphone (n = 6), smartglasses (n = 6), and XperGuide (n = 6) guidance. Placement error was defined as the distance from the needle tip to the target center. Placement time was recorded. For XperGuide, dose-area product (DAP, mGy*cm2) and fluoroscopy time (sec) were recorded. Statistical comparisons were made using a two-way repeated measures ANOVA. RESULTS: The placement error using the smartphone, smartglasses, or XperGuide was similar (3.98 ± 1.68 mm, 5.18 ± 3.84 mm, 4.13 ± 2.38 mm, respectively, p = 0.11). Compared to CBCT-guided fluoroscopy, the smartphone and smartglasses reduced placement time by 38% (p = 0.02) and 55% (p = 0.001), respectively. The DAP for insertion using XperGuide was 3086 ± 2920 mGy*cm2, and no intra-procedural radiation was required for augmented reality. CONCLUSIONS: Smartphone- and smartglasses-based augmented reality reduced needle placement time and radiation exposure while maintaining placement accuracy compared to a clinically validated needle navigation platform.

Determination of disease severity in COVID-19 patients using deep learning in chest X-ray images.

PURPOSE: Chest X-ray plays a key role in diagnosis and management of COVID-19 patients and imaging features associated with clinical elements may assist with the development or validation of automated image analysis tools. We aimed to identify associations between clinical and radiographic features as well as to assess the feasibility of deep learning applied to chest X-rays in the setting of an acute COVID-19 outbreak. METHODS: A retrospective study of X-rays, clinical, and laboratory data was performed from 48 SARS-CoV-2 RT-PCR positive patients (age 60±17 years, 15 women) between February 22 and March 6, 2020 from a tertiary care hospital in Milan, Italy. Sixty-five chest X-rays were reviewed by two radiologists for alveolar and interstitial opacities and classified by severity on a scale from 0 to 3. Clinical factors (age, symptoms, comorbidities) were investigated for association with opacity severity and also with placement of central line or endotracheal tube. Deep learning models were then trained for two tasks: lung segmentation and opacity detection. Imaging characteristics were compared to clinical datapoints using the unpaired student's t-test or Mann-Whitney U test. Cohen's kappa analysis was used to evaluate the concordance of deep learning to conventional radiologist interpretation. RESULTS: Fifty-six percent of patients presented with alveolar opacities, 73% had interstitial opacities, and 23% had normal X-rays. The presence of alveolar or interstitial opacities was statistically correlated with age (P = 0.008) and comorbidities (P = 0.005). The extent of alveolar or interstitial opacities on baseline X-ray was significantly associated with the presence of endotracheal tube (P = 0.0008 and P = 0.049) or central line (P = 0.003 and P = 0.007). In comparison to human interpretation, the deep learning model achieved a kappa concordance of 0.51 for alveolar opacities and 0.71 for interstitial opacities. CONCLUSION: Chest X-ray analysis in an acute COVID-19 outbreak showed that the severity of opacities was associated with advanced age, comorbidities, as well as acuity of care. Artificial intelligence tools based upon deep learning of COVID-19 chest X-rays are feasible in the acute outbreak setting.

CT and clinical assessment in asymptomatic and pre-symptomatic patients with early SARS-CoV-2 in outbreak settings.

OBJECTIVES: The early infection dynamics of patients with SARS-CoV-2 are not well understood. We aimed to investigate and characterize associations between clinical, laboratory, and imaging features of asymptomatic and pre-symptomatic patients with SARS-CoV-2. METHODS: Seventy-four patients with RT-PCR-proven SARS-CoV-2 infection were asymptomatic at presentation. All were retrospectively identified from 825 patients with chest CT scans and positive RT-PCR following exposure or travel risks in outbreak settings in Japan and China. CTs were obtained for every patient within a day of admission and were reviewed for infiltrate subtypes and percent with assistance from a deep learning tool. Correlations of clinical, laboratory, and imaging features were analyzed and comparisons were performed using univariate and multivariate logistic regression. RESULTS: Forty-eight of 74 (65%) initially asymptomatic patients had CT infiltrates that pre-dated symptom onset by 3.8 days. The most common CT infiltrates were ground glass opacities (45/48; 94%) and consolidation (22/48; 46%). Patient body temperature (p < 0.01), CRP (p < 0.01), and KL-6 (p = 0.02) were associated with the presence of CT infiltrates. Infiltrate volume (p = 0.01), percent lung involvement (p = 0.01), and consolidation (p = 0.043) were associated with subsequent development of symptoms. CONCLUSIONS: COVID-19 CT infiltrates pre-dated symptoms in two-thirds of patients. Body temperature elevation and laboratory evaluations may identify asymptomatic patients with SARS-CoV-2 CT infiltrates at presentation, and the characteristics of CT infiltrates could help identify asymptomatic SARS-CoV-2 patients who subsequently develop symptoms. The role of chest CT in COVID-19 may be illuminated by a better understanding of CT infiltrates in patients with early disease or SARS-CoV-2 exposure. KEY POINTS: • Forty-eight of 74 (65%) pre-selected asymptomatic patients with SARS-CoV-2 had abnormal chest CT findings. • CT infiltrates pre-dated symptom onset by 3.8 days (range 1-5). • KL-6, CRP, and elevated body temperature identified patients with CT infiltrates. Higher infiltrate volume, percent lung involvement, and pulmonary consolidation identified patients who developed symptoms.

Artificial intelligence for the detection of COVID-19 pneumonia on chest CT using multinational datasets.

Chest CT is emerging as a valuable diagnostic tool for clinical management of COVID-19 associated lung disease. Artificial intelligence (AI) has the potential to aid in rapid evaluation of CT scans for differentiation of COVID-19 findings from other clinical entities. Here we show that a series of deep learning algorithms, trained in a diverse multinational cohort of 1280 patients to localize parietal pleura/lung parenchyma followed by classification of COVID-19 pneumonia, can achieve up to 90.8% accuracy, with 84% sensitivity and 93% specificity, as evaluated in an independent test set (not included in training and validation) of 1337 patients. Normal controls included chest CTs from oncology, emergency, and pneumonia-related indications. The false positive rate in 140 patients with laboratory confirmed other (non COVID-19) pneumonias was 10%. AI-based algorithms can readily identify CT scans with COVID-19 associated pneumonia, as well as distinguish non-COVID related pneumonias with high specificity in diverse patient populations.

Cognitive Impairment in Patients with Breast Cancer before Surgery: Results from a CANTO Cohort Subgroup.

BACKGROUND: Twenty to 30% of patients with breast cancer have cognitive impairment after surgery and before adjuvant treatment, but very few studies have focused on cognition before any treatment. This study used a subgroup of women with newly diagnosed breast cancer from the French cancer and toxicities (CANTO) cohort to describe cognition before any treatment in comparison with a group of healthy controls (HC). METHODS: Cognitive assessment was performed before any breast cancer treatment (surgery or neoadjuvant treatment) on women with newly diagnosed invasive stage I-III breast cancer and HCs. Objective cognitive performance, cognitive complaints, anxiety, depression, and fatigue were assessed. Objective cognitive impairment was defined according to International Cognition and Cancer Task Force recommendations. RESULTS: Of the 264 included patients with breast cancer (54 ± 11 years) and 132 age-matched HCs (53 ± 9 years), overall objective cognitive impairment was observed in 28% of patients with breast cancer and 8% of HCs (P < 0.001). Cognitive complaints were reported by 24% of patients versus 12% of HCs (P < 0.01). Patients reported significantly more anxiety and emotional and cognitive fatigue than HCs (P < 0.01). After adjustment, significantly more patients with breast cancer had overall objective cognitive impairment than HCs [OR = 3.01; 95% confidence interval (CI): 1.31-6.88] without significant difference between groups for cognitive complaints (OR = 1.38; 95% CI: 0.65-2.92). Cognitive complaints were positively associated with fatigue (OR = 1.03; 95% CI: 1.02-1.05). CONCLUSIONS: In this prospective study, compared with HCs, patients with localized breast cancer had more objective cognitive impairment before any treatment. Cognitive complaints were mostly related to fatigue. IMPACT: Baseline assessment before treatment is important to assess the impact of each cancer treatment on cognition.

CBCT-Based Image Guidance for Percutaneous Access: Electromagnetic Navigation Versus 3D Image Fusion with Fluoroscopy Versus Combination of Both Technologies-A Phantom Study.

PURPOSE: We set out to compare three types of three-dimensional CBCT-based imaging guidance modalities in a phantom study: image fusion with fluoroscopy (IF), electromagnetic navigation (EMN) and the association of both technologies (CEMNIF). MATERIALS AND METHODS: Four targets with a median diameter of 11 mm [first quartile (Q1): 10; third quartile (Q3): 12] with acute angle access (z-axis < 45°) and four targets of 10 mm [8-15] with large angle access (z-axis > 45°) were defined on an abdominal phantom (CIRS, Meditest, Tabuteau, France). Acute angle access targets were punctured using IF, EMN or CEMNIF and large angle access targets with EMN by four operators with various experiences. Efficacy (target reached), accuracy (distance between needle tip and target center), procedure time, radiation exposure and reproducibility were explored and compared. RESULTS: All targets were reached (100% efficacy) by all operators. For targets with acute angle access, procedure times (EMN: 265 s [236-360], IF: 292 s [260-345], CEMNIF: 320 s [240-333]) and accuracy (EMN: 3 mm [2-5], IF: 2 mm [1-3], CEMNIF: 3 mm [2-4]) were similar. Radiation exposure (EMN: 0; IF: 708 mGy.cm2 [599-1128]; CEMNIF: 51 mGy.cm2 [15-150]; p < 0.001) was significantly higher with IF than with CEMNIF and EMN. For targets with large angle access, procedure times (EMN: 345 s [259-457], CEMNIF: 425 s [340-473]; p = 0.01) and radiation exposure (EMN: 0, CEMIF: 159 mGy.cm2 [39-316]; p < 0.001) were significantly lower with EMN but with lower accuracy (EMN: 4 mm [4-6] and CEMNIF: 4 mm [3, 4]; p = 0.01). The operator's experience did not impact the tested parameters regardless of the technique. CONCLUSION: In this phantom study, EMN was not limited to acute angle targets. Efficacy and accuracy of puncture for acute angle access targets with EMN, IF or CEMNIF were similar. CEMNIF is more accurate for large angle access targets at the cost of a slightly higher procedure time and radiation exposure.

Influence of thoracolumbar fascia stretching on lumbar back muscle stiffness: A supersonic shear wave elastography approach.

The lumbar paraspinal muscle compartment (PMC) is a stabilizing system of the spine whose efficiency depends on its elastic properties, which may be quantifiable by supersonic shear wave elastography (SWE). The thoracolumbar fascia (TLF) encapsulates the lumbar paraspinal muscles (LPM) and creates a PMC. Tensioning of the TLF via the stretching of the latissimus dorsi is supposed to increase stiffness within the PMC. The aims of this study were (1) to test the reliability of SWE in the multifidus and the erector spinae (ES) in prone and sited position; (2) to investigate the role of the tensioning of the pTLF, via stretching of the latissimus dorsi (LD), on LPM stiffness. Stiffness of ES and multifidus was measured using SWE at L3-L4 in procubitus and seated position in 15 participants. Stretching of LD was performed with arm elevation. Parametric paired tests, multiple analyses of variance, and intraclass correlation were used for statistical analysis. Reliability estimates were fair to excellent. Reliability was greater in ES than the multifidus, greater in seated position than during rest. Stiffness was greater in the ES than in multifidus, and in seated position than at rest. Tensioning of the TLF via LD stretching did not generate significant LPM stiffness changes. SWE is a reliable tool for assessing stiffness in the LPM. Reliability of SWE protocols is improved during seated position. Tensioning of the TLF via LD stretching did not influence LPM stiffness. Clin. Anat. 32:73-80, 2019. © 2018 Wiley Periodicals, Inc.