Prognostic relevance of radiological findings on early postoperative MRI for 187 consecutive glioblastoma patients receiving standard therapy

Several prognostic factors are known to influence survival for patients treated with IDH-wildtype glioblastoma, but unknown factors may remain. We aimed to investigate the prognostic implications of early postoperative MRI findings. A total of 187 glioblastoma patients treated with standard therapy were consecutively included. Patients either underwent a biopsy or surgery followed by an early postoperative MRI. Progression-free survival (PFS) and overall survival (OS) were analysed for known prognostic factors and MRI-derived candidate factors: resection status as defined by the response assessment in neuro-oncology (RANO)-working group (no contrast-enhancing residual tumour, non-measurable contrast-enhancing residual tumour, or measurable contrast-enhancing residual tumour) with biopsy as reference, contrast enhancement patterns (no enhancement, thin linear, thick linear, diffuse, nodular), and the presence of distant tumours. In the multivariate analysis, patients with no contrast-enhancing residual tumour or non-measurable contrast-enhancing residual tumour on the early postoperative MRI displayed a significantly improved progression-free survival compared with patients receiving only a biopsy. Only patients with non-measurable contrast-enhancing residual tumour showed improved overall survival in the multivariate analysis. Contrast enhancement patterns were not associated with survival. The presence of distant tumours was significantly associated with both poor progression-free survival and overall survival and should be considered incorporated into prognostic models.

Multimodality Imaging in Cranial Giant Cell Arteritis: First Experience with High-Resolution T1-Weighted 3D Black Blood without Contrast Enhancement Magnetic Resonance Imaging

In order to support or refute the clinical suspicion of cranial giant cell arteritis (GCA), a supplemental imaging modality is often required. High-resolution black blood Magnetic Resonance Imaging (BB MRI) techniques with contrast enhancement can visualize artery wall inflammation in GCA. We compared findings on BB MRI without contrast enhancement with findings on 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography/low-dose computed tomography (2-[18F]FDG PET/CT) in ten patients suspected of having GCA and in five control subjects who had a 2-[18F]FDG PET/CT performed as a routine control for malignant melanoma. BB MRI was consistent with 2-[18F]FDG PET/CT in 10 out of 10 cases in the group with suspected GCA. In four out of five cases in the control group, the BB MRI was consistent with 2-[18F]FDG PET/CT. In this small population, BB MRI without contrast enhancement shows promising performance in the diagnosis of GCA, and might be an applicable imaging modality in patients.

An Automatic DWI/FLAIR Mismatch Assessment of Stroke Patients

DWI/FLAIR mismatch assessment for ischemic stroke patients shows promising results in determining if patients are eligible for recombinant tissue-type plasminogen activator (r-tPA) treatment. However, the mismatch criteria suffer from two major issues: binary classification of a non-binary problem and the subjectiveness of the assessor. In this article, we present a simple automatic method for segmenting stroke-related parenchymal hyperintensities on FLAIR, allowing for an automatic and continuous DWI/FLAIR mismatch assessment. We further show that our method's segmentations have comparable inter-rater agreement (DICE 0.820, SD 0.12) compared to that of two neuro-radiologists (DICE 0.856, SD 0.07), that our method appears robust to hyper-parameter choices (suggesting good generalizability), and lastly, that our methods continuous DWI/FLAIR mismatch assessment correlates to mismatch assessments made for a cohort of wake-up stroke patients at hospital submission. The proposed method shows promising results in automating the segmentation of parenchymal hyperintensity within ischemic stroke lesions and could help reduce inter-observer variability of DWI/FLAIR mismatch assessment performed in clinical environments as well as offer a continuous assessment instead of the current binary one.

Prediction of shunt response in idiopathic normal pressure hydrocephalus by combined lumbar infusion test and preoperative imaging scoring

BACKGROUND AND PURPOSE

Idiopathic normal pressure hydrocephalus (iNPH) is a potentially treatable disorder, but prognostic tests or biomarkers are lacking. The aim was to study the predictive power of clinical, neuroimaging and lumbar infusion test parameters (resistance to outflow Rout , cardiac-related pulse amplitude PA and the PA to intracranial pressure ICP ratio).

METHODS

In all, 127 patients diagnosed with iNPH who had a lumbar infusion test, a subsequent ventriculo-peritoneal shunt operation and at least 2 months of postoperative follow-up were retrospectively included. Preoperative magnetic resonance images were visually scored for NPH features using the iNPH Radscale. Preoperative and postoperative assessment was performed using cognitive testing, as well as gait and incontinence scales.

RESULTS

At follow-up (7.4 months, range 2-20 months), an overall positive response was seen in 82% of the patients. Gait was more severely impaired at baseline in responders compared to non-responders. The iNPH Radscale score was borderline significantly higher in responders compared with non-responders, whereas no significant differences in infusion test parameters were seen between responders and non-responders. Infusion test parameters performed modestly with high positive (75%-92%) but low negative (17%-23%) predictive values. Although not significant, PA and PA/ICP seemed to perform better than Rout , and the odds ratio for shunt response seemed to increase in patients with higher PA/ICP, especially in patients with lower iNPH Radscale scores.

CONCLUSION

Although only indicative, lumbar infusion test results increased the likelihood of a positive shunt outcome. Pulse amplitude measures showed promising results that should be further explored in prospective studies.

Artificial Intelligence for Automated DWI/FLAIR Mismatch Assessment on Magnetic Resonance Imaging in Stroke: A Systematic Review

We conducted this Systematic Review to create an overview of the currently existing Artificial Intelligence (AI) methods for Magnetic Resonance Diffusion-Weighted Imaging (DWI)/Fluid-Attenuated Inversion Recovery (FLAIR)-mismatch assessment and to determine how well DWI/FLAIR mismatch algorithms perform compared to domain experts. We searched PubMed Medline, Ovid Embase, Scopus, Web of Science, Cochrane, and IEEE Xplore literature databases for relevant studies published between 1 January 2017 and 20 November 2022, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We assessed the included studies using the Quality Assessment of Diagnostic Accuracy Studies 2 tool. Five studies fit the scope of this review. The area under the curve ranged from 0.74 to 0.90. The sensitivity and specificity ranged from 0.70 to 0.85 and 0.74 to 0.84, respectively. Negative predictive value, positive predictive value, and accuracy ranged from 0.55 to 0.82, 0.74 to 0.91, and 0.73 to 0.83, respectively. In a binary classification of ±4.5 h from stroke onset, the surveyed AI methods performed equivalent to or even better than domain experts. However, using the relation between time since stroke onset (TSS) and increasing visibility of FLAIR hyperintensity lesions is not recommended for the determination of TSS within the first 4.5 h. An AI algorithm on DWI/FLAIR mismatch assessment focused on treatment eligibility, outcome prediction, and consideration of patient-specific data could potentially increase the proportion of stroke patients with unknown onset who could be treated with thrombolysis.

Performance and Agreement When Annotating Chest X-ray Text Reports—A Preliminary Step in the Development of a Deep Learning-Based Prioritization and Detection System

A chest X-ray report is a communicative tool and can be used as data for developing artificial intelligence-based decision support systems. For both, consistent understanding and labeling is important. Our aim was to investigate how readers would comprehend and annotate 200 chest X-ray reports. Reports written between 1 January 2015 and 11 March 2022 were selected based on search words. Annotators included three board-certified radiologists, two trained radiologists (physicians), two radiographers (radiological technicians), a non-radiological physician, and a medical student. Consensus labels by two or more of the experienced radiologists were considered “gold standard”. Matthew’s correlation coefficient (MCC) was calculated to assess annotation performance, and descriptive statistics were used to assess agreement between individual annotators and labels. The intermediate radiologist had the best correlation to “gold standard” (MCC 0.77). This was followed by the novice radiologist and medical student (MCC 0.71 for both), the novice radiographer (MCC 0.65), non-radiological physician (MCC 0.64), and experienced radiographer (MCC 0.57). Our findings showed that for developing an artificial intelligence-based support system, if trained radiologists are not available, annotations from non-radiological annotators with basic and general knowledge may be more aligned with radiologists compared to annotations from sub-specialized medical staff, if their sub-specialization is outside of diagnostic radiology.

Pseudo-Label Guided Image Synthesis for Semi-Supervised COVID-19 Pneumonia Infection Segmentation

Coronavirus disease 2019 (COVID-19) has become a severe global pandemic. Accurate pneumonia infection segmentation is important for assisting doctors in diagnosing COVID-19. Deep learning-based methods can be developed for automatic segmentation, but the lack of large-scale well-annotated COVID-19 training datasets may hinder their performance. Semi-supervised segmentation is a promising solution which explores large amounts of unlabelled data, while most existing methods focus on pseudo-label refinement. In this paper, we propose a new perspective on semi-supervised learning for COVID-19 pneumonia infection segmentation, namely pseudo-label guided image synthesis. The main idea is to keep the pseudo-labels and synthesize new images to match them. The synthetic image has the same COVID-19 infected regions as indicated in the pseudo-label, and the reference style extracted from the style code pool is added to make it more realistic. We introduce two representative methods by incorporating the synthetic images into model training, including single-stage Synthesis-Assisted Cross Pseudo Supervision (SA-CPS) and multi-stage Synthesis-Assisted Self-Training (SA-ST), which can work individually as well as cooperatively. Synthesis-assisted methods expand the training data with high-quality synthetic data, thus improving the segmentation performance. Extensive experiments on two COVID-19 CT datasets for segmenting the infections demonstrate our method is superior to existing schemes for semi-supervised segmentation, and achieves the state-of-the-art performance on both datasets. Code is available at: https://github.com/FeiLyu/SASSL.

Evaluation of the HD-GLIO Deep Learning Algorithm for Brain Tumour Segmentation on Postoperative MRI

In the context of brain tumour response assessment, deep learning-based three-dimensional (3D) tumour segmentation has shown potential to enter the routine radiological workflow. The purpose of the present study was to perform an external evaluation of a state-of-the-art deep learning 3D brain tumour segmentation algorithm (HD-GLIO) on an independent cohort of consecutive, post-operative patients. For 66 consecutive magnetic resonance imaging examinations, we compared delineations of contrast-enhancing (CE) tumour lesions and non-enhancing T2/FLAIR hyperintense abnormality (NE) lesions by the HD-GLIO algorithm and radiologists using Dice similarity coefficients (Dice). Volume agreement was assessed using concordance correlation coefficients (CCCs) and Bland-Altman plots. The algorithm performed very well regarding the segmentation of NE volumes (median Dice = 0.79) and CE tumour volumes larger than 1.0 cm³ (median Dice = 0.86). If considering all cases with CE tumour lesions, the performance dropped significantly (median Dice = 0.40). Volume agreement was excellent with CCCs of 0.997 (CE tumour volumes) and 0.922 (NE volumes). The findings have implications for the application of the HD-GLIO algorithm in the routine radiological workflow where small contrast-enhancing tumours will constitute a considerable share of the follow-up cases. Our study underlines that independent validations on clinical datasets are key to asserting the robustness of deep learning algorithms.

Inter- and Intra-Observer Agreement When Using a Diagnostic Labeling Scheme for Annotating Findings on Chest X-rays-An Early Step in the Development of a Deep Learning-Based Decision Support System

Consistent annotation of data is a prerequisite for the successful training and testing of artificial intelligence-based decision support systems in radiology. This can be obtained by standardizing terminology when annotating diagnostic images. The purpose of this study was to evaluate the annotation consistency among radiologists when using a novel diagnostic labeling scheme for chest X-rays. Six radiologists with experience ranging from one to sixteen years, annotated a set of 100 fully anonymized chest X-rays. The blinded radiologists annotated on two separate occasions. Statistical analyses were done using Randolph's kappa and PABAK, and the proportions of specific agreements were calculated. Fair-to-excellent agreement was found for all labels among the annotators (Randolph's Kappa, 0.40-0.99). The PABAK ranged from 0.12 to 1 for the two-reader inter-rater agreement and 0.26 to 1 for the intra-rater agreement. Descriptive and broad labels achieved the highest proportion of positive agreement in both the inter- and intra-reader analyses. Annotating findings with specific, interpretive labels were found to be difficult for less experienced radiologists. Annotating images with descriptive labels may increase agreement between radiologists with different experience levels compared to annotation with interpretive labels.

Automated Identification of Multiple Findings on Brain MRI for Improving Scan Acquisition and Interpretation Workflows: A Systematic Review

We conducted a systematic review of the current status of machine learning (ML) algorithms’ ability to identify multiple brain diseases, and we evaluated their applicability for improving existing scan acquisition and interpretation workflows. PubMed Medline, Ovid Embase, Scopus, Web of Science, and IEEE Xplore literature databases were searched for relevant studies published between January 2017 and February 2022. The quality of the included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 tool. The applicability of ML algorithms for successful workflow improvement was qualitatively assessed based on the satisfaction of three clinical requirements. A total of 19 studies were included for qualitative synthesis. The included studies performed classification tasks (n = 12) and segmentation tasks (n = 7). For classification algorithms, the area under the receiver operating characteristic curve (AUC) ranged from 0.765 to 0.997, while accuracy, sensitivity, and specificity ranged from 80% to 100%, 72% to 100%, and 65% to 100%, respectively. For segmentation algorithms, the Dice coefficient ranged from 0.300 to 0.912. No studies satisfied all clinical requirements for successful workflow improvements due to key limitations pertaining to the study’s design, study data, reference standards, and performance reporting. Standardized reporting guidelines tailored for ML in radiology, prospective study designs, and multi-site testing could help alleviate this.

Can Shunt Response in Patients with Idiopathic Normal Pressure Hydrocephalus Be Predicted from Preoperative Brain Imaging? A Retrospective Study of the Diagnostic Use of the Normal Pressure Hydrocephalus Radscale in 119 Patients

BACKGROUND AND PURPOSE

The Normal Pressure Hydrocephalus Radscale is a combined scoring of 7 different structural imaging markers on preoperative brain CT or MR imaging in patients with idiopathic normal pressure hydrocephalus: callosal angle, Evans Index, Sylvian fissure dilation, apical sulcal narrowing, mean temporal horn diameter, periventricular WM lesions, and focal sulcal dilation. The purpose of this retrospective study was to assess the performance of the Normal Pressure Hydrocephalus Radscale in distinguishing idiopathic normal pressure hydrocephalus shunt responders from nonresponders.

MATERIALS AND METHODS

The preoperative MR imaging and CT scans of 119 patients with idiopathic normal pressure hydrocephalus were scored using the Normal Pressure Hydrocephalus Radscale. A summary shunt-response score assessed within 6 months from ventriculoperitoneal shunt surgery, combining the effect on cognition, gait, and urinary incontinence, was used as a reference. The difference between the mean Normal Pressure Hydrocephalus Radscale for responders and nonresponders was tested using the Student t test. The area under the curve was calculated for the Normal Pressure Hydrocephalus Radscale to assess shunt response. To ascertain reproducibility, we assessed the interobserver agreement between the 2 independent observers as intraclass correlation coefficients for the Normal Pressure Hydrocephalus Radscale for 74 MR imaging scans and 19 CT scans.

RESULTS

Ninety-four (79%) of 119 patients were shunt responders. The mean Normal Pressure Hydrocephalus Radscale score for shunt responders was 8.35 (SD, 1.53), and for nonresponders, 7.48 (SD, 1.53) (P = .02). The area under the curve for the Normal Pressure Hydrocephalus Radscale was 0.66 (range, 0.54-0.78). The intraclass correlation coefficient for the Normal Pressure Hydrocephalus Radscale was 0.86 for MR imaging and 0.82 for CT.

CONCLUSIONS

The Normal Pressure Hydrocephalus Radscale showed moderate discrimination for shunt response but cannot, on its own, be used for selecting patients with idiopathic normal pressure hydrocephalus for shunt surgery.

The Added Effect of Artificial Intelligence on Physicians' Performance in Detecting Thoracic Pathologies on CT and Chest X-ray: A Systematic Review

Our systematic review investigated the additional effect of artificial intelligence-based devices on human observers when diagnosing and/or detecting thoracic pathologies using different diagnostic imaging modalities, such as chest X-ray and CT. Peer-reviewed, original research articles from EMBASE, PubMed, Cochrane library, SCOPUS, and Web of Science were retrieved. Included articles were published within the last 20 years and used a device based on artificial intelligence (AI) technology to detect or diagnose pulmonary findings. The AI-based device had to be used in an observer test where the performance of human observers with and without addition of the device was measured as sensitivity, specificity, accuracy, AUC, or time spent on image reading. A total of 38 studies were included for final assessment. The quality assessment tool for diagnostic accuracy studies (QUADAS-2) was used for bias assessment. The average sensitivity increased from 67.8% to 74.6%; specificity from 82.2% to 85.4%; accuracy from 75.4% to 81.7%; and Area Under the ROC Curve (AUC) from 0.75 to 0.80. Generally, a faster reading time was reported when radiologists were aided by AI-based devices. Our systematic review showed that performance generally improved for the physicians when assisted by AI-based devices compared to unaided interpretation.

Surgically Induced Contrast Enhancements on Intraoperative and Early Postoperative MRI Following High-Grade Glioma Surgery: A Systematic Review

For the radiological assessment of resection of high-grade gliomas, a 72-h diagnostic window is recommended to limit surgically induced contrast enhancements. However, such enhancements may occur earlier than 72 h post-surgery. This systematic review aimed to assess the evidence on the timing of the postsurgical MRI. PubMed, Embase, Web of Science and Cochrane were searched following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Only original research articles describing surgically induced contrast enhancements on MRI after resection for high-grade gliomas were included and analysed. The frequency of different contrast enhancement patterns on intraoperative MRI (iMRI) and early postoperative MRI (epMRI) was recorded. The search resulted in 1443 studies after removing duplicates, and a total of 12 studies were chosen for final review. Surgically induced contrast enhancements were reported at all time points after surgery, including on iMRI, but their type and frequency vary. Thin linear contrast enhancements were commonly found to be surgically induced and were less frequently recorded on postoperative days 1 and 2. This suggests that the optimal time to scan may be at or before this time. However, the evidence is limited, and higher-quality studies using larger and consecutively sampled populations are needed.

Carotid Stenosis Assessment with Vector Concentration before and after Stenting

Digital subtraction angiography (DSA) is considered the reference method for the assessment of carotid artery stenosis; however, the procedure is invasive and accompanied by ionizing radiation. Velocity estimation with duplex ultrasound (DUS) is widely used for carotid artery stenosis assessment since no radiation or intravenous contrast is required; however, the method is angle-dependent. Vector concentration (VC) is a parameter for flow complexity assessment derived from the angle independent ultrasound method vector flow imaging (VFI), and VC has shown to correlate strongly with stenosis degree. The aim of this study was to compare VC estimates and DUS estimated peak-systolic (PSV) and end-diastolic velocities (EDV) for carotid artery stenosis patients, with the stenosis degree obtained with DSA. Eleven patients with symptomatic carotid artery stenosis were examined with DUS, VFI, and DSA before and after stent treatment. Compared to DSA, VC showed a strong correlation (r = -0.79, p < 0.001), while PSV (r = 0.68, p = 0.002) and EDV (r = 0.51, p = 0.048) obtained with DUS showed a moderate correlation. VFI using VC calculations may be a useful ultrasound method for carotid artery stenosis and stent patency assessment.

Can Strain Elastography Predict Malignancy of Soft Tissue Tumors in a Tertiary Sarcoma Center?

This study aims to investigate the ability of ultrasound strain elastography as an adjunct to predict malignancy in soft tissue tumors suspect of sarcoma or metastasis in a tertiary reference center for sarcoma. A total of 137 patients were included prospectively. Patients were referred on the basis of clinical or radiological suspicion of malignant soft tissue tumor. All patients had previously undergone diagnostic imaging (MRI, CT or PET-CT). After recording strain elastography cine loops, ultrasound guided biopsy was performed. Three investigators, who were blinded to final diagnosis, reviewed all elastograms retrospectively. For each elastogram, a qualitative, visual 5-point score was decided in consensus and a strain ratio was calculated. Final pathology obtained from biopsy or tumor resection served as gold standard. Eighty-one tumors were benign, and 56 were malignant. t-tests showed a significant difference in mean visual score between benign and malignant tumors. There was no significant difference in mean strain ratio between the two groups. Strain elastography may be a valuable adjunct to conventional B-mode ultrasound, perhaps primarily in primary care, when considering whether to refer to a sarcoma center or to biopsy, although biopsies cannot reliably be ruled out based on the current data.

Cortical thickness following electroconvulsive therapy in patients with depression: a longitudinal MRI study

OBJECTIVE

Several studies have found an increase in hippocampal volume following electroconvulsive therapy (ECT), but the effect on cortical thickness has been less investigated. We aimed to examine the effects of ECT on cortical thickness and their associations with clinical outcome.

METHOD

Using 3 Tesla MRI scanner, we obtained T1-weighted brain images of 18 severely depressed patients at three time points: before, right after and 6 months after a series of ECT. The thickness of 68 cortical regions was extracted using Free Surfer, and Linear Mixed Model was used to analyze the longitudinal changes.

RESULTS

We found significant increases in cortical thickness of 26 regions right after a series of ECT, mainly within the frontal, temporal and insular cortex. The thickness returned to the baseline values at 6-month follow-up. We detected no significant decreases in cortical thickness. The increase in the thickness of the right lateral orbitofrontal cortex was associated with a greater antidepressant effect, r = 0.75, P = 0.0005. None of the cortical regions showed any associations with cognitive side effects.

CONCLUSION

The increases in cortical thickness induced by ECT are transient. Further multimodal MRI studies should examine the neural correlates of these increases and their relationship with the antidepressant effect.

Hand-Held Ultrasound Devices Compared with High-End Ultrasound Systems: A Systematic Review

The aim of this study was to review the scientific literature available on the comparison of hand-held ultrasound devices with high-end systems for abdominal and pleural applications. PubMed, Embase, Web of Science and Cochrane were searched following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Original research describing hand-held ultrasound devices compared with high-end systems was included and assessed using Quality Assessment of Diagnostic Accuracy Studies (QUADAS)-2. The search was limited to articles published since 1 January 2012. A total of 2486 articles were found and screened by title and abstract. A total of 16 articles were chosen for final review. All of the included articles showed good overall agreement between hand-held and high-end ultrasound systems. Strong correlations were found when evaluating ascites, hydronephrosis, pleural cavities, in detection of abdominal aortic aneurysms and for use with obstetric and gynaecological patients. Other articles found good agreement for cholelithiasis and for determining the best site for paracentesis. QUADAS-2 analysis suggested few risks of bias and almost no concerns regarding applicability. For distinct clinical questions, hand-held devices may be a valuable supplement to physical examination. However, evidence is inadequate, and more research is needed on the abdominal and pleural use of hand-held ultrasound with more standardised comparisons, using only blinded reviewers.

Strain histograms are equal to strain ratios in predicting malignancy in breast tumours

Objectives

To assess whether strain histograms are equal to strain ratios in predicting breast tumour malignancy and to see if either could be used to upgrade Breast Imaging Reporting and Data System (BI-RADS) 3 tumours for immediate biopsy.

Methods

Ninety-nine breast tumours were examined using B-mode BI-RADS scorings and strain elastography. Strain histograms and ratios were assessed, and areas- under-the-receiver-operating-characteristic-curve (AUROC) for each method calculated. In BI-RADS 3 tumours cut-offs for strain histogram and ratio values were calculated to see if some tumours could be upgraded for immediate biopsy. Linear regression was performed to evaluate the effect of tumour depth and size, and breast density on strain elastography.

Results

Forty-four of 99 (44.4%) tumours were malignant. AUROC of BI-RADS, strain histograms and strain ratios were 0.949, 0.830 and 0.794 respectively. There was no significant difference between AUROCs of strain histograms and strain ratios (P = 0.405), while they were both inferior to BI-RADS scoring (P<0.001, P = 0.008). Four out of 26 BI-RADS 3 tumours were malignant. When cut-offs of 189 for strain histograms and 1.44 for strain ratios were used to upgrade BI-RADS 3 tumours, AUROCS were 0.961 (Strain histograms and BI-RADS) and 0.941 (Strain ratios and BI-RADS). None of them was significantly different from BI-RADS scoring alone (P = 0.249 and P = 0.414). Tumour size and depth, and breast density influenced neither strain histograms (P = 0.196, P = 0.115 and P = 0.321) nor strain ratios (P = 0.411, P = 0.596 and P = 0.321)

Conclusion

Strain histogram analyses are reliable and easy to do in breast cancer diagnosis and perform comparably to strain ratio analyses. No significant difference in AUROCs between BI-RADS scoring and elastography combined with BI-RADS scoring was found in this study.

Ultrasound Elastography Is Useful for Evaluation of Liver Fibrosis in Children-A Systematic Review

OBJECTIVES

Adult studies have proven ultrasound elastography as a validated measure of liver fibrosis. The present study aimed to review the available literature on ultrasound elastography in children to evaluate the ability of the method to distinguish healthy from fibrotic liver tissue and investigate whether cutoff values for liver fibrosis in children have been established.

METHODS

A literature search was performed in MEDLINE, EMBASE, the Cochrane Library, and Web of Science to identify studies on ultrasound elastography of the liver in children. Only original research articles in English concerning ultrasound elastography in children with and without liver disease, younger than 18 years, were included. All reference lists of the included articles were hand-searched for further references.

RESULTS

Twenty-seven articles were included. Elastography in children without liver disease was investigated in 14 studies and were comparable to those existing for adults. Twelve studies compared elastography with liver biopsy in children with liver disease and found that cirrhosis was correctly diagnosed, whereas it was more difficult to assess severe fibrosis correctly. For the distinction between no, mild, and moderate fibrosis in children with liver disease the method was less accurate. Ultrasound elastography was able to differentiate between children with and without liver fibrosis. In children without liver disease ultrasound, elastography showed consistent liver stiffness values comparable to those found in adults. No fibrosis-specific cutoffs were proposed.

CONCLUSIONS

Ultrasound elastography was able to diagnose cirrhosis, distinguish healthy from fibrotic liver tissue, and showed consistent liver stiffness values in children without liver disease.

Evaluation of healthy muscle tissue by strain and shear wave elastography - Dependency on depth and ROI position in relation to underlying bone

PURPOSE

The aim of this study was to evaluate the influence of depth and underlying bone on strain ratios and shear wave speeds for three different muscles in healthy volunteers. For strain ratios the influence from different reference region-of-interest positions was also evaluated.

MATERIAL AND METHODS

Ten healthy volunteers (five males and five females) had their biceps brachii, gastrocnemius, and quadriceps muscle examined with strain- and shear wave elastography at three different depths and in regions located above bone and beside bone. Strain ratios were averaged from cine-loops of 10s length, and shear wave speeds were measured 10 times at each target point. The distance from the skin surface to the centre of each region-of-interest was measured. Measurements were evaluated with descriptive statistics and linear regression.

RESULTS

Linear regression showed a significant influence on strain ratio measurements from the reference region-of-interest position, i.e. being above the same structures as the target region-of-interest or not (means: 1.65 and 0.78; (P<0.001)). For shear wave speeds, there was a significant influence from depth and location above or beside bone (P=0.011 and P=0.031).

CONCLUSION

Strain ratio values depend significantly on reference and target region-of-interest being above the same tissue, for instance bone. Strain ratios were not influenced by depth in this study. Shear wave speeds decreased with increasing scanning depth and if there was bone below the region-of-interest.

Accuracy of visual scoring and semi-quantification of ultrasound strain elastography--a phantom study

Purpose

The aim of this study was to evaluate the performance of strain elastography in an elasticity phantom and to assess which factors influenced visual scoring, strain histograms and strain ratios. Furthermore this study aimed to evaluate the effect of observer experience on visual scorings.

Materials and Methods

Two operators examined 20 targets of various stiffness and size (16.7 to 2.5 mm) in an elasticity phantom at a depth of 3.5 cm with a 5–18 MHz transducer. Two pre-settings were used yielding 80 scans. Eight evaluators, four experienced, four inexperienced, performed visual scorings. Cut-offs for semi-quantitative methods were established for prediction of target stiffness. Data was pooled in two categories allowing calculations of sensitivity and specificity. Statistical tests chi-square test and linear regression as relevant.

Results

Strain ratios and strain histograms were superior to visual scorings of both experienced and inexperienced observers (p = 0.025, strain histograms vs. experienced observers, p<0.001, strain histograms vs. inexperienced observers, p = 0.044 strain ratios vs. experienced observers and p = 0.002 strain ratios vs. inexperienced observers). No significant difference in predicting target stiffness between strain ratios and strain histograms (p = 0.83) nor between experienced and inexperienced observers (p = 0.054) was shown when using four categories. When pooling data in two groups (80 kPa/45 kPa vs. 14/8 kPa) the difference between the observers became significant (p<0.001). Target size had a significant influence on strain ratios measurements (p = 0.017) and on visual scorings (p<0.001) but not on the strain histograms(p = 0.358). Observer experience had significant effect on visual scorings(p = 0.003).

Conclusion

Strain ratios and strain histograms are superior to visual scoring in assessing target stiffness in a phantom. Target size had a significant impact on strain ratios and visual scoring, but not on strain histograms. Experience influenced visual scorings but the difference between experienced and inexperienced observers was only significant when looking at two classes of target stiffness.

The hydrostatic pressure indifference point underestimates orthostatic redistribution of blood in humans

The hydrostatic indifference point (HIP; where venous pressure is unaffected by posture) is located at the level of the diaphragm and is believed to indicate the orthostatic redistribution of blood, but it remains unknown whether HIP coincides with the indifference point for blood volume (VIP). During graded (± 20°) head-up (HUT) and head-down tilt (HDT) in 12 male volunteers, we determined HIP from central venous pressure and VIP from redistribution of both blood, using ultrasound imaging of the inferior caval vein (VIPui), and fluid volume, by regional electrical admittance (VIPadm). Furthermore, we evaluated whether inflation of medical antishock trousers (to 70 mmHg) affected HIP and VIP. Leaving cardiovascular variables unaffected by tilt, HIP was located 7 ± 4 cm (mean ± SD) below the 4th intercostal space (IC-4) during HUT and was similar (7 ± 3 cm) during HDT and higher (P < 0.0001) than both VIPui (HUT: 22 ± 16 cm; HDT: 13 ± 7 cm) and VIPadm (HUT: 29 ± 9 cm; HDT: 20 ± 9 cm below IC-4). During HUT antishock trousers elevated both HIP and VIPui [to 3 ± 5 cm (P = 0.028) and 17 ± 7 cm below IC-4 (P = 0.051), respectively], while VIPadm remained unaffected. By simultaneous recording of pressure and filling of the inferior caval vein as well as fluid distribution, we found HIP located corresponding to the diaphragm while VIP was placed low in the abdomen, and that medical antishock trousers elevated both HIP and VIP. The low indifference point for volume shows that the gravitational influence on distribution of blood is more profound than indicated by the indifference point for venous pressure.