Radiological Structured Report Integrated with Quantitative Imaging Biomarkers and Qualitative Scoring Systems.

The benefits of structured reporting (SR) in radiology are well-known and have been widely described. However, there are limitations that must be overcome. Radiologists may be reluctant to change the conventional way of reporting. Error rates could potentially increase if SR is used improperly. Interruption of the visual search pattern by keeping the eyes focused on the report rather than the images may increase reporting time. Templates that include unnecessary or irrelevant information may undermine the consistency of the report. Last, the lack of support for multiple languages may hamper the adaptation of the report to the target audience. This work aims to mitigate these limitations with a web-based structured reporting system based on templates. By including field validators and logical rules, the system avoids reporting mistakes and allows to automatically calculate values and radiological qualitative scores. The system can manage quantitative information from imaging biomarkers, combining this with qualitative radiological information usually present in the structured report. It manages SR templates as plugins (IHE MRRT compliant and compatible with RSNA's Radreport templates), ensures a seamless integration with PACS/RIS systems, and adapts the report to the target audience by means of natural language extracts generated in multiple languages. We describe a use case of SR template for prostate cancer including PI-RADS 2.1 scoring system and imaging biomarkers. For the time being, the system comprises 24 SR templates and provides service in 37 hospitals and healthcare institutions, endorsing the success of this contribution to mitigate some of the limitations of the SR.

Identifying pulmonary nodules or masses on chest radiography using deep learning: external validation and strategies to improve clinical practice.

AIM: To test the diagnostic performance of a deep learning-based system for the detection of clinically significant pulmonary nodules/masses on chest radiographs. MATERIALS AND METHODS: Using a retrospective study of 100 patients (47 with clinically significant pulmonary nodules/masses and 53 control subjects without pulmonary nodules), two radiologists verified clinically significantly pulmonary nodules/masses according to chest computed tomography (CT) findings. A computer-aided diagnosis (CAD) software using a deep-learning approach was used to detect pulmonary nodules/masses to determine the diagnostic performance in four algorithms (heat map, abnormal probability, nodule probability, and mass probability). RESULTS: A total of 100 cases were included in the analysis. Among the four algorithms, mass algorithm could achieve a 76.6% sensitivity (36/47, 11 false negative) and 88.68% specificity (47/53, six false-positive) in the detection of pulmonary nodules/masses at the optimal probability score cut-off of 0.2884. Compared to the other three algorithms, mass probability algorithm had best predictive ability for pulmonary nodule/mass detection at the optimal probability score cut-off of 0.2884 (AUCMass: 0.916 versus AUCHeat map: 0.682, p<0.001; AUCMass: 0.916 versus AUCAbnormal: 0.810, p=0.002; AUCMass: 0.916 versus AUCNodule: 0.813, p=0.014). CONCLUSION: In conclusion, the deep-learning based computer-aided diagnosis system will likely play a vital role in the early detection and diagnosis of pulmonary nodules/masses on chest radiographs. In future applications, these algorithms could support triage workflow via double reading to improve sensitivity and specificity during the diagnostic process.

Differences in multi-echo chemical shift encoded MRI proton density fat fraction estimation based on multifrequency fat peaks selection in non-alcoholic fatty liver disease patients.

AIM: To compare the performance of multi-echo chemical-shift-encoded (MECSE) magnetic resonance imaging (MRI) proton density fat fraction (PDFF) estimation, considering three different fat frequency peak combinations, for the quantification of steatosis in patients with non-alcoholic fatty liver disease (NAFLD). MATERIALS AND METHODS: The present study was a prospective cross-sectional research of 121 patients with metabolic syndrome and evidence of hepatic steatosis on ultrasound, who underwent a 3 T MRI examination. All patients were studied with a multifrequency MECSE sequence. The PDFF was calculated using six peaks (MECSEp123456), three peaks (MECSEp456), and a single peak (MECSEp5) model. The two simpler fat peak models were compared to the six peaks model, which was considered the reference standard. Linearity was evaluated using linear regression while agreement was described using Bland-Altman analysis. RESULTS: The mean age was 47 (±9) years and BMI was 29.9 (±2.9) kg/m2. Steatosis distribution was 15%/31%/54% (S1/S2/S3, respectively). Compared to MECSEp123456, both models provided linear PDFF measurements (R2= 0.99 and 0.97, MECSEp456 and MECSEp5 respectively). Regression slope (0.92; p<0.001) and mean Bland-Altman bias (-1.5%; 95% limits of agreement: -3.19%, 0.22%) indicated minimal underestimation by using PDFF-MECSEp456. Nonetheless, mean differences in PDFF estimations varied from -1.5% (MECSEp456,p=0.006) to -2.2% (MECSEp5,p<0.001) when compared to full six fat frequencies model. CONCLUSION: Although simpler spectral fat MECSE analysis shows a linear relationship with the standard six peaks model, their variation in estimated PDFF values introduces a low but clinically significant bias in fat quantification and steatosis grading in NAFLD patients.

Tissue iron quantification in chronic liver diseases using MRI shows a relationship between iron accumulation in liver, spleen, and bone marrow.

AIM: To investigate iron loading within the liver, pancreas, spleen, and bone marrow using magnetic resonance imaging (MRI) transverse relaxation rate (R2*), in patients with diffuse liver diseases; to evaluate the relationships between iron accumulation in these tissue compartments; and to assess the association between tissue iron overload and the pattern of hepatic cellular iron distribution (hepatocytes versus Kupffer cells). MATERIAL AND METHODS: Fifty-six patients with diffuse liver diseases had MRI-derived R2* values, using a multi-echo chemical-shift encoded MRI sequence, of the liver, pancreas, spleen, and vertebral bone marrow. All patients had liver biopsy samples scored for hepatic iron grading (0-4) and iron cellular distribution (within hepatocytes only or within both hepatocytes and Kupffer cells). RESULTS: Liver R2* increased with histological iron grade (RS=0.58, p<0.001) and correlated with spleen (RS=0.71, p<0.001) and bone marrow R2* (RS=0.66, p<0.001), but not with pancreatic R2* (RS=0.22, p=0.096). Splenic and bone marrow R2* values were also correlated (RS=0.72, p<0.001). Patients with iron inside Kupffer cells had the highest R2* in liver, spleen and bone marrow. CONCLUSIONS: Patients with chronic diffuse liver diseases have concomitant hepatic, splenic, and bone marrow iron loading. The highest hepatic iron scores and iron inside Kupffer cells were associated with the highest splenic and bone marrow deposits, suggesting systemic iron accumulation in the mononuclear phagocytic system.

Neuroinflammation in obesity: circulating lipopolysaccharide-binding protein associates with brain structure and cognitive performance.

BACKGROUND/OBJECTIVES: Growing evidence implicates neuroinflammation in the pathogenesis of diet-induced obesity and cognitive dysfunction in rodent models. Obesity is associated with reduced white matter integrity and cognitive decline. Circulating lipopolysaccharide binding protein (LBP) concentration is known to be increased in patients with obesity. Here, we aimed to evaluate whether circulating LBP is associated longitudinally with white matter structure and cognitive performance according to obesity status. SUBJECTS/METHODS: This longitudinal study analyzed circulating LBP (ELISA), DTI-metrics (axial diffusivity (L1), fractional anisotropy (FA) and radial diffusivity (RD)) in specific regions of the white matter of 24 consecutive middle-aged obese subjects (13 women) and 20 healthy volunteers (10 women) at baseline and two years later. Digit Span Test (DST) was used as a measure of working memory/short-term verbal memory. RESULTS: Circulating LBP concentration was associated with FA and L1 values of several white matter regions both at baseline and follow-up. The associations remained significant after controlling for age, BMI, fat mass and plasma high sensitivity C-reactive protein. Importantly, the increase in LBP over time impacted negatively on FA and L1 values and on DST performance. CONCLUSIONS: Circulating LBP associates with brain white matter integrity and working memory/short-term verbal memory in both obese and non-obese subjects.

Quantitative phase-contrast MRI study of cerebrospinal fluid flow: a method for identifying patients with normal-pressure hydrocephalus.

OBJECTIVES: The aim of this study is to evaluate the use of phase-contrast MR imaging to diagnose normal pressure hydrocephalus (NPH) and differentiate it from other neurological disorders with similar clinical symptoms. METHODS: The study included 108 subjects, of whom 61 were healthy controls and 47, patients; in the patient group, 19 had cerebrovascular disease (CVD) and 28 had NPH. All patients underwent a phase-contrast MRI study and several CSF flow and velocity parameters were measured at the aqueduct of Sylvius. Discriminant analyses were performed to evaluate the classification capacity of both individual parameters and the combination of different parameters. RESULTS: Maximum diastolic velocity, mean flow, and stroke volume showed statistically significant differences that could be used to distinguish between NPH and CVD patients (P<.001). Stroke volume and mean flow showed no false positive results and successful classification rates of 86% and 79%, respectively. No other parameters or combination produced better results. CONCLUSIONS: Phase-contrast MR imaging is a useful tool for the early diagnosis of patients with NPH. CSF flow quantitative parameters, along with morphological features in a conventional MR study, enable us to differentiate between NPH and CVD patients.

[Reproducibility and accuracy in the morphometric and mechanical quantification of trabecular bone from 3 Tesla magnetic resonance images]. / Reproducibilidad y exactitud en la cuantificación morfométrica y mecánica del hueso trabecular a partir de imágenes de resonancia magnética de Tesla.

OBJECTIVE: We used an animal model to analyze the reproducibility and accuracy of certain biomarkers of bone image quality in comparison to a gold standard of computed microtomography (µCT). MATERIAL AND METHODS: We used magnetic resonance (MR) imaging and µCT to study the metaphyses of 5 sheep tibiae. The MR images (3 Teslas) were acquired with a T1-weighted gradient echo sequence and an isotropic spatial resolution of 180µm. The µCT images were acquired using a scanner with a spatial resolution of 7.5µm isotropic voxels. In the preparation of the images, we applied equalization, interpolation, and thresholding algorithms. In the quantitative analysis, we calculated the percentage of bone volume (BV/TV), the trabecular thickness (Tb.Th), the trabecular separation (Tb.Sp), the trabecular index (Tb.N), the 2D fractal dimension (D(2D)), the 3D fractal dimension (D(3D)), and the elastic module in the three spatial directions (Ex, Ey and Ez). RESULTS: The morphometric and mechanical quantification of trabecular bone by MR was very reproducible, with percentages of variation below 9% for all the parameters. Its accuracy compared to the gold standard (µCT) was high, with errors less than 15% for BV/TV, D(2D), D(3D), and E(app)x, E(app)y and E(app)z. CONCLUSIONS: Our experimental results in animals confirm that the parameters of BV/TV, D(2D), D(3D), and E(app)x, E(app)y and E(app)z obtained by MR have excellent reproducibility and accuracy and can be used as imaging biomarkers for the quality of trabecular bone.

[Integrating information about imaging biomarkers into structured radiology reports]. / Integrando el informe de biomarcadores de imagen en el informe radiológico estructurado.

Imaging biomarkers describe objective characteristics that are related to normal biological processes, diseases, or the response to treatment. They enable radiologists to incorporate into their reports data about structure, function, and tissue components. With the aim of taking maximum advantage of the quantification of medical images, we present a procedure to integrate imaging biomarkers into radiological reports, bringing the new paradigm of personal medicine closer to radiological workflow. In this manner, the results of quantification can complement traditional radiological diagnosis, improving accuracy and the evaluation of the efficacy of treatments. A more personalized, standardized, structured radiological report should include quantitative analyses to complement conventional qualitative reporting in selected cases.

[Safe use of magnetic resonance imaging: practical recommendations for personnel]. / Utilización segura de la resonancia magnética. Recomendaciones prácticas para el personal que trabaja con resonancia magnética.

MRI is a powerful diagnostic imaging tool and its use has increased significantly in hospitals all over the world. Due to the technical particularities of MRI, all staff members dealing with the scanner need to have adequate knowledge of how it works and of aspects related to safety. The European parliament and council's directive on minimum health and safety requirements for workers dealing with electromagnetic fields (EMF) 2004/40/CE represents a threat to the clinical development and healthcare use of MRI. The efforts of the Alliance for MRI led to a postponement of the European parliament's decision, first until April 2012 and finally until October 2013. The purpose of this article is to define and propose a set of practical rules to ensure the protection of workers involved with MRI scanners. It also aims to define our position with respect to UE directive (2004/40/CE).

[Imaging biomarkers, quantitative imaging, and bioengineering]. / Biomarcadores de imagen, imagen cuantitativa y bioingeniería.

Imaging biomarkers define objective characteristics extracted from medical images that are related to normal biological processes, diseases, or the response to treatment. To develop an imaging biomarker, it is necessary to carry out a series of steps to validate its relation with the reality studied and to check its clinical and technical validity. This process includes defining tests for the concepts and mechanisms; obtaining standardized and optimized anatomic, functional, and molecular images; analyzing the data with computer models; displaying data appropriately; obtaining the appropriate statistic measures; and conducting tests on the principle, efficacy, and effectiveness. In this article, we aim to explain the steps that must be established to enable biomarkers to be correctly applied, from their theoretical conception to their clinical implementation. To this end, we use the evaluation of angiogenesis in articular cartilage as an example.

Magnetic Resonance imaging analysis of liver fibrosis and inflammation: overwhelming gray zones restrict clinical use.

Magnetic resonance (MR) identification and grading of subjects with liver fibrosis and inflammation represents a clinical challenge. MR elastography plays a well-defined role in fibrosis estimation, but its use is not widely available in clinical settings. Given that liver MR is becoming the reference standard for fat and iron quantitation, there is a need to clarify whether there is any role for MR imaging in the concomitant evaluation of fibrosis and inflammation in this setting. This review summarizes the diagnostic estimations of different MR imaging parameters obtained from conventional non-contrast-enhanced multiple b values diffusion-weighted acquisitions, variable flip angles T1 relaxation maps and STIR images. Although some derived parameters have shown a significant correlation to histological scores, a small magnitude of effect with wide overlap across severity grades is the rule. Contrary to fat and iron quantification, the low precision and reproducibility of MR imaging metrics limits its clinical relevance in fibrosis and inflammation assessment. In a sequential clinical approach combining different methodologies, MR imaging has no applicability for ruling-out and low accuracy for ruling-in advanced fibrosis. Thereby, MR elastography remains as the only image method with high diagnostic accuracy for the detection of advanced fibrosis. Until date, inflammation remains in a gray zone where biopsy cannot be replaced, and further investigations are needed. The present review offers an in-depth discuss of the MR imaging diagnostic performance for the evaluation of liver fibrosis and inflammation, highlighting the need for scientific improvements.

Quantifying steatosis in the liver and pancreas with MRI in patient with chronic liver disease. / Cuantificación por resonancia magnética de esteatosis hepática y pancreática en hepatopatía crónica.

AIM: To compare pancreatic and hepatic steatosis quantified by proton density fat fraction (PDFF) on magnetic resonance imaging (MRI) in patients with chronic liver disease. MATERIAL AND METHODS: This cross-sectional study included 46 adult patients who underwent liver biopsy for chronic viral hepatitis (n=19) or other chronic non-alcoholic liver diseases (NALD) (n=27). Liver biopsy was used as the gold standard for diagnosing and grading hepatic steatosis. All patients underwent clinical evaluation and MRI with a multi-echo chemical shift-encoded (MECSE) gradient-echo sequence for liver and pancreas PDFF quantification. We used Spearman's correlation coefficient to determine the degree of association between hepatic PDFF and steatosis grade, and between pancreatic PDFF and steatosis grade and hepatic PDFF. To compare the chronic viral hepatitis group and the NALD group, we used t-tests for continuous or ordinal variables and chi-square tests for categorical variables. RESULTS: Hepatic PDFF measurements correlated with steatosis grades (RS=0.875, p<0.001). Pancreatic PDFF correlated with hepatic steatosis grades (RS=0.573, p<0.001) and hepatic PDFF measurements (RS=0.536, p<0.001). In the subgroup of patients with chronic NALD, the correlations remained significant between pancreatic PDFF and hepatic PDFF (RS=0.632, p<0.001) and between pancreatic PDFF and liver steatosis (RS=0.608, p<0.001); however, in the subgroup of patients with viral hepatitis these correlations were no longer significant. CONCLUSION: Pancreatic fat deposition correlates with hepatic steatosis in patients with chronic NALD, but not in those with chronic viral hepatitis.

[Magnetic resonance for evaluating the response to treatment for ovarian hyperstimulation syndrome: comparison of pharmokinetic models.]. / Resonancia magnética en la respuesta al tratamiento del síndrome de hiperestimulación ovárica: comparación de modelos farmacocinéticos.

OBJECTIVE: To evaluate the response to treatment with cabergoline for ovarian hyperstimulation syndrome (OHS) using mono- and bi-compartmental MRI models. MATERIAL AND METHODS: We studied 20 ovum donors with a high risk of developing OHS, divided in two groups (placebo vs. treatment). MRI perfusion studies were performed before and after the beginning of treatment. We compared the monocompartmental model, with the parameters vascular permeability (K(trans)), extraction ratio (k(ep)), and extravascular extracellular space fraction (v(e)), against the bicompartmental model, with the same parameters as in the monocompartmental model and the additional parameter vascular space fraction (v(p)). The differences between groups (placebo vs. treatment) on the two MRI studies and for each pharmacokinetic model were analyzed using t-tests for independent samples. The intraclass correlation coefficient (ICC) was used to assess the variability of the measurements. RESULTS: In the placebo group, a significant increase in K(trans) was observed with both models (p=0.021 for one compartment; and p<0.001 for two compartments). In the treatment group, no statistically significant differences were found for any parameter in either model. Regarding differences between groups, in the bicompartmental model K(trans) increased 168.6%+/-151.9% in the placebo group versus 43.3%+/-54.5% in the treatment group, p=0.04). In the monocompartmental model, no differences were found between groups. In the variability analysis, the ICC was higher than 0.95 for all parameters except v(p) (ICC=0.89). CONCLUSIONS: Capillary permeability calculated with bicompartmental pharmacokinetic models after MRI contrast administration is a biomarker of the treatment effect in OHS patients.

Insulin resistance and NAFLD: Relationship with intrahepatic iron and serum TNF-α using 1H MR spectroscopy and MRI.

AIM: The association of non-alcoholic fatty liver disease (NAFLD) with insulin resistance (IR) is well established, yet little is known of their possible relationship with intrahepatic iron and serum tumour necrosis factor (TNF)-α concentrations in adults without diabetes. Thus, this study looked at the relationship of intrahepatic iron and serum TNF-α with intrahepatic triglycerides and IR in non-diabetic adults. METHODS: In this cross-sectional study of 104 healthy non-diabetic Caucasians, a quantitative magnetic resonance (MR) imaging T2 gradient-echo technique was used to measure hepatic iron, with 1H-MR spectroscopy used to measure hepatic triglycerides. HOMA-IR was calculated to determine IR. RESULTS: The prevalence of hepatic iron overload (HIOL) was 26.6% in individuals with NAFLD vs. 0% in those without. IR was present in 87.5% of subjects with both NAFLD and HIOL, in 45.4% of those with NAFLD but not HIOL, and in 4.5% of those with neither. HOMA-IR was positively correlated with hepatic triglycerides (r = 0.56, P < 0.001) and hepatic iron (r = 0.52, P < 0.001), whereas serum TNF-α concentrations correlated with intrahepatic triglyceride levels (r = 0.28, P < 0.04), but not with intrahepatic iron. Hepatic triglycerides, serum TNF-α and age were the only significant determinants of IR in regression analyses. CONCLUSION: IR is closely associated with intrahepatic triglycerides and, to a lesser extent, intrahepatic iron, with some interplay between them. High serum TNF-α concentrations may contribute to the association between NAFLD and IR, while increased hepatic triglycerides appear to be a determinant of the development of HIOL in non-diabetic subjects without haemochromatosis.

Evaluation of PET texture features with heterogeneous phantoms: complementarity and effect of motion and segmentation method.

A major source of error in quantitative PET/CT scans of lung cancer tumors is respiratory motion. Regarding the variability of PET texture features (TF), the impact of respiratory motion has not been properly studied with experimental phantoms. The primary aim of this work was to evaluate the current use of PET texture analysis for heterogeneity characterization in lesions affected by respiratory motion. Twenty-eight heterogeneous lesions were simulated by a mixture of alginate and 18 F-fluoro-2-deoxy-D-glucose (FDG). Sixteen respiratory patterns were applied. Firstly, the TF response for different heterogeneous phantoms and its robustness with respect to the segmentation method were calculated. Secondly, the variability for TF derived from PET image with (gated, G-) and without (ungated, U-) motion compensation was analyzed. Finally, TF complementarity was assessed. In the comparison of TF derived from the ideal contour with respect to TF derived from 40%-threshold and adaptive-threshold PET contours, 7/8 TF showed strong linear correlation (LC) (p < 0.001, r > 0.75), despite a significant volume underestimation. Independence of lesion movement (LC in 100% of the combined pairs of movements, p < 0.05) was obtained for 1/8 TF with U-image (width of the volume-activity histogram, WH) and 4/8 TF with G-image (WH and energy (ENG), local-homogeneity (LH) and entropy (ENT), derived from the co-ocurrence matrix). Their variability in terms of the coefficient of variance ([Formula: see text]) resulted in [Formula: see text](WH) = 0.18 on the U-image and [Formula: see text](WH) = 0.24, [Formula: see text](ENG) = 0.15, [Formula: see text](LH) = 0.07 and [Formula: see text](ENT) = 0.06 on the G-image. Apart from WH (r > 0.9, p < 0.001), not one of these TF has shown LC with C max. Complementarity was observed for the TF pairs: ENG-LH, CONT (contrast)-ENT and LH-ENT. In conclusion, the effect of respiratory motion should be taken into account when the heterogeneity of lung cancer is quantified on PET/CT images. Despite inaccurate volume delineation, TF derived from 40% and COA contours could be reliable for their prognostic use. The TF that exhibited simultaneous added value and independence of lesion movement were ENG and ENT computed from the G-image. Their use is therefore recommended for heterogeneity quantification of lesions affected by respiratory motion.

[Modification of longitudinal relaxation time (T1) as a biomarker of patellar cartilage degeneration]. / Modificación del tiempo de relajación longitudinal (T1) como biomarcador de la degeneración del cartílago patelar.

OBJECTIVES: To study the viability of longitudinal relaxation time (T1) of patellar cartilage as a biomarker of the degree of degeneration. MATERIAL AND METHODS: We included 15 subjects classified into three groups according to clinical criteria (pain, functional limitation, and duration of symptoms) and imaging criteria as follows: (a) normal (3 men, 2 women; age 30+/-14 years), (b) with initial degeneration of the patellar cartilage (3 men, 2 women; age 30+/-6 years), or (c) with advanced degeneration (3 men, 2 women; age 57+/-10 years). All underwent MRI examination using special echo-gradient sequences to segment the cartilage and calculate the T1 maps. We selected the entire cartilage and the regions of interest classified according to clinical and imaging criteria as normal, initial degeneration, and advanced degeneration. The T1 values of the cartilage were obtained pixel by pixel and were calculated as the mean for the entire cartilage or by subregions (normal, initial, advanced). Differences between groups for the entire cartilage and the regions were analyzed using Student-Newman-Keuls post-hoc ANOVA. Reproducibility was evaluated using the coefficient of variance. RESULTS: No significant differences in the overall analysis of the entire cartilage were found between the three groups (normal: 1003+/-172 ms, initial: 1064+/-124 ms, advanced: 1041+/-308 ms, p=0.665). However, the analysis by regions revealed significant differences (normal: 908+/-53 ms, initial degeneration: 1057+/-157 ms, advanced degeneration: 1133+/-116 ms, p=0.029). The reproducibility analysis found variations of 1.3% for the overall calculation, 3.7% for the regional calculation, and 8.2% for the acquisition. CONCLUSION: In this preliminary study, calculating the T1 of the cartilage enabled regions with different degrees of degeneration to be differentiated.