Quantitative multi-slice computed tomography assessment of the mitral valvular complex for transcatheter mitral valve interventions part 1: systematic measurement methodology and inter-observer variability

AIMS Transcatheter mitral valve replacement (TMVR) is an emerging technology with the potential to treat patients with severe mitral regurgitation at excessive risk for surgical mitral valve surgery. Multimodal imaging of the mitral valvular complex and surrounding structures will be an important component for patient selection for TMVR. Our aim was to describe and evaluate a systematic multi-slice computed tomography (MSCT) image analysis methodology that provides measurements relevant for transcatheter mitral valve replacement. METHODS AND RESULTS A systematic step-by-step measurement methodology is described for structures of the mitral valvular complex including: the mitral valve annulus, left ventricle, left atrium, papillary muscles and left ventricular outflow tract. To evaluate reproducibility, two observers applied this methodology to a retrospective series of 49 cardiac MSCT scans in patients with heart failure and significant mitral regurgitation. For each of 25 geometrical metrics, we evaluated inter-observer difference and intra-class correlation. The inter-observer difference was below 10% and the intra-class correlation was above 0.81 for measurements of critical importance in the sizing of TMVR devices: the mitral valve annulus diameters, area, perimeter, the inter-trigone distance, and the aorto-mitral angle. CONCLUSIONS MSCT can provide measurements that are important for patient selection and sizing of TMVR devices. These measurements have excellent inter-observer reproducibility in patients with functional mitral regurgitation.

Sixty-four-detector CT angiography of infrarenal aortic neck length and angulation: prospective analysis of interobserver variability

PURPOSE: To quantify the interobserver variability of abdominal aortic aneurysm (AAA) neck length and angulation measurements. MATERIALS AND METHODS: A total of 25 consecutive patients scheduled for endovascular AAA repair underwent follow-up 64-row computed tomographic (CT) angiography in 0.625-mm collimation. AAA neck length and angulation were determined by four blinded, independent readers. AAA neck length was defined as the longitudinal distance between the first transverse CT slice directly distal to the lowermost renal artery and the first transverse CT slice that showed at least a 15% larger outer aortic wall diameter versus the diameter measured directly below the lowermost renal artery. Infrarenal AAA neck angulation was defined as the true angle between the longitudinal axis of the proximal AAA neck and the longitudinal axis of the AAA lumen as analyzed on three-dimensional CT reconstructions. RESULTS: Mean deviation in aortic neck length determination was 32.3% and that in aortic neck angulation was 32.1%. Interobserver variability of aortic neck length and angulation measurements was considerable: in any reader combination, at least one measurement difference was outside the predefined limits of agreement. CONCLUSIONS: Assessment of the longitudinal extension and angulation of the infrarenal aortic neck is associated with substantial observer variability, even if measurement is carried out according to a standardized protocol. Further studies are mandatory to assess dedicated technical approaches to minimize variance in the determination of the longitudinal extension and angulation of the infrarenal aortic neck.

Multi-centre validation of an automatic algorithm for fast 4D myocardial segmentation in cine CMR datasets

Quantitative analysis of cine cardiac magnetic resonance (CMR) images for the assessment of global left ventricular morphology and function remains a routine task in clinical cardiology practice. To date, this process requires user interaction and therefore prolongs the examination (i.e. cost) and introduces observer variability. In this study, we sought to validate the feasibility, accuracy, and time efficiency of a novel framework for automatic quantification of left ventricular global function in a clinical setting.

Optimisation of paediatrics computed radiography for full spine curvature measurements using a phantom: a pilot study

Aim: Optimise a set of exposure factors, with the lowest effective dose, to delineate spinal curvature with the modified Cobb method in a full spine using computed radiography (CR) for a 5-year-old paediatric anthropomorphic phantom. Methods: Images were acquired by varying a set of parameters: positions (antero-posterior (AP), posteroanterior (PA) and lateral), kilo-voltage peak (kVp) (66-90), source-to-image distance (SID) (150 to 200cm), broad focus and the use of a grid (grid in/out) to analyse the impact on E and image quality (IQ). IQ was analysed applying two approaches: objective [contrast-to-noise-ratio/(CNR] and perceptual, using 5 observers. Monte-Carlo modelling was used for dose estimation. Cohen’s Kappa coefficient was used to calculate inter-observer-variability. The angle was measured using Cobb’s method on lateral projections under different imaging conditions. Results: PA promoted the lowest effective dose (0.013 mSv) compared to AP (0.048 mSv) and lateral (0.025 mSv). The exposure parameters that allowed lower dose were 200cm SID, 90 kVp, broad focus and grid out for paediatrics using an Agfa CR system. Thirty-seven images were assessed for IQ and thirty-two were classified adequate. Cobb angle measurements varied between 16°±2.9 and 19.9°±0.9. Conclusion: Cobb angle measurements can be performed using the lowest dose with a low contrast-tonoise ratio. The variation on measurements for this was ±2.9° and this is within the range of acceptable clinical error without impact on clinical diagnosis. Further work is recommended on improvement to the sample size and a more robust perceptual IQ assessment protocol for observers.

Analysis of prion strains by PrPSc profiling in sporadic Creutzfeldt-Jakob disease.

BACKGROUND: Prion diseases are a group of invariably fatal neurodegenerative disorders affecting humans and a wide range of mammals. An essential part of the infectious agent, termed the prion, is composed of an abnormal isoform (PrPSc) of a host-encoded normal cellular protein (PrPC). The conversion of PrPC to PrPSc is thought to play a crucial role in the development of prion diseases and leads to PrPSc deposition, mainly in the central nervous system. Sporadic Creutzfeldt-Jakob disease (sCJD), the most common form of human prion disease, presents with a marked clinical heterogeneity. This diversity is accompanied by a molecular signature which can be defined by histological, biochemical, and genetic means. The molecular classification of sCJD is an important tool to aid in the understanding of underlying disease mechanisms and the development of therapy protocols. Comparability of classifications is hampered by disparity of applied methods and inter-observer variability. METHODS AND FINDINGS: To overcome these difficulties, we developed a new quantification protocol for PrPSc by using internal standards on each Western blot, which allows for generation and direct comparison of individual PrPSc profiles. By studying PrPSc profiles and PrPSc type expression within nine defined central nervous system areas of 50 patients with sCJD, we were able to show distinct PrPSc distribution patterns in diverse subtypes of sCJD. Furthermore, we were able to demonstrate the co-existence of more than one PrPSc type in individuals with sCJD in about 20% of all patients and in more than 50% of patients heterozygous for a polymorphism on codon 129 of the gene encoding the prion protein (PRNP). CONCLUSION: PrPSc profiling represents a valuable tool for the molecular classification of human prion diseases and has important implications for their diagnosis by brain biopsy. Our results show that the co-existence of more than one PrPSc type might be influenced by genetic and brain region-specific determinants. These findings provide valuable insights into the generation of distinct PrPSc types.

Reproducibility of straylight measurement by C-Quant for assessment of retinal straylight using the compensation comparison method.

BACKGROUND: Straylight gives the appearance of a veil of light thrown over a person's retinal image when there is a strong light source present. We examined the reproducibility of the measurements by C-Quant, and assessed its correlation to characteristics of the eye and subjects' age. PARTICIPANTS AND METHODS: Five repeated straylight measurements were taken using the dominant eye of 45 healthy subjects (age 21-59) with a BCVA of 20/20: 14 emmetropic, 16 myopic, eight hyperopic and seven with astigmatism. We assessed the extent of reproducibility of straylight measures using the intraclass correlation coefficient. RESULTS: The mean straylight value of all measurements was 1.01 (SD 0.23, median 0.97, interquartile range 0.85-1.1). Per 10 years of age, straylight increased in average by 0.10 (95%CI 0.04 to 0.16, p < 0.01]. We found no independent association of refraction (range -5.25 dpt to +2 dpt) on straylight values (0.001; 95%CI -0.022 to 0.024, p = 0.92). Compared to emmetropic subjects, myopia reduced straylight (-.011; -0.024 to 0.02, p = 0.11), whereas higher straylight values (0.09; -0.01 to 0.20, p = 0.09) were observed in subjects with blue irises as compared to dark-colored irises when correcting for age. The intraclass correlation coefficient (ICC) of repeated measurements was 0.83 (95%CI 0.76 to 0.90). CONCLUSIONS: Our study showed that straylight measurements with the C-Quant had a high reproducibility, i.e. a lack of large intra-observer variability, making it appropriate to be applied in long-term follow-up studies assessing the long-term effect of surgical procedures on the quality of vision.

Assessment of myocardial edema and area-at-risk in acute myocardial infarction by CMR: Evaluation of a novel T2-mapping method

Objectives. The goal of this study is to evaluate a T2-mapping sequence by: (i) measuring the reproducibility intra- and inter-observer variability in healthy volunteers in two separate scanning session with a T2 reference phantom; (2) measuring the mean T2 relaxation times by T2-mapping in infarcted myocardium in patients with subacute MI and compare it with patient's the gold standard X-ray coronary angiography and healthy volunteers results. Background. Myocardial edema is a consequence of an inflammation of the tissue, as seen in myocardial infarct (MI). It can be visualized by cardiovascular magnetic resonance (CMR) imaging using the T2 relaxation time. T2-mapping is a quantitative methodology that has the potential to address the limitation of the conventional T2-weighted (T2W) imaging. Methods. The T2-mapping protocol used for all MRI scans consisted in a radial gradient echo acquisition with a lung-liver navigator for free-breathing acquisition and affine image registration. Mid-basal short axis slices were acquired.T2-maps analyses: 2 observers semi- automatically segmented the left ventricle in 6 segments accordingly to the AHA standards. 8 healthy volunteers (age: 27 ± 4 years; 62.5% male) were scanned in 2 separate sessions. 17 patients (age : 61.9 ± 13.9 years; 82.4% male) with subacute STEMI (70.6%) and NSTEMI underwent a T2-mapping scanning session. Results. In healthy volunteers, the mean inter- and intra-observer variability over the entire short axis slice (segment 1 to 6) was 0.1 ms (95% confidence interval (CI): -0.4 to 0.5, p = 0.62) and 0.2 ms (95% CI: -2.8 to 3.2, p = 0.94, respectively. T2 relaxation time measurements with and without the correction of the phantom yielded an average difference of 3.0 ± 1.1 % and 3.1 ± 2.1 % (p = 0.828), respectively. In patients, the inter-observer variability in the entire short axis slice (S1-S6), was 0.3 ms (95% CI: -1.8 to 2.4, p = 0.85). Edema location as determined through the T2-mapping and the coronary artery occlusion as determined on X-ray coronary angiography correlated in 78.6%, but only in 60% in apical infarcts. All except one of the maximal T2 values in infarct patients were greater than the upper limit of the 95% confidence interval for normal myocardium. Conclusions. The T2-mapping methodology is accurate in detecting infarcted, i.e. edematous tissue in patients with subacute infarcts. This study further demonstrated that this T2-mapping technique is reproducible and robust enough to be used on a segmental basis for edema detection without the need of a phantom to yield a T2 correction factor. This new quantitative T2-mapping technique is promising and is likely to allow for serial follow-up studies in patients to improve our knowledge on infarct pathophysiology, on infarct healing, and for the assessment of novel treatment strategies for acute infarctions.

Quality Assessment of Cardiac Magnetic Resonance Images at 1.5/3.0 T: Description and Validation of Standardized Criteria

PURPOSE: Cardiovascular magnetic resonance (CMR) has become a robust and important diagnostic imaging modality in cardiovascular medicine. However,insufficient image quality may compromise its diagnostic accuracy. No standardized criteria are available to assess the quality of CMR studies. We aimed todescribe and validate standardized criteria to evaluate the quality of CMR studies including: a) cine steady-state free precession, b) delayed gadoliniumenhancement, and c) adenosine stress first-pass perfusion. These criteria will serve for the assessment of the image quality in the setting of the Euro-CMR registry.METHOD AND MATERIALS: First, a total of 45 quality criteria were defined (35 qualitative criteria with a score from 0-3, and 10 quantitative criteria). Thequalitative score ranged from 0 to 105. The lower the qualitative score, the better the quality. The quantitative criteria were based on the absolute signal intensity (delayed enhancement) and on the signal increase (perfusion) of the anterior/posterior left ventricular wall after gadolinium injection. These criteria were then applied in 30 patients scanned with a 1.5T system and in 15 patients scanned with a 3.0T system. The examinations were jointly interpreted by 3 CMR experts and 1 study nurse. In these 45 patients the correlation between the results of the quality assessment obtained by the different readers was calculated.RESULTS: On the 1.5T machine, the mean quality score was 3.5. The mean difference between each pair of observers was 0.2 (5.7%) with a mean standarddeviation of 1.4. On the 3.0T machine, the mean quality score was 4.4. The mean difference between each pair of onservers was 0.3 (6.4%) with a meanstandard deviation of 1.6. The quantitative quality assessments between observers were well correlated for the 1.5T machine: R was between 0.78 and 0.99 (pCONCLUSION: The described criteria for the assessment of CMR image quality are robust and have a low inter-observer variability, especially on 1.5T systems.CLINICAL RELEVANCE/APPLICATION: These criteria will allow the standardization of CMR examinations. They will help to improve the overall quality ofexaminations and the comparison between clinical studies.

Three-dimensional morphological analysis of intracranial aneurysms: a fully automated method for aneurysm sac isolation and quantification

Morphological descriptors are practical and essential biomarkers for diagnosis andtreatment selection for intracranial aneurysm management according to the current guidelinesin use. Nevertheless, relatively little work has been dedicated to improve the three-dimensionalquanti cation of aneurysmal morphology, automate the analysis, and hence reduce the inherentintra- and inter-observer variability of manual analysis. In this paper we propose a methodologyfor the automated isolation and morphological quanti cation of saccular intracranial aneurysmsbased on a 3D representation of the vascular anatomy.

A pipeline approach with spatial information for segmenting multiple sclerosis lesions on brain magnetic resonance imaging

Background: Conventional magnetic resonance imaging (MRI) techniques are highly sensitive to detect multiple sclerosis (MS) plaques, enabling a quantitative assessment of inflammatory activity and lesion load. In quantitative analyses of focal lesions, manual or semi-automated segmentations have been widely used to compute the total number of lesions and the total lesion volume. These techniques, however, are both challenging and time-consuming, being also prone to intra-observer and inter-observer variability.Aim: To develop an automated approach to segment brain tissues and MS lesions from brain MRI images. The goal is to reduce the user interaction and to provide an objective tool that eliminates the inter- and intra-observer variability.Methods: Based on the recent methods developed by Souplet et al. and de Boer et al., we propose a novel pipeline which includes the following steps: bias correction, skull stripping, atlas registration, tissue classification, and lesion segmentation. After the initial pre-processing steps, a MRI scan is automatically segmented into 4 classes: white matter (WM), grey matter (GM), cerebrospinal fluid (CSF) and partial volume. An expectation maximisation method which fits a multivariate Gaussian mixture model to T1-w, T2-w and PD-w images is used for this purpose. Based on the obtained tissue masks and using the estimated GM mean and variance, we apply an intensity threshold to the FLAIR image, which provides the lesion segmentation. With the aim of improving this initial result, spatial information coming from the neighbouring tissue labels is used to refine the final lesion segmentation.Results:The experimental evaluation was performed using real data sets of 1.5T and the corresponding ground truth annotations provided by expert radiologists. The following values were obtained: 64% of true positive (TP) fraction, 80% of false positive (FP) fraction, and an average surface distance of 7.89 mm. The results of our approach were quantitatively compared to our implementations of the works of Souplet et al. and de Boer et al., obtaining higher TP and lower FP values.Conclusion: Promising MS lesion segmentation results have been obtained in terms of TP. However, the high number of FP which is still a well-known problem of all the automated MS lesion segmentation approaches has to be improved in order to use them for the standard clinical practice. Our future work will focus on tackling this issue.

A new technique with high reproducibility to estimate renal oxygenation using BOLD-MRI in chronic kidney disease.

OBJECTIVES: To assess inter-observer variability of renal blood oxygenation level-dependent MRI (BOLD-MRI) using a new method of analysis, called the concentric objects (CO) technique, in comparison with the classical ROI (region of interest)-based technique. METHODS: MR imaging (3T) was performed before and after furosemide in 10 chronic kidney disease (CKD) patients (mean eGFR 43±24ml/min/1.73m(2)) and 10 healthy volunteers (eGFR 101±28ml/min1.73m(2)), and R2* maps were determined on four coronal slices. In the CO-technique, R2* values were based on a semi-automatic procedure that divided each kidney in six equal layers, whereas in the ROI-technique, all circles (ROIs) were placed manually in the cortex and medulla. The mean R2*values as assessed by two independent investigators were compared. RESULTS: With the CO-technique, inter-observer variability was 0.7%-1.9% across all layers in non-CKD, versus 1.6%-3.8% in CKD. With the ROI-technique, median variability for cortical and medullary R2* values was 3.6 and 6.8% in non-CKD, versus 4.7 and 12.5% in CKD; similar results were observed after furosemide. CONCLUSION: The CO-technique offers a new, investigator-independent, highly reproducible alternative to the ROI-based technique to estimate renal tissue oxygenation in CKD.

How Reliable Is Ki-67 Immunohistochemistry in Grade 2 Breast Carcinomas? A QA Study of the Swiss Working Group of Breast- and Gynecopathologists.

Adjuvant chemotherapy decisions in breast cancer are increasingly based on the pathologist's assessment of tumor proliferation. The Swiss Working Group of Gyneco- and Breast Pathologists has surveyed inter- and intraobserver consistency of Ki-67-based proliferative fraction in breast carcinomas. METHODS: Five pathologists evaluated MIB-1-labeling index (LI) in ten breast carcinomas (G1, G2, G3) by counting and eyeballing. In the same way, 15 pathologists all over Switzerland then assessed MIB-1-LI on three G2 carcinomas, in self-selected or pre-defined areas of the tumors, comparing centrally immunostained slides with slides immunostained in the different laboratoires. To study intra-observer variability, the same tumors were re-examined 4 months later. RESULTS: The Kappa values for the first series of ten carcinomas of various degrees of differentiation showed good to very good agreement for MIB-1-LI (Kappa 0.56-0.72). However, we found very high inter-observer variabilities (Kappa 0.04-0.14) in the read-outs of the G2 carcinomas. It was not possible to explain the inconsistencies exclusively by any of the following factors: (i) pathologists' divergent definitions of what counts as a positive nucleus (ii) the mode of assessment (counting vs. eyeballing), (iii) immunostaining technique, and (iv) the selection of the tumor area in which to count. Despite intensive confrontation of all participating pathologists with the problem, inter-observer agreement did not improve when the same slides were re-examined 4 months later (Kappa 0.01-0.04) and intra-observer agreement was likewise poor (Kappa 0.00-0.35). CONCLUSION: Assessment of mid-range Ki-67-LI suffers from high inter- and intra-observer variability. Oncologists should be aware of this caveat when using Ki-67-LI as a basis for treatment decisions in moderately differentiated breast carcinomas.

Automated grading of left ventricular segmental wall motion by an artificial neural network using color kinesis images

The present study describes an auxiliary tool in the diagnosis of left ventricular (LV) segmental wall motion (WM) abnormalities based on color-coded echocardiographic WM images. An artificial neural network (ANN) was developed and validated for grading LV segmental WM using data from color kinesis (CK) images, a technique developed to display the timing and magnitude of global and regional WM in real time. We evaluated 21 normal subjects and 20 patients with LVWM abnormalities revealed by two-dimensional echocardiography. CK images were obtained in two sets of viewing planes. A method was developed to analyze CK images, providing quantitation of fractional area change in each of the 16 LV segments. Two experienced observers analyzed LVWM from two-dimensional images and scored them as: 1) normal, 2) mild hypokinesia, 3) moderate hypokinesia, 4) severe hypokinesia, 5) akinesia, and 6) dyskinesia. Based on expert analysis of 10 normal subjects and 10 patients, we trained a multilayer perceptron ANN using a back-propagation algorithm to provide automated grading of LVWM, and this ANN was then tested in the remaining subjects. Excellent concordance between expert and ANN analysis was shown by ROC curve analysis, with measured area under the curve of 0.975. An excellent correlation was also obtained for global LV segmental WM index by expert and ANN analysis (R² = 0.99). In conclusion, ANN showed high accuracy for automated semi-quantitative grading of WM based on CK images. This technique can be an important aid, improving diagnostic accuracy and reducing inter-observer variability in scoring segmental LVWM.

The use of artificial intelligence algorithms to guide surgical treatment of adolescent idiopathic scoliosis

La scoliose idiopathique de l’adolescent (SIA) est une déformation tri-dimensionelle du rachis. Son traitement comprend l’observation, l’utilisation de corsets pour limiter sa progression ou la chirurgie pour corriger la déformation squelettique et cesser sa progression. Le traitement chirurgical reste controversé au niveau des indications, mais aussi de la chirurgie à entreprendre. Malgré la présence de classifications pour guider le traitement de la SIA, une variabilité dans la stratégie opératoire intra et inter-observateur a été décrite dans la littérature. Cette variabilité s’accentue d’autant plus avec l’évolution des techniques chirurgicales et de l’instrumentation disponible. L’avancement de la technologie et son intégration dans le milieu médical a mené à l’utilisation d’algorithmes d’intelligence artificielle informatiques pour aider la classification et l’évaluation tridimensionnelle de la scoliose. Certains algorithmes ont démontré être efficace pour diminuer la variabilité dans la classification de la scoliose et pour guider le traitement. L’objectif général de cette thèse est de développer une application utilisant des outils d’intelligence artificielle pour intégrer les données d’un nouveau patient et les évidences disponibles dans la littérature pour guider le traitement chirurgical de la SIA. Pour cela une revue de la littérature sur les applications existantes dans l’évaluation de la SIA fut entreprise pour rassembler les éléments qui permettraient la mise en place d’une application efficace et acceptée dans le milieu clinique. Cette revue de la littérature nous a permis de réaliser que l’existence de “black box” dans les applications développées est une limitation pour l’intégration clinique ou la justification basée sur les évidence est essentielle. Dans une première étude nous avons développé un arbre décisionnel de classification de la scoliose idiopathique basé sur la classification de Lenke qui est la plus communément utilisée de nos jours mais a été critiquée pour sa complexité et la variabilité inter et intra-observateur. Cet arbre décisionnel a démontré qu’il permet d’augmenter la précision de classification proportionnellement au temps passé à classifier et ce indépendamment du niveau de connaissance sur la SIA. Dans une deuxième étude, un algorithme de stratégies chirurgicales basé sur des règles extraites de la littérature a été développé pour guider les chirurgiens dans la sélection de l’approche et les niveaux de fusion pour la SIA. Lorsque cet algorithme est appliqué à une large base de donnée de 1556 cas de SIA, il est capable de proposer une stratégie opératoire similaire à celle d’un chirurgien expert dans prêt de 70% des cas. Cette étude a confirmé la possibilité d’extraire des stratégies opératoires valides à l’aide d’un arbre décisionnel utilisant des règles extraites de la littérature. Dans une troisième étude, la classification de 1776 patients avec la SIA à l’aide d’une carte de Kohonen, un type de réseaux de neurone a permis de démontrer qu’il existe des scoliose typiques (scoliose à courbes uniques ou double thoracique) pour lesquelles la variabilité dans le traitement chirurgical varie peu des recommandations par la classification de Lenke tandis que les scolioses a courbes multiples ou tangentielles à deux groupes de courbes typiques étaient celles avec le plus de variation dans la stratégie opératoire. Finalement, une plateforme logicielle a été développée intégrant chacune des études ci-dessus. Cette interface logicielle permet l’entrée de données radiologiques pour un patient scoliotique, classifie la SIA à l’aide de l’arbre décisionnel de classification et suggère une approche chirurgicale basée sur l’arbre décisionnel de stratégies opératoires. Une analyse de la correction post-opératoire obtenue démontre une tendance, bien que non-statistiquement significative, à une meilleure balance chez les patients opérés suivant la stratégie recommandée par la plateforme logicielle que ceux aillant un traitement différent. Les études exposées dans cette thèse soulignent que l’utilisation d’algorithmes d’intelligence artificielle dans la classification et l’élaboration de stratégies opératoires de la SIA peuvent être intégrées dans une plateforme logicielle et pourraient assister les chirurgiens dans leur planification préopératoire.

Impacto de un curso teórico de mamografía en la categorización de microcalcificaciones de acuerdo al BI-RADS 4ed

Introducción: Por medio del presente estudio se busca determinar el impacto de un curso teórico de mamografía en la categorización de microcalficaciones mamarias. Materiales y métodos: Se realizó un estudio doble ciego para evaluar la variación de los valores predictivos positivos (VPP) de los descriptores morfológicos y de distribución de calcificaciones del BI-RADS 4ed, luego de un curso teórico de mamografía de 6 horas distribuido en 12 charlas semanales de 30 minutos. Se utilizó la base de datos de un estudio previo, en el cual dos radiólogos clasificaron las calcificaciones presentes en 108 mamografías de pacientes con diagnóstico histológico. Se realizó una nueva categorización de las calcificaciones según los descriptores. Se calcularon además, los valores kappa ponderados de concordancia intra e inter-observador, la sensibilidad y especificidad. Resultados: Para las calcificaciones de alta probabilidad de malignidad (pleomórficas finas y lineales ramificadas en conjunto), se obtuvieron VPP de 41 y 40%, con aumento leve respecto a la lectura inicial. El índice kappa ponderado para el acuerdo inter-observador fue de 0,305 lo que indica concordancia débil, con discreto incremento respecto a la evaluación inicial 0,260. La concordancia intra-observador para el evaluador 1 dio un valor kappa 0,471, moderada; y para el evaluador 2 un valor kappa 0,400, débil. Discusión: Un módulo teórico corto permite mejorar ligeramente la concordancia inter-observador en la evaluación de microcalcificaciones mamarias mediante el BI-RADS 4ed, así como los valores predictivos positivos de microcalficaciones de alta probabilidad de malignidad.