Can a single image processing algorithm work equally well across all phases of DCE-MRI?

Image segmentation and registration are said to be challenging when applied to dynamic contrast enhanced MRI sequences (DCE-MRI). The contrast agent causes rapid changes in intensity in the region of interest and elsewhere, which can lead to false positive predictions for segmentation tasks and confound the image registration similarity metric. While it is widely assumed that contrast changes increase the difficulty of these tasks, to our knowledge no work has quantified these effects. In this paper we examine the effect of training with different ratios of contrast enhanced (CE) data on two popular tasks: segmentation with nnU-Net and Mask R-CNN and registration using VoxelMorph and VTN. We experimented further by strategically using the available datasets through pretraining and fine tuning with different splits of data. We found that to create a generalisable model, pretraining with CE data and fine tuning with non-CE data gave the best result. This interesting find could be expanded to other deep learning based image processing tasks with DCE-MRI and provide significant improvements to the models performance

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Filtering, Segmentation and ultrasound images tracking. : clinical applications.

La réalisation des néphrolithotomies percutanées est essentiellement conditionnée par la qualité dela ponction calicièle préalable. En effet, en cas d’échec de celle-ci, l’intervention ne peut avoir lieu.Réalisée le plus souvent sous échographie, sa qualité est fortement conditionnée par celle du retouréchographique, considéré comme essentiel par la deuxième consultation internationale sur la lithiase pour limiter les saignements consécutifs à l’intervention.L’imagerie échographique est largement plébiscitée en raison de son faible coût, de l’innocuité del’examen, liée à son caractère non invasif, de sa portabilité ainsi que de son excellente résolutiontemporelle ; elle possède toutefois une très faible résolution spatiale et souffre de nombreux artefacts tels que la mauvaise résolution des images, un fort bruit apparent et une forte dépendance àl’opérateur.L’objectif de cette thèse est de concevoir une méthode de filtrage des données échographiques ainsiqu’une méthode de segmentation et de suivi du rein sur des séquences ultrasonores, dans le butd’améliorer les conditions d’exécution d’interventions chirurgicales telles que les néphrolithotomiespercutanées.Le filtrage des données, soumis et publié dans SPIE 2010, est réalisé en exploitant le mode deformation des images : le signal radiofréquence est filtré directement, avant même la formation del’image 2D finale. Pour ce faire, nous utilisons une méthode basée sur les ondelettes, en seuillantdirectement les coefficients d’ondelettes aux différentes échelles à partir d’un algorithme de typesplit and merge appliqué avant reconstruction de l’image 2D.La méthode de suivi développée (une étude préliminaire a été publiée dans SPIE 2009), exploiteun premier contour fourni par le praticien pour déterminer, en utilisant des informations purementlocales, la position du contour sur l’image suivante de la séquence. L’image est transformée pourne plus être qu’un ensemble de vignettes caractérisées par leurs critères de texture et une premièresegmentation basée région est effectuée sur cette image des vignettes. Cette première étape effectuée, le contour de l’image précédente de la séquence est utilisé comme initialisation afin de recalculer le contour de l’image courante sur l’image des vignettes segmentée. L’utilisation d’informations locales nous a permis de développer une méthode facilement parallélisable, ce qui permettra de travailler dans une optique temps réel.La validation de la méthode de filtrage a été réalisée sur des signaux radiofréquence simulés. Laméthode a été comparée à différents algorithmes de l’état de l’art en terme de ratio signal sur bruitet de calcul de USDSAI. Les résultats ont montré la qualité de la méthode proposée comparativement aux autres. La méthode de segmentation, quant-à elle, a été validée sans filtrage préalable, sur des séquences 2D réelles pour un temps d’exécution sans optimisation, inférieur à la minute pour des images 512*512.The achievement of percutaneous nephrolithotomies is mainly conditioned by the quality of the initial puncture. Indeed, if it is not well performed , the intervention cannot be fulfilled.In order to make it more accurate this puncture is often realized under ultrasound control. Thus the quality of the ultrasound feedback is very critical and when clear enough it greatly helps limiting bleeding.Thanks to its low cost, its non invasive nature and its excellent temporal resolution, ultrasound imaging is considered very appropriate for this purpose. However, this solution is not perfect it is characterized by a low spatial resolution and the results present artifacts due to a poor image resolution (compared to images provided by some other medical devices) and speckle noise.Finally this technic is greatly operator dependent.Aims of the work presented here are, first to design a filtering method for ultrasound data and then to develop a segmentation and tracking algorithm on kidney ultrasound sequences in order to improve the executing conditions of surgical interventions such as percutaneous nephrolithotomies.The results about data filtering was submitted and published in SPIE 2010. The method uses the way ultrasound images are formed to filter them: the radiofrequency signal is directly filtered, before the bi-dimensional reconstruction. In order to do so, a wavelet based method, thresholding directly wavelet coefficients at different scales has been developed. The method is based on a “split and merge” like algorithm.The proposed algorithm was validated on simulated signals and its results compared to the ones obtained with different state of the art algorithms. Experiments show that this new proposed approach is better.The segmentation and tracking method (of which a prospective study was published in SPIE 2009) uses a first contour given by a human expert and then determines, using only local informations, the position of the next contour on the following image of the sequence. The tracking technique was validated on real data with no previous filtering and successfully compared with state of the art methods

Filtrage, segmentation et suivi d'images échographiques : applications cliniques

The achievement of percutaneous nephrolithotomies is mainly conditioned by the quality of the initial puncture. Indeed, if it is not well performed , the intervention cannot be fulfilled.In order to make it more accurate this puncture is often realized under ultrasound control. Thus the quality of the ultrasound feedback is very critical and when clear enough it greatly helps limiting bleeding.Thanks to its low cost, its non invasive nature and its excellent temporal resolution, ultrasound imaging is considered very appropriate for this purpose. However, this solution is not perfect it is characterized by a low spatial resolution and the results present artifacts due to a poor image resolution (compared to images provided by some other medical devices) and speckle noise.Finally this technic is greatly operator dependent.Aims of the work presented here are, first to design a filtering method for ultrasound data and then to develop a segmentation and tracking algorithm on kidney ultrasound sequences in order to improve the executing conditions of surgical interventions such as percutaneous nephrolithotomies.The results about data filtering was submitted and published in SPIE 2010. The method uses the way ultrasound images are formed to filter them: the radiofrequency signal is directly filtered, before the bi-dimensional reconstruction. In order to do so, a wavelet based method, thresholding directly wavelet coefficients at different scales has been developed. The method is based on a “split and merge” like algorithm.The proposed algorithm was validated on simulated signals and its results compared to the ones obtained with different state of the art algorithms. Experiments show that this new proposed approach is better.The segmentation and tracking method (of which a prospective study was published in SPIE 2009) uses a first contour given by a human expert and then determines, using only local informations, the position of the next contour on the following image of the sequence. The tracking technique was validated on real data with no previous filtering and successfully compared with state of the art methods.La réalisation des néphrolithotomies percutanées est essentiellement conditionnée par la qualité dela ponction calicièle préalable. En effet, en cas d’échec de celle-ci, l’intervention ne peut avoir lieu.Réalisée le plus souvent sous échographie, sa qualité est fortement conditionnée par celle du retouréchographique, considéré comme essentiel par la deuxième consultation internationale sur la lithiase pour limiter les saignements consécutifs à l’intervention.L’imagerie échographique est largement plébiscitée en raison de son faible coût, de l’innocuité del’examen, liée à son caractère non invasif, de sa portabilité ainsi que de son excellente résolutiontemporelle ; elle possède toutefois une très faible résolution spatiale et souffre de nombreux artefacts tels que la mauvaise résolution des images, un fort bruit apparent et une forte dépendance àl’opérateur.L’objectif de cette thèse est de concevoir une méthode de filtrage des données échographiques ainsiqu’une méthode de segmentation et de suivi du rein sur des séquences ultrasonores, dans le butd’améliorer les conditions d’exécution d’interventions chirurgicales telles que les néphrolithotomiespercutanées.Le filtrage des données, soumis et publié dans SPIE 2010, est réalisé en exploitant le mode deformation des images : le signal radiofréquence est filtré directement, avant même la formation del’image 2D finale. Pour ce faire, nous utilisons une méthode basée sur les ondelettes, en seuillantdirectement les coefficients d’ondelettes aux différentes échelles à partir d’un algorithme de typesplit and merge appliqué avant reconstruction de l’image 2D.La méthode de suivi développée (une étude préliminaire a été publiée dans SPIE 2009), exploiteun premier contour fourni par le praticien pour déterminer, en utilisant des informations purementlocales, la position du contour sur l’image suivante de la séquence. L’image est transformée pourne plus être qu’un ensemble de vignettes caractérisées par leurs critères de texture et une premièresegmentation basée région est effectuée sur cette image des vignettes. Cette première étape effectuée, le contour de l’image précédente de la séquence est utilisé comme initialisation afin de recalculer le contour de l’image courante sur l’image des vignettes segmentée. L’utilisation d’informations locales nous a permis de développer une méthode facilement parallélisable, ce qui permettra de travailler dans une optique temps réel.La validation de la méthode de filtrage a été réalisée sur des signaux radiofréquence simulés. Laméthode a été comparée à différents algorithmes de l’état de l’art en terme de ratio signal sur bruitet de calcul de USDSAI. Les résultats ont montré la qualité de la méthode proposée comparativement aux autres. La méthode de segmentation, quant-à elle, a été validée sans filtrage préalable, sur des séquences 2D réelles pour un temps d’exécution sans optimisation, inférieur à la minute pour des images 512*512

Shape-based multi-region segmentation framework: application to 3D infants MRI data

International audience<p>This paper presents a novel shape-guided multi-region variational region growing framework for extracting simultaneously thoracic and abdominal organs on 3D infants whole body MRI. Due to the inherent low qualityof these data, classical segmentation methods tend to fail at the multi-segmentation task. To compensate forthe low resolution and the lack of contrast and to enable the simultaneous segmentation of multiple organs, weintroduce a segmentation framework on a graph of supervoxels that combines supervoxels intensity distributionweighted by gradient vector flow value and a shape prior per tissue. The intensity-based homogeneity criteriaand the shape prior, encoded using Legendre moments, are added as energy terms in the functional to be op-timized. The intensity-based energy is computed using both local (voxel value) and global (neigboring regionsmean values, adjacent voxels values and distance to the neighboring regions) criteria. Inter-region conflict resolution is handled using a weighted Voronoi decomposition method, the weights being determined using tissuesdensities. The energy terms of the global energy equation are weighted using an information on growth directionand on gradient vector flow value in order to either guide the segmentation toward the image natural edges ifit is consistent with image and shape prior terms or enforce the shape prior term otherwise. Results on 3Dinfants MRI data are presented and compared to a set of manual segmentations. Both visual comparison andquantitative measurements show good results.</p

Segmentation of embryonic and fetal 3D ultrasound images based on pixel intensity distributions and shape priors

International audience<p>This paper presents a novel variational segmentation framework combiningshape priors and parametric intensity distribution modeling for extractingthe fetal envelope on 3D obstetric ultrasound images. To overcome issuesrelated to poor image quality and missing boundaries, we inject three types ofinformation in the segmentation process: tissue-specic parametric modelingof pixel intensities, a shape prior for the fetal envelope and a shape modelof the fetus' back. The shape prior is encoded with Legendre moments andused to constraint the evolution of a level-set function. The back model isused to post-process the segmented fetal envelope. Results are presentedon 3D ultrasound data and compared to a set of manual segmentations.The robustness of the algorithm is studied, and both visual and quantitativecomparisons show satisfactory results obtained by the proposed method onthe tested dataset.</p

Etude de la reproductibilité des interprétations d'IRM cérébrales néonatales

National audienc

Segmentation of fetal envelope from 3D Ultrasound images based on pixel intensity statistical distribution and shape priors

International audienc

3D articulated growth model of the fetus skeleton, envelope and soft tissues

International audience<p>Fetal dosimetry studies require thedevelopment of accurate 3D models of the fe-tus. This paper proposes a 3D articulated fe-tal growth model including skeleton, body en-velope, brain and lungs based on medical im-ages of 10 dierent fetuses acquired in clinicalroutine. The structures of interest were semi-manually segmented from the images and sur-face meshes were generated. A generic mesh ofeach structure has been deformed towards thesegmented ones. By interpolating linearly be-tween the subjects of the database, each struc-ture can be estimated at any age and in anyposition. This process results in an automatedmodel, the operator being only required tospecify the age and position of the desired es-timated fetus.</p

Infants and young children modeling method for numerical dosimetry studies: application to plane wave exposure

International audience<p>Numerical dosimetry studies require the development of accuratenumerical 3D models of the human body. This paper proposes a novel methodfor building 3D heterogeneous young children models combining results obtainedfrom a semi-automatic multi-organ segmentation algorithm and an anatomydeformation method. The data consist of 3D Magnetic Resonance Images, whichare first segmented to obtain a set of initial tissues. A deformation procedureguided by the segmentation results is then developed in order to obtain 5 youngchildren models ranging from the age of 5 to 37 months. By constraining thedeformation of an older child model toward a younger one using segmentationresults, we assure the anatomical realism of the models. Using the proposedframework, five models, containing thirteen tissues, are built. Three of thesemodels are used in a prospective dosimetry study to analyze young child exposureto radiofrequency electromagnetic fields. The results lean to show the existence ofa relationship between age and whole body exposure. The results also highlightthe necessity to specifically study and develop measurements of child tissuesdielectric properties.</p