Semi-Supervised Bladder Tissue Classification in Multi-Domain Endoscopic Images.

OBJECTIVE: Accurate visual classification of bladder tissue during Trans-Urethral Resection of Bladder Tumor (TURBT) procedures is essential to improve early cancer diagnosis and treatment. During TURBT interventions, White Light Imaging (WLI) and Narrow Band Imaging (NBI) techniques are used for lesion detection. Each imaging technique provides diverse visual information that allows clinicians to identify and classify cancerous lesions. Computer vision methods that use both imaging techniques could improve endoscopic diagnosis. We address the challenge of tissue classification when annotations are available only in one domain, in our case WLI, and the endoscopic images correspond to an unpaired dataset, i.e. there is no exact equivalent for every image in both NBI and WLI domains. METHOD: We propose a semi-surprised Generative Adversarial Network (GAN)-based method composed of three main components: a teacher network trained on the labeled WLI data; a cycle-consistency GAN to perform unpaired image-to-image translation, and a multi-input student network. To ensure the quality of the synthetic images generated by the proposed GAN we perform a detailed quantitative, and qualitative analysis with the help of specialists. CONCLUSION: The overall average classification accuracy, precision, and recall obtained with the proposed method for tissue classification are 0.90, 0.88, and 0.89 respectively, while the same metrics obtained in the unlabeled domain (NBI) are 0.92, 0.64, and 0.94 respectively. The quality of the generated images is reliable enough to deceive specialists. SIGNIFICANCE: This study shows the potential of using semi-supervised GAN-based bladder tissue classification when annotations are limited in multi-domain data.

In Vitro Antibody Quantification with Hyperspectral Imaging in a Large Field of View for Clinical Applications.

Hyperspectral imaging (HSI) is a non-invasive, contrast-free optical-based tool that has recently been applied in medical and basic research fields. The opportunity to use HSI to identify exogenous tumor markers in a large field of view (LFOV) could increase precision in oncological diagnosis and surgical treatment. In this study, the anti-high mobility group B1 (HMGB1) labeled with Alexa fluorophore (647 nm) was used as the target molecule. This is the proof-of-concept of HSI's ability to quantify antibodies via an in vitro setting. A first test was performed to understand whether the relative absorbance provided by the HSI camera was dependent on volume at a 1:1 concentration. A serial dilution of 1:1, 10, 100, 1000, and 10,000 with phosphatase-buffered saline (PBS) was then used to test the sensitivity of the camera at the minimum and maximum volumes. For the analysis, images at 640 nm were extracted from the hypercubes according to peak signals matching the specificities of the antibody manufacturer. The results showed a positive correlation between relative absorbance and volume (r = 0.9709, p = 0.0013). The correlation between concentration and relative absorbance at min (1 µL) and max (20 µL) volume showed r = 0.9925, p < 0.0001, and r = 0.9992, p < 0.0001, respectively. These results demonstrate the HSI potential in quantifying HMGB1, hence deserving further studies in ex vivo and in vivo settings.

Surgical Models of Liver Regeneration in Pigs: A Practical Review of the Literature for Researchers.

The remarkable capacity of regeneration of the liver is well known, although the involved mechanisms are far from being understood. Furthermore, limits concerning the residual functional mass of the liver remain critical in both fields of hepatic resection and transplantation. The aim of the present study was to review the surgical experiments regarding liver regeneration in pigs to promote experimental methodological standardization. The Pubmed, Medline, Scopus, and Cochrane Library databases were searched. Studies evaluating liver regeneration through surgical experiments performed on pigs were included. A total of 139 titles were screened, and 41 articles were included in the study, with 689 pigs in total. A total of 29 studies (71% of all) had a survival design, with an average study duration of 13 days. Overall, 36 studies (88%) considered partial hepatectomy, of which four were an associating liver partition and portal vein ligation for staged hepatectomy (ALPPS). Remnant liver volume ranged from 10% to 60%. Only 2 studies considered a hepatotoxic pre-treatment, while 25 studies evaluated additional liver procedures, such as stem cell application, ischemia/reperfusion injury, portal vein modulation, liver scaffold application, bio-artificial, and pharmacological liver treatment. Only nine authors analysed how cytokines and growth factors changed in response to liver resection. The most used imaging system to evaluate liver volume was CT-scan volumetry, even if performed only by nine authors. The pig represents one of the best animal models for the study of liver regeneration. However, it remains a mostly unexplored field due to the lack of experiments reproducing the chronic pathological aspects of the liver and the heterogeneity of existing studies.

Spatiotemporal Modeling of Grip Forces Captures Proficiency in Manual Robot Control.

New technologies for monitoring grip forces during hand and finger movements in non-standard task contexts have provided unprecedented functional insights into somatosensory cognition. Somatosensory cognition is the basis of our ability to manipulate and transform objects of the physical world and to grasp them with the right amount of force. In previous work, the wireless tracking of grip-force signals recorded from biosensors in the palm of the human hand has permitted us to unravel some of the functional synergies that underlie perceptual and motor learning under conditions of non-standard and essentially unreliable sensory input. This paper builds on this previous work and discusses further, functionally motivated, analyses of individual grip-force data in manual robot control. Grip forces were recorded from various loci in the dominant and non-dominant hands of individuals with wearable wireless sensor technology. Statistical analyses bring to the fore skill-specific temporal variations in thousands of grip forces of a complete novice and a highly proficient expert in manual robot control. A brain-inspired neural network model that uses the output metric of a self-organizing pap with unsupervised winner-take-all learning was run on the sensor output from both hands of each user. The neural network metric expresses the difference between an input representation and its model representation at any given moment in time and reliably captures the differences between novice and expert performance in terms of grip-force variability.Functionally motivated spatiotemporal analysis of individual average grip forces, computed for time windows of constant size in the output of a restricted amount of task-relevant sensors in the dominant (preferred) hand, reveal finger-specific synergies reflecting robotic task skill. The analyses lead the way towards grip-force monitoring in real time. This will permit tracking task skill evolution in trainees, or identify individual proficiency levels in human robot-interaction, which represents unprecedented challenges for perceptual and motor adaptation in environmental contexts of high sensory uncertainty. Cross-disciplinary insights from systems neuroscience and cognitive behavioral science, and the predictive modeling of operator skills using parsimonious Artificial Intelligence (AI), will contribute towards improving the outcome of new types of surgery, in particular the single-port approaches such as NOTES (Natural Orifice Transluminal Endoscopic Surgery) and SILS (Single-Incision Laparoscopic Surgery).

Distortion and instability compensation with deep learning for rotational scanning endoscopic optical coherence tomography.

Optical Coherence Tomography (OCT) is increasingly used in endoluminal procedures since it provides high-speed and high resolution imaging. Distortion and instability of images obtained with a proximal scanning endoscopic OCT system are significant due to the motor rotation irregularity, the friction between the rotating probe and outer sheath and synchronization issues. On-line compensation of artefacts is essential to ensure image quality suitable for real-time assistance during diagnosis or minimally invasive treatment. In this paper, we propose a new online correction method to tackle both B-scan distortion, video stream shaking and drift problem of endoscopic OCT linked to A-line level image shifting. The proposed computational approach for OCT scanning video correction integrates a Convolutional Neural Network (CNN) to improve the estimation of azimuthal shifting of each A-line. To suppress the accumulative error of integral estimation we also introduce another CNN branch to estimate a dynamic overall orientation angle. We train the network with semi-synthetic OCT videos by intentionally adding rotational distortion into real OCT scanning images. The results show that networks trained on this semi-synthetic data generalize to stabilize real OCT videos, and the algorithm efficacy is demonstrated on both ex vivo and in vivo data, where strong scanning artifacts are successfully corrected.

Does interventional MRI-guided brain cryotherapy cause a blood-brain barrier disruption? Radiological analysis and perspectives.

Glioblastoma is the most common primary malignant brain tumor with an incidence of 5/100,000 inhabitants/year and a 5-year survival rate of 6.8%. Despite recent advances in the molecular biology understanding of glioblastoma, CNS chemotherapy remains challenging because of the impermeable blood-brain barrier (BBB). Interventional MRI-guided brain cryotherapy (IMRgC) is technique that creates a tissue lesion by making a severe targeted hypothermia and possibly a BBB disruption. This study goal was to analyze the effect of IMRgC on human BBB glioblastoma through its gadolinium enhancing features. All patients harboring a local glioblastoma recurrence and meeting all the inclusion criteria were consecutively included into this retrospective study during a 2-year period. The primary endpoint was to analyze the modification of the gadolinium enhancement on MRI T1 sequences using MR perfusion weighted images during follow-up. The secondary endpoint was to assess any ischemic/hemorrhagic complication following cryotherapy procedure using diffusion weighted imaging (DWI), susceptibility weighted imaging (SWI), or fluid-attenuated inversion recovery (FLAIR). Among the 6 patients studied, all (100%) showed a BBB disruption on the cryotherapy site through the analysis of the perfusion weighted images with an average delay of 2.83 months following the procedure. The gadolinium enhancement located around the cavity then spontaneously decreased in 4/6 patients (67%). No ischemic or hemorrhagic complication was recorded. This study confirms the IMRgC capacity to disrupt BBB as already suggested by the literature. IMRgC might represent a new option in the management of GBM allowing the combined effect of direct cryoablation and enhanced chemotherapy.

Using spatial-temporal ensembles of convolutional neural networks for lumen segmentation in ureteroscopy.

PURPOSE: Ureteroscopy is an efficient endoscopic minimally invasive technique for the diagnosis and treatment of upper tract urothelial carcinoma. During ureteroscopy, the automatic segmentation of the hollow lumen is of primary importance, since it indicates the path that the endoscope should follow. In order to obtain an accurate segmentation of the hollow lumen, this paper presents an automatic method based on convolutional neural networks (CNNs). METHODS: The proposed method is based on an ensemble of 4 parallel CNNs to simultaneously process single and multi-frame information. Of these, two architectures are taken as core-models, namely U-Net based in residual blocks ([Formula: see text]) and Mask-RCNN ([Formula: see text]), which are fed with single still-frames I(t). The other two models ([Formula: see text], [Formula: see text]) are modifications of the former ones consisting on the addition of a stage which makes use of 3D convolutions to process temporal information. [Formula: see text], [Formula: see text] are fed with triplets of frames ([Formula: see text], I(t), [Formula: see text]) to produce the segmentation for I(t). RESULTS: The proposed method was evaluated using a custom dataset of 11 videos (2673 frames) which were collected and manually annotated from 6 patients. We obtain a Dice similarity coefficient of 0.80, outperforming previous state-of-the-art methods. CONCLUSION: The obtained results show that spatial-temporal information can be effectively exploited by the ensemble model to improve hollow lumen segmentation in ureteroscopic images. The method is effective also in the presence of poor visibility, occasional bleeding, or specular reflections.

Steerable OCT catheter for real-time assistance during teleoperated endoscopic treatment of colorectal cancer.

When detected early, colorectal cancer can be treated with minimally invasive flexible endoscopy. However, since only specialized experts can delineate margins and perform endoscopic resections of lesions, patients still often undergo colon resections. To better assist in the performance of surgical tasks, a robotized flexible interventional endoscope was previously developed, having two additional side channels for surgical instrument. We propose to enhance the imaging capabilities of this device by combining it with optical coherence tomography (OCT). For this purpose, we have developed a new steerable OCT instrument with an outer diameter of 3.5 mm. The steerable instrument is terminated with a 2 cm long transparent sheath to allow three-dimensional OCT imaging using a side-focusing optical probe with two external scanning actuators. The instrument is connected to an OCT imaging system built around the OCT Axsun engine, with a 1310 nm center wavelength swept source laser and 100 kHz A-line rate. Once inserted in one of the side channels of the robotized endoscope, bending, rotation and translation of the steerable OCT instrument can be controlled by a physician using a joystick. Ex vivo and in vivo tests show that the novel, steerable and teleoperated OCT device enhances dexterity, allowing for inspection of the surgical field without the need for changing the position of the main endoscope.

Sensors for Expert Grip Force Profiling: Towards Benchmarking Manual Control of a Robotic Device for Surgical Tool Movements.

STRAS (Single access Transluminal Robotic Assistant for Surgeons) is a new robotic system based on the Anubis® platform of Karl Storz for application to intra-luminal surgical procedures. Pre-clinical testing of STRAS has recently permitted to demonstrate major advantages of the system in comparison with classic procedures. Benchmark methods permitting to establish objective criteria for 'expertise' need to be worked out now to effectively train surgeons on this new system in the near future. STRAS consists of three cable-driven sub-systems, one endoscope serving as guide, and two flexible instruments. The flexible instruments have three degrees of freedom and can be teleoperated by a single user via two specially designed master interfaces. In this study, small force sensors sewn into a wearable glove to ergonomically fit the master handles of the robotic system were employed for monitoring the forces applied by an expert and a trainee (complete novice) during all the steps of surgical task execution in a simulator task (4-step-pick-and-drop). Analysis of grip-force profiles is performed sensor by sensor to bring to the fore specific differences in handgrip force profiles in specific sensor locations on anatomically relevant parts of the fingers and hand controlling the master/slave system.

Targetability of osteoid osteomas and bone metastases by MR-guided high intensity focused ultrasound (MRgHIFU).

PURPOSE: To retrospectively evaluate the suitability of MRgHIFU for osteoid osteomas (OOs) and bone metastases in patients who underwent minimally-invasive percutaneous thermal ablation. MATERIALS AND METHODS: One hundred and sixty-seven lesions (115 metastases and 52 OOs) treated percutaneously between October 2014 and June 2017 were retrospectively analyzed. Tumors were located in the spine or sacrum (54), pelvis (43), limbs (50), ribs (17) and sternum (3). Tumor volume, matrix, anatomical environment and need for protection of surrounding structures or consolidation were assessed. Cases were classified into three categories: (a) lesions suitable for MRgHIFU therapy alone; (b) lesions suitable for MRgHIFU if protection of surrounding structures and/or bone consolidation is performed; (c) lesions not suitable for MRgHIFU. RESULTS: Twenty-six (50%) of OOs were classified as suitable for MRgHIFU alone and 17 (32.7%) as suitable for MRgHIFU with hydro-dissection. Matrix of treatable OOs was sclerotic (19), lytic (15) or mixed (9), with mean volume 0.56 cm3. Forty-one (35.7%) of metastases were classified as suitable for MRgHIFU alone and 43 (37.4%) as suitable with hydro-dissection and/or consolidation. Matrix of metastases was sclerotic (13), lytic (37) or mixed (34), with mean volume 71.9 cm3. Mean depth of targetable lesions was 50.9 ± 28.4 mm. 97.7% of pelvic lesions and 94% of peripheral bone lesions were targetable by HIFU. 66.6% of spinal or sacral lesions were considered untreatable. CONCLUSION: MRgHIFU cannot be systematically performed non-invasively on bone tumors. Combination with minimally-invasive thermo-protective techniques may increase the number of eligible cases.

A Novel Telemanipulated Robotic Assistant for Surgical Endoscopy: Preclinical Application to ESD.

OBJECTIVE: Minimally invasive surgical interventions in the gastrointestinal tract, such as endoscopic submucosal dissection (ESD), are very difficult for surgeons when performed with standard flexible endoscopes. Robotic flexible systems have been identified as a solution to improve manipulation. However, only a few such systems have been brought to preclinical trials as of now. As a result, novel robotic tools are required. METHODS: We developed a telemanipulated robotic device, called STRAS, which aims to assist surgeons during intraluminal surgical endoscopy. This is a modular system, based on a flexible endoscope and flexible instruments, which provides 10 degrees of freedom (DoFs). The modularity allows the user to easily set up the robot and to navigate toward the operating area. The robot can then be teleoperated using master interfaces specifically designed to intuitively control all available DoFs. STRAS capabilities have been tested in laboratory conditions and during preclinical experiments. RESULTS: We report 12 colorectal ESDs performed in pigs, in which large lesions were successfully removed. Dissection speeds are compared with those obtained in similar conditions with the manual Anubiscope platform from Karl Storz. We show significant improvements ( ). CONCLUSION: These experiments show that STRAS (v2) provides sufficient DoFs, workspace, and force to perform ESD, that it allows a single surgeon to perform all the surgical tasks and those performances are improved with respect to manual systems. SIGNIFICANCE: The concepts developed for STRAS are validated and could bring new tools for surgeons to improve comfort, ease, and performances for intraluminal surgical endoscopy.

Seeing virtual while acting real: Visual display and strategy effects on the time and precision of eye-hand coordination.

Effects of different visual displays on the time and precision of bare-handed or tool-mediated eye-hand coordination were investigated in a pick-and-place-task with complete novices. All of them scored well above average in spatial perspective taking ability and performed the task with their dominant hand. Two groups of novices, four men and four women in each group, had to place a small object in a precise order on the centre of five targets on a Real-world Action Field (RAF), as swiftly as possible and as precisely as possible, using a tool or not (control). Each individual session consisted of four visual display conditions. The order of conditions was counterbalanced between individuals and sessions. Subjects looked at what their hands were doing 1) directly in front of them ("natural" top-down view) 2) in top-down 2D fisheye view 3) in top-down undistorted 2D view or 4) in 3D stereoscopic top-down view (head-mounted OCULUS DK 2). It was made sure that object movements in all image conditions matched the real-world movements in time and space. One group was looking at the 2D images with the monitor positioned sideways (sub-optimal); the other group was looking at the monitor placed straight ahead of them (near-optimal). All image viewing conditions had significantly detrimental effects on time (seconds) and precision (pixels) of task execution when compared with "natural" direct viewing. More importantly, we find significant trade-offs between time and precision between and within groups, and significant interactions between viewing conditions and manipulation conditions. The results shed new light on controversial findings relative to visual display effects on eye-hand coordination, and lead to conclude that differences in camera systems and adaptive strategies of novices are likely to explain these.

Endoluminal surgical triangulation 2.0: A new flexible surgical robot. Preliminary pre-clinical results with colonic submucosal dissection.

BACKGROUND: Complex intraluminal surgical interventions of the gastrointestinal tract are challenging due to the limitation of existing instruments. Our group has developed a master-slave robotic flexible endoscopic platform that provides instrument triangulation in an endoluminal environment. MATERIALS AND METHODS: Colonic endoscopic submucosal dissections (ESD) were carried out in eight pigs. The robot was introduced transanally. A combination of adapted tele-operated instruments was used. Specimens were inspected and measured. RESULTS: Out of 18 ESDs in total, 12 were successfully completed. Among the completed procedures, two perforations and one system failure occurred and were managed intraoperatively. There was no major bleeding. Mean size of the removed specimens was 18.2 ± 9.8 cm2 and mean total procedure time was 73 ± 35.5 min. CONCLUSIONS: Experimental colorectal ESDs using the flexible surgical robot were feasible and reflected a short learning curve. After some technical improvements the system might allow for a wider adoption of complex endoluminal surgical procedures.

Magnetic resonance evaluation of cardiac thrombi and masses by T1 and T2 mapping: an observational study.

The purpose of this work was to evaluate CMR T1 and T2 mapping sequences in patients with intracardiac thrombi and masses in order to assess T1 and T2 relaxometry usefulness and to allow better etiological diagnosis. This observational study of patients scheduled for routine CMR was performed from September 2014 to August 2015. All patients referred to our department for a 1.5 T CMR were screened to participate. T1 mapping were acquired before and after Gadolinium injection; T2 mapping images were obtained before injection. 41 patients were included. 22 presented with cardiac thrombi and 19 with cardiac masses. The native T1 of thrombi was 1037 ± 152 ms (vs 1032 ± 39 ms for myocardium, p = 0.88; vs 1565 ± 88 ms for blood pool, p < 0.0001). T2 were 74 ± 13 ms (vs 51 ± 3 ms for myocardium, p < 0.0001; vs 170 ± 32 ms for blood pool, p < 0.0001). Recent thrombi had a native T1 shorter than old thrombi (911 ± 177 vs 1169 ± 107 ms, p = 0.01). The masses having a shorter T1 than the myocardium were lipomas (278 ± 29 ms), calcifications (621 ± 218 ms), and melanoma (736 ms). All other masses showed T1 values higher than myocardial T1, with T2 consistently >70 ms. T1 and T2 mapping CMR sequences can be useful and represent a new approach for the evaluation of cardiac thrombi and masses.

K-space data processing for magnetic resonance elastography (MRE).

OBJECTIVE: Magnetic resonance elastography (MRE) requires substantial data processing based on phase image reconstruction, wave enhancement, and inverse problem solving. The objective of this study is to propose a new, fast MRE method based on MR raw data processing, particularly adapted to applications requiring fast MRE measurement or high elastogram update rate. MATERIALS AND METHODS: The proposed method allows measuring tissue elasticity directly from raw data without prior phase image reconstruction and without phase unwrapping. Experimental feasibility is assessed both in a gelatin phantom and in the liver of a porcine model in vivo. Elastograms are reconstructed with the raw MRE method and compared to those obtained using conventional MRE. In a third experiment, changes in elasticity are monitored in real-time in a gelatin phantom during its solidification by using both conventional MRE and raw MRE. RESULTS: The raw MRE method shows promising results by providing similar elasticity values to the ones obtained with conventional MRE methods while decreasing the number of processing steps and circumventing the delicate step of phase unwrapping. Limitations of the proposed method are the influence of the magnitude on the elastogram and the requirement for a minimum number of phase offsets. CONCLUSION: This study demonstrates the feasibility of directly reconstructing elastograms from raw data.

Articulated clinician detection using 3D pictorial structures on RGB-D data.

Reliable human pose estimation (HPE) is essential to many clinical applications, such as surgical workflow analysis, radiation safety monitoring and human-robot cooperation. Proposed methods for the operating room (OR) rely either on foreground estimation using a multi-camera system, which is a challenge in real ORs due to color similarities and frequent illumination changes, or on wearable sensors or markers, which are invasive and therefore difficult to introduce in the room. Instead, we propose a novel approach based on Pictorial Structures (PS) and on RGB-D data, which can be easily deployed in real ORs. We extend the PS framework in two ways. First, we build robust and discriminative part detectors using both color and depth images. We also present a novel descriptor for depth images, called histogram of depth differences (HDD). Second, we extend PS to 3D by proposing 3D pairwise constraints and a new method that makes exact inference tractable. Our approach is evaluated for pose estimation and clinician detection on a challenging RGB-D dataset recorded in a busy operating room during live surgeries. We conduct series of experiments to study the different part detectors in conjunction with the various 2D or 3D pairwise constraints. Our comparisons demonstrate that 3D PS with RGB-D part detectors significantly improves the results in a visually challenging operating environment.

EndoNet: A Deep Architecture for Recognition Tasks on Laparoscopic Videos.

Surgical workflow recognition has numerous potential medical applications, such as the automatic indexing of surgical video databases and the optimization of real-time operating room scheduling, among others. As a result, surgical phase recognition has been studied in the context of several kinds of surgeries, such as cataract, neurological, and laparoscopic surgeries. In the literature, two types of features are typically used to perform this task: visual features and tool usage signals. However, the used visual features are mostly handcrafted. Furthermore, the tool usage signals are usually collected via a manual annotation process or by using additional equipment. In this paper, we propose a novel method for phase recognition that uses a convolutional neural network (CNN) to automatically learn features from cholecystectomy videos and that relies uniquely on visual information. In previous studies, it has been shown that the tool usage signals can provide valuable information in performing the phase recognition task. Thus, we present a novel CNN architecture, called EndoNet, that is designed to carry out the phase recognition and tool presence detection tasks in a multi-task manner. To the best of our knowledge, this is the first work proposing to use a CNN for multiple recognition tasks on laparoscopic videos. Experimental comparisons to other methods show that EndoNet yields state-of-the-art results for both tasks.

Getting nowhere fast: trade-off between speed and precision in training to execute image-guided hand-tool movements.

BACKGROUND: The speed and precision with which objects are moved by hand or hand-tool interaction under image guidance depend on a specific type of visual and spatial sensorimotor learning. Novices have to learn to optimally control what their hands are doing in a real-world environment while looking at an image representation of the scene on a video monitor. Previous research has shown slower task execution times and lower performance scores under image-guidance compared with situations of direct action viewing. The cognitive processes for overcoming this drawback by training are not yet understood. METHODS: We investigated the effects of training on the time and precision of direct view versus image guided object positioning on targets of a Real-world Action Field (RAF). Two men and two women had to learn to perform the task as swiftly and as precisely as possible with their dominant hand, using a tool or not and wearing a glove or not. Individuals were trained in sessions of mixed trial blocks with no feed-back. RESULTS: As predicted, image-guidance produced significantly slower times and lesser precision in all trainees and sessions compared with direct viewing. With training, all trainees get faster in all conditions, but only one of them gets reliably more precise in the image-guided conditions. Speed-accuracy trade-offs in the individual performance data show that the highest precision scores and steepest learning curve, for time and precision, were produced by the slowest starter. Fast starters produced consistently poorer precision scores in all sessions. The fastest starter showed no sign of stable precision learning, even after extended training. CONCLUSIONS: Performance evolution towards optimal precision is compromised when novices start by going as fast as they can. The findings have direct implications for individual skill monitoring in training programmes for image-guided technology applications with human operators.

Interventional MR elastography for MRI-guided percutaneous procedures.

PURPOSE: MRI-guided thermal ablations require reliable monitoring methods to ensure complete destruction of the diseased tissue while avoiding damage to the surrounding healthy tissue. Based on the fact that thermal ablations result in substantial changes in biomechanical properties, interventional MR elastography (MRE) dedicated to the monitoring of MR-guided thermal therapies is proposed here. METHODS: Interventional MRE consists of a needle MRE driver, a fast and interactive gradient echo pulse sequence with motion encoding, and an inverse problem solver in real-time. This complete protocol was tested in vivo on swine and the ability to monitor elasticity changes in real-time was assessed in phantom. RESULTS: Thanks to a short repetition time, a reduction of the number of phase-offsets and the use of a sliding window, one refreshed elastogram was provided every 2.56 s for an excitation frequency of 100 Hz. In vivo elastograms of swine liver were successfully provided in real-time during one breath-hold. Changes of elasticity were successfully monitored in a phantom during its gelation with the same elastogram frame rate. CONCLUSION: This study demonstrates the ability of detecting elasticity changes in real-time and providing elastograms in vivo with interventional MRE that could be used for the monitoring of thermal ablations.