Intraoperative US Images Research Articles

Automatic hepatic tumor segmentation in intra-operative ultrasound: a supervised deep-learning approach.

Training and evaluation of the performance of a supervised deep-learning model for the segmentation of hepatic tumors from intraoperative US (iUS) images, with the purpose of improving the accuracy of tumor margin assessment during liver surgeries and the detection of lesions during colorectal surgeries. In this retrospective study, a U-Net network was trained with the nnU-Net framework in different configurations for the segmentation of CRLM from iUS. The model was trained on B-mode intraoperative hepatic US images, hand-labeled by an expert clinician. The model was tested on an independent set of similar images. The average age of the study population was 61.9 ± 9.9 years. Ground truth for the test set was provided by a radiologist, and three extra delineation sets were used for the computation of inter-observer variability. The presented model achieved a DSC of 0.84 (), which is comparable to the expert human raters scores. The model segmented hypoechoic and mixed lesions more accurately (DSC of 0.89 and 0.88, respectively) than hyper- and isoechoic ones (DSC of 0.70 and 0.60, respectively) only missing isoechoic or >20mm in diameter (8% of the tumors) lesions. The inclusion of extra margins of probable tumor tissue around the lesions in the training ground truth resulted in lower DSCs of 0.75 (). The model can accurately segment hepatic tumors from iUS images and has the potential to speed up the resection margin definition during surgeries and the detection of lesion in screenings by automating iUS assessment.

Modeling of Respiratory Motion to Support the Minimally Invasive Destruction of Liver Tumors.

Objective: Respiratory movements are a significant factor that may hinder the use of image navigation systems during minimally invasive procedures used to destroy focal lesions in the liver. This article aims to present a method of estimating the displacement of the target point due to respiratory movements during the procedure, working in real time. Method: The real-time method using skin markers and non-rigid registration algorithms has been implemented and tested for various classes of transformation. The method was validated using clinical data from 21 patients diagnosed with liver tumors. For each patient, each marker was treated as a target and the remaining markers as target position predictors, resulting in 162 configurations and 1095 respiratory cycles analyzed. In addition, the possibility of estimating the respiratory phase signal directly from intraoperative US images and the possibility of synchronization with the 4D CT respiratory sequence are also presented, based on ten patients. Results: The median value of the target registration error (TRE) was 3.47 for the non-rigid registration method using the combination of rigid transformation and elastic body spline curves, and an adaptation of the assessing quality using image registration circuits (AQUIRC) method. The average maximum distance was 3.4 (minimum: 1.6, maximum 6.8) mm. Conclusions: The proposed method obtained promising real-time TRE values. It also allowed for the estimation of the TRE at a given geometric margin level to determine the estimated target position. Directions for further quantitative research and the practical possibility of combining both methods are also presented.

Fusion of Multiple-angles Intraoperative US Images and Pretreatment MR Images for USgHIFU Treatment of Uterine Fibroid: Retrospective Evaluation Based on Clinical Dataset.

High-intensity focused ultrasound (HIFU) has been widely used for treatment of uterine fibroids. However, due to the limited resolution of ultrasound image in deep organs, the guidance of ultrasound-guided HIFU (USgHIFU) treatment greatly depends on clinicians' experience in US image. To address this issue, fusion of intraoperative US images and pretreatment MR images has been proposed. Contour segmentation and multiple-angles 2D US images combination are performed to obtain 3D points along the contour of uterus. Iterative closest point (ICP) algorithm based on prior knowledge is used to register these point sets. MR and US images of six treated patients are used for evaluation. The mean distance error (MDE) of our algorithm is 1.71±0.59 mm, and the average running time is 0.18 s. The results have verified the feasibility of fusion of MR images and US images for USgHIFU guidance. In addition, this method may be also potential for post-ablation evaluation with follow-up MR images.

2392 ROBUST (Robotic Uterine Standardized Techniqueor): A Novel System for Uterine Biopsy

Study Objective The differential diagnosis of fibroids could be challenging with other uterine masses including adenomyomas or uterine cancers and sarcomas. Minimally Invasive procedures including morcellation mandates a thorough imaging and if possible histologic analyses. To date such a pathologic approach has a very poor accuracy, even conducted under ultrasound, MRI or hysteroscopic guidance. A targeted biopsy requires the development of state of the art imaging and robotics to enable a secure, reproducible, and accurate sampling. The aim of our study is to develop such a device based on the latest innovations in 3D imaging and robotics. Design ROBUST includes a robotic system called APOLLO® to position an ultrasound probe and an needle attached to it. A «co-manipulation mode » is used to control a robotized probe holder with Trinity, a 3D Ultrasound System performing image fusions. Setting University Hospital and University Research Laboratory in Robotics Patients or Participants Phantom Model Interventions Numerical approach on a phantom to estimate the interaction between the probe tip and the insertion environment. It is implemented on a robotic control law in order to accurately position the probe tip on uterine target Measurements and Main Results Biomechanical study of the uterus were performed to ensure the robustness and the efficacy of the image fusion. The fusion between intraoperative US images will allow the tracking of the organ displacement and deformation. A graphical interface dedicated to uterus diagnosis and puncture accessories will be developed. The guidance of the clinician gesture through a co-manipulated mode will allow an optimized targeting, exploiting the MRI targets of the imaging system, and taking account of the anatomical limits with a force feedback system Conclusion Two experiments manipulating Freely an ultrasound probe along two perpendicular translation and after insertion in an anatomical phantom helped us to assess a mathematical model to improve a robotic device to direct ultrasound guided biopsies.

Supporting diagnostics and therapy planning for percutaneous ablation of liver and abdominal tumors and pre-clinical evaluation

Percutaneous ablation methods are used to treat primary and metastatic liver tumors. Image guided navigation support minimally invasive interventions of rigid anatomical structures. When working with the displacement and deformation of soft tissues during surgery, as in the abdomen, imaging navigation systems are in the preliminary implementation stage.In this study a multi-stage approach has been developed to support percutaneous liver tumors ablation. It includes CT image acquisition protocol with the amplitude of respiratory motion that yields images subjected to a semi-automatic method able to deliver personalized abdominal model. Then, US probe and ablation needle calibration, as well as patient position adjustment method during the procedure for the preoperative anatomy model, have been combined. Finally, an advanced module for fusion of the preoperative CT with intraoperative US images was designed. These modules have been tested on a phantom and in the clinical environment.The final average Spatial calibration error was 1,7 mm, the average error of matching the position of the markers was about 2 mm during the entire breathing cycle, and average markers fusion error 495 mm. The obtained results indicate the possibility of using the developed method of navigation in clinical practice.

Comparison of ablation defect on MR imaging with computer simulation estimated treatment zone following irreversible electroporation of patient prostate.

To determine whether patient specific numerical simulations of irreversible electroporation (IRE) of the prostate correlates with the treatment effect seen on follow-up MR imaging. Computer models were created using intra-operative US images, post-treatment follow-up MR images and clinical data from six patients receiving IRE. Isoelectric contours drawn using simulation results were compared with MR imaging to estimate the energy threshold separating treated and untreated tissue. Simulation estimates of injury to the neurovascular bundle and rectum were compared with clinical follow-up and patient reported outcomes. At the electric field strength of 700 V/cm, simulation estimated electric field distribution was not different from the ablation defect seen on follow-up MR imaging (p = 0.43). Simulation predicted cross sectional area of treatment (mean 532.33 ± 142.32 mm2) corresponded well with the treatment zone seen on MR imaging (mean 540.16 ± 237.13 mm2). Simulation results did not suggest injury to the rectum or neurovascular bundle, matching clinical follow-up at 3 months. Computer simulation estimated zone of irreversible electroporation in the prostate at 700 V/cm was comparable to measurements made on follow-up MR imaging. Numerical simulation may aid treatment planning for irreversible electroporation of the prostate in patients.

A 3D ultrasound scanning system for image guided liver interventions

Two-dimensional ultrasound (2D US) imaging is commonly used for diagnostic and intraoperative guidance of interventional liver procedures; however, 2D US lacks volumetric information that may benefit interventional procedures. Over the past decade, three-dimensional ultrasound (3D US) has been developed to provide the missing spatial information. 3D US image acquisition is mainly based on mechanical, electromagnetic, and freehand tracking of conventional 2D US transducers, or 2D array transducers available on high-end machines. These approaches share many problems during clinical use for interventional liver imaging due to lack of flexibility and compatibility with interventional equipment, limited field-of-view (FOV), and significant capital cost compared to the benefits they introduce. In this paper, a novel system for mechanical 3D US scanning is introduced to address these issues. The authors have developed a handheld mechanical 3D US system that incorporates mechanical translation and tilt sector sweeping of any standard 2D US transducer to acquire 3D images. Each mechanical scanning function can be operated independently or may be combined to allow for a hybrid wide FOV acquisition. The hybrid motion mode facilitates registration of other modalities (e.g., CT or MRI) to the intraoperative 3D US images by providing a larger FOV in which to acquire anatomical information. The tilting mechanism of the developed mover allows image acquisition in the intercostal rib space to avoid acoustic shadowing from bone. The geometric and volumetric scanning validity of the 3D US system was evaluated on tissue mimicking US phantoms for different modes of operation. Identical experiments were performed on a commercially available 3D US system for direct comparison. To replicate a clinical scenario, the authors evaluated their 3D US system by comparing it to CT for measurement of angle and distance between interventional needles in different configurations, similar to those used for percutaneous ablation of liver tumors. The mean geometrical hybrid 3D reconstruction error measured from scanning of a known string phantom was less than 1 mm in two directions and 2.5 mm in the scanning direction, which was comparable or better than the same measurements obtained from a commercially available 3D US system. The error in volume measurements of spherical phantom models depended on depth of the object. For a 20 cm(3) model at a depth of 15 cm, a standard depth for liver imaging, the mean error was 3.6% ± 4.5% comparable to the 2.3% ± 1.8% error for the 3D US commercial system. The error in 3D US measurement of the tip distance and angle between two microwave ablation antennas inserted into the phantom was 0.9 ± 0.5 mm and 1.1° ± 0.7°, respectively. A 3D US system with hybrid scanning motions for large field-of-view 3D abdominal imaging has been developed and validated. The superior spatial information provided by 3D US might enhance image-guidance for percutaneous interventional treatment of liver malignancies. The system has potential to be integrated with other liver procedures and has application in other abdominal organs such as kidneys, spleen, or adrenals.

58 Comparison of prostate volumes delineated on pre-implant MRI, pre-implant US and intra-operative US images for planning of permanent prostate implants

58 Comparison of prostate volumes delineated on pre-implant MRI, pre-implant US and intra-operative US images for planning of permanent prostate implants

90 Fusion of pre-implant MRI and intra-operative US images for planning of permanent prostate implants

90 Fusion of pre-implant MRI and intra-operative US images for planning of permanent prostate implants