Intracranial aneurysm detection: an object detection perspective.

PURPOSE: Intracranial aneurysm detection from 3D Time-Of-Flight Magnetic Resonance Angiography images is a problem of increasing clinical importance. Recently, a streak of methods have shown promising performance by using segmentation neural networks. However, these methods may be less relevant in a clinical settings where diagnostic decisions rely on detecting objects rather than their segmentation. METHODS: We introduce a 3D single-stage object detection method tailored for small object detection such as aneurysms. Our anchor-free method incorporates fast data annotation, adapted data sampling and generation to address class imbalance problem, and spherical representations for improved detection. RESULTS: A comprehensive evaluation was conducted, comparing our method with the state-of-the-art SCPM-Net, nnDetection and nnUNet baselines, using two datasets comprising 402 subjects. The evaluation used adapted object detection metrics. Our method exhibited comparable or superior performance, with an average precision of 78.96%, sensitivity of 86.78%, and 0.53 false positives per case. CONCLUSION: Our method significantly reduces the detection complexity compared to existing methods and highlights the advantages of object detection over segmentation-based approaches for aneurysm detection. It also holds potential for application to other small object detection problems.

ICG-induced NIR fluorescence mapping in patients with head & neck tumors after the previous radiotherapy.

BACKGROUND: The distinction between tumor and healthy tissues is complicated in the areas previously subjected to radiation therapy (RT). This is related to the fact that tissues can undergo delayed and irreversible deterioration such as inflammation, vascular alteration and fibrosis. The trials related to the fluorescence -guided surgery (FSG) in Head and Neck Squamous Cell Carcinoma (HNSCC) patients, previously subjected to RT, have not yet been reported. The present study addresses for the first time the possibilities of tumor near-infrared (NIR) imaging using Indocynaine Green (ICG) in irradiated areas. METHODS: Four patients with histologically confirmed HNSCC were included in this study. All included patients were previously treated with RT with at least 50 Gy. RT-radiation fields from original treatment fully encompassed the second tumor or recurrence. ICG was injected via cephalic vein 45 min before the images were captured using a NIR camera system Artemis. The images were also captured before ICG injection serving as background signal. The fluorescence intensity measurements were carried out using specially designed software. RESULTS: ICG fluorescence clearly demonstrated a significant difference in fluorescence intensity between healthy and tumor tissues in 2 of 4 patients. Histology post-resection analysis confirmed a complete tumor resection with safe surgical margins. No difference between tumor and surrounding healthy tissue was detected in patients with an epidermoid carcinoma developed from sclerohypertrophic lichen. CONCLUSIONS: In our pilot study, we clearly established the feasibility of using NIR FGS with ICG to delineate tumor and healthy tissues in irradiated areas in infiltrating lichen-free tumors.

Constrained stochastic state estimation of deformable 1D objects: Application to single-view 3D reconstruction of catheters with radio-opaque markers.

Minimally invasive fluoroscopy-based procedures are the gold standard for diagnosis and treatment of various pathologies of the cardiovascular system. This kind of procedures imply for the clinicians to infer the 3D shape of the device from 2D images, which is known to be an ill-posed problem. In this paper we present a method to reconstruct the 3D shape of the interventional device, with the aim of improving the navigation. The method combines a physics-based simulation with non-linear Bayesian filter. Whereas the physics-based model provides a prediction of the shape of the device navigating within the blood vessels (taking into account non-linear interactions between the catheter and the surrounding anatomy), an Unscented Kalman Filter is used to correct the navigation model using 2D image features as external observations. The proposed framework has been evaluated on both synthetic and real data, under different model parameterizations, filter parameters tuning and external observations data-sets. Comparing the reconstructed 3D shape with a known ground truth, for the synthetic data-set, we obtained average values for 3D Hausdorff Distance of 0.81±0.53mm, for the 3D mean distance at the segment of 0.37±0.17mm and an average 3D tip error of 0.24±0.13mm. For the real data-set,we obtained an average 3D Hausdorff distance of 1.74±0.77mm, a average 3D mean distance at the distal segment of 0.91±0.14mm, an average 3D error on the tip of 0.53±0.09mm. These results show the ability of our method to retrieve the 3D shape of the device, under a variety of filter parameterizations and challenging conditions: uncertainties on model parameterization, ambiguous views and non-linear complex phenomena such as stick and slip motions.

Multimodal acquisition of articulatory data: Geometrical and temporal registration.

Acquisition of dynamic articulatory data is of major importance for studying speech production. It turns out that one technique alone often is not enough to get a correct coverage of the whole vocal tract at a sufficient sampling rate. Ultrasound (US) imaging has been proposed as a good acquisition technique for the tongue surface because it offers a good temporal sampling, does not alter speech production, is cheap, and is widely available. However, it cannot be used alone and this paper describes a multimodal acquisition system which uses electromagnetography sensors to locate the US probe. The paper particularly focuses on the calibration of the US modality which is the key point of the system. This approach enables US data to be merged with other data. The use of the system is illustrated via an experiment consisting of measuring the minimal tongue to palate distance in order to evaluate and design Magnetic Resonance Imaging protocols well suited for the acquisition of three-dimensional images of the vocal tract. Compared to manual registration of acquisition modalities which is often used in acquisition of articulatory data, the approach presented relies on automatic techniques well founded from geometrical and mathematical points of view.

Impact of Soft Tissue Heterogeneity on Augmented Reality for Liver Surgery.

This paper presents a method for real-time augmented reality of internal liver structures during minimally invasive hepatic surgery. Vessels and tumors computed from pre-operative CT scans can be overlaid onto the laparoscopic view for surgery guidance. Compared to current methods, our method is able to locate the in-depth positions of the tumors based on partial three-dimensional liver tissue motion using a real-time biomechanical model. This model permits to properly handle the motion of internal structures even in the case of anisotropic or heterogeneous tissues, as it is the case for the liver and many anatomical structures. Experimentations conducted on phantom liver permits to measure the accuracy of the augmentation while real-time augmentation on in vivo human liver during real surgery shows the benefits of such an approach for minimally invasive surgery.

Towards interactive planning of coil embolization in brain aneurysms.

Many vascular pathologies can now be treated in a minimally invasive way thanks to interventional radiology. Instead of open surgery, it allows to reach the lesion of the arteries with therapeutic devices through a catheter. As a particular case, intracranial aneurysms are treated by filling the localized widening of the artery with a set of coils to prevent a rupture due to the weakened arterial wall. Considering the location of the lesion, close to the brain, and its very small size, the procedure requires a combination of careful planning and excellent technical skills. An interactive and reliable simulation, adapted to the patient anatomy, would be an interesting tool for helping the interventional neuroradiologist plan and rehearse a coil embolization procedure. This paper describes an original method to perform interactive simulations of coil embolization and proposes a clinical metric to quantitatively measure how the first coil fills the aneurysm. The simulation relies on an accurate reconstruction of the aneurysm anatomy and a real-time model of the coil for which sliding and friction contacts are taken into account. Simulation results are compared to real embolization procedure and exhibit good adequacy.

A methodology for validating a 3D imaging modality for brain AVM delineation: application to 3DRA.

A general methodology is described to validate a 3D imaging modality with respect to 2D digital subtracted angiography (DSA) for brain AVMs (BAVM) delineation. It relies on the assessment of the statistical compatibility of the radiosurgical target delineated in 3D with its delineations in 2D. This methodology is demonstrated through a preliminary evaluation of 3D rotational angiography (3DRA). Generally speaking, BAVM delineation cannot be performed on 3DRA alone. However, in our study, 3DRA showed similar performances to DSA for rather easy cases, and even better for three patients. Conversely, three problematic cases are identified and discussed.