3D ultrasound registration-based visual servoing for neurosurgical navigation

DefCor-Net: Physics-aware ultrasound deformation correction

The recovery of morphologically accurate anatomical images from deformed ones is challenging in ultrasound (US) image acquisition, but crucial to accurate and consistent diagnosis, particularly in the emerging field of computer-assisted diagnosis. This article presents a novel physics-aware deformation correction approach based on a coarse-to-fine, multi-scale deep neural network (DefCor-Net). To achieve pixel-wise performance, DefCor-Net incorporates biomedical knowledge by estimating pixel-wise stiffness online using a U-shaped feature extractor. The deformation field is then computed using polynomial regression by integrating the measured force applied by the US probe. Based on real-time estimation of pixel-by-pixel tissue properties, the learning-based approach enables the potential for anatomy-aware deformation correction. To demonstrate the effectiveness of the proposed DefCor-Net, images recorded at multiple locations on forearms and upper arms of six volunteers are used to train and validate DefCor-Net. The results demonstrate that DefCor-Net can significantly improve the accuracy of deformation correction to recover the original geometry (Dice Coefficient: from 14.3±20.9 to 82.6±12.1 when the force is 6N). Code:https://github.com/KarolineZhy/DefCorNet.

ENDOSCOPIC INTERLAMINAR SPINE SURGERY GUIDED BY PORTABLE ULTRASOUND: A NEW TECHNIQUE

ABSTRACT This paper describes the technique of interlaminar endoscopic surgery guided by a portable ultrasound device. This innovation allows endoscopic surgery to be performed without the use of real-time radiography, which is associated with a higher risk of radiation damage. The portable wireless ultrasound device used for this technique, which has not been yet described in the world literature for minimally invasive surgeries, can be used as an imaging tool to delimit the interlaminar space in minimally invasive surgeries via both transverse and sagittal views. Level of evidence I; Quality of evidence A.

Ultrasound-guided needle insertion robotic system for percutaneous puncture

PURPOSE

Ultrasound (US)-guided percutaneous puncture technology can realize real-time, minimally invasive interventional therapy without radiation. The location accuracy of the puncture needle directly determines the precision and safety of the operation. It is a challenge for novices and young surgeons to perform a free-hand puncture guided by the ultrasound images to achieve the desired accuracy. This work aims to develop a robotic system to assist surgeons to perform percutaneous punctures with high precision.

METHODS

An US-guided puncture robot was designed to allow the mounting and control of the needle to achieve localization and insertion. The US probe fitted within the puncture robot was held by a passive arm. Moreover, the puncture robot was calibrated with a novel calibration method to achieve coordinate transformation between the robot and the US image. The system allowed the operators to plan the puncture target and puncture path on US images, and the robot performed needle insertion automatically. Five groups of puncture experiments were performed to verify the validity and accuracy of the proposed robotic system.

RESULTS

Assisted by the robotic system, the positioning and orientation accuracies of the needle insertion were 0.9 ± 0.29 mm and 0.76 ± 0.34°, respectively. These are improved compared with the results obtained with the free-hand puncture (1.82 ± 0.51 mm and 2.79 ± 1.32°, respectively). Moreover, the proposed robotic system can reduce the operation time and number of needle insertions (14.28 ± 3.21 s and one needle insertion, respectively), compared with the free-hand puncture (25.14 ± 6.09 s and 1.96 ± 0.68 needle insertions, respectively).

CONCLUSION

A robotic system for percutaneous puncture guided by US images was developed and demonstrated. The experimental results indicate that the proposed system is accurate and feasible. It can assist novices and young surgeons to perform the puncture operation with increased accuracy.

GPU implementation of photoacoustic short-lag spatial coherence imaging for improved image-guided interventions

SIGNIFICANCE

Photoacoustic-based visual servoing is a promising technique for surgical tool tip tracking and automated visualization of photoacoustic targets during interventional procedures. However, one outstanding challenge has been the reliability of obtaining segmentations using low-energy light sources that operate within existing laser safety limits.

AIM

We developed the first known graphical processing unit (GPU)-based real-time implementation of short-lag spatial coherence (SLSC) beamforming for photoacoustic imaging and applied this real-time algorithm to improve signal segmentation during photoacoustic-based visual servoing with low-energy lasers.

APPROACH

A 1-mm-core-diameter optical fiber was inserted into ex vivo bovine tissue. Photoacoustic-based visual servoing was implemented as the fiber was manually displaced by a translation stage, which provided ground truth measurements of the fiber displacement. GPU-SLSC results were compared with a central processing unit (CPU)-SLSC approach and an amplitude-based delay-and-sum (DAS) beamforming approach. Performance was additionally evaluated with in vivo cardiac data.

RESULTS

The GPU-SLSC implementation achieved frame rates up to 41.2 Hz, representing a factor of 348 speedup when compared with offline CPU-SLSC. In addition, GPU-SLSC successfully recovered low-energy signals (i.e., ≤268  μJ) with mean ± standard deviation of signal-to-noise ratios of 11.2  ±  2.4 (compared with 3.5  ±  0.8 with conventional DAS beamforming). When energies were lower than the safety limit for skin (i.e., 394.6  μJ for 900-nm wavelength laser light), the median and interquartile range (IQR) of visual servoing tracking errors obtained with GPU-SLSC were 0.64 and 0.52 mm, respectively (which were lower than the median and IQR obtained with DAS by 1.39 and 8.45 mm, respectively). GPU-SLSC additionally reduced the percentage of failed segmentations when applied to in vivo cardiac data.

CONCLUSIONS

Results are promising for the use of low-energy, miniaturized lasers to perform GPU-SLSC photoacoustic-based visual servoing in the operating room with laser pulse repetition frequencies as high as 41.2 Hz.

The state-of-the-art in ultrasound-guided spine interventions

During the last two decades, intra-operative ultrasound (iUS) imaging has been employed for various surgical procedures of the spine, including spinal fusion and needle injections. Accurate and efficient registration of pre-operative computed tomography or magnetic resonance images with iUS images are key elements in the success of iUS-based spine navigation. While widely investigated in research, iUS-based spine navigation has not yet been established in the clinic. This is due to several factors including the lack of a standard methodology for the assessment of accuracy, robustness, reliability, and usability of the registration method. To address these issues, we present a systematic review of the state-of-the-art techniques for iUS-guided registration in spinal image-guided surgery (IGS). The review follows a new taxonomy based on the four steps involved in the surgical workflow that include pre-processing, registration initialization, estimation of the required patient to image transformation, and a visualization process. We provide a detailed analysis of the measurements in terms of accuracy, robustness, reliability, and usability that need to be met during the evaluation of a spinal IGS framework. Although this review is focused on spinal navigation, we expect similar evaluation criteria to be relevant for other IGS applications.