Topology observing 3D device reconstruction from continuous-sweep limited angle fluoroscopy

BACKGROUND

Minimally invasive procedures usually require navigating a microcatheter and guidewire through endoluminal structures such as blood vessels and airways to sites of the disease. For numerous clinical applications, two-dimensional (2D) fluoroscopy is the primary modality used for real-time image guidance during navigation. However, 2D imaging can pose challenges for navigation in complex structures. Real-time 3D visualization of devices within the anatomic context could provide considerable benefits for these procedures. Continuous-sweep limited angle (CLA) fluoroscopy has recently been proposed to provide a compromise between conventional rotational 3D acquisitions and real-time fluoroscopy.

PURPOSE

The purpose of this work was to develop and evaluate a noniterative 3D device reconstruction approach for CLA fluoroscopy acquisitions, which takes into account endoluminal topology to avoid impossible paths between disconnected branches.

METHODS

The algorithm relies on a static 3D roadmap (RM) of vessels or airways, which may be generated from conventional cone beam CT (CBCT) acquisitions prior to navigation. The RM is converted to a graph representation describing its topology. During catheter navigation, the device is segmented from the live 2D projection images using a deep learning approach from which the centerlines are extracted. Rays from the focal spot to detector pixels representing 2D device points are identified and intersections with the RM are computed. Based on the RM graph, a subset of line segments is selected as candidates to exclude device paths through disconnected branches of the RM. Depth localization for each point along the device is then performed by finding the point closest to the previous 3D reconstruction along the candidate segments. This process is repeated as the projection angle changes for each CLA image frame. The approach was evaluated in a phantom study in which a catheter and guidewire were navigated along five pathways within a complex vessel phantom. The result was compared to static cCBCT acquisitions of the device in the final position.

RESULTS

The average root mean squared 3D distance between CLA reconstruction and reference centerline was1.87 ± 0.30 $1.87 \pm 0.30$ mm. The Euclidean distance at the device tip was2.92 ± 2.35 $2.92 \pm 2.35$ mm. The correct pathway was identified during reconstruction in100 % $100\%$ of frames (n = 1475 $n=1475$ ). The percentage of 3D device points reconstructed inside the 3D roadmap was91.83 ± 2.52 % $91.83 \pm 2.52\%$ with an average distance of0.62 ± 0.30 $0.62 \pm 0.30$ mm between the device points outside the roadmap and the nearest point within the roadmap.

CONCLUSIONS

This study demonstrates the feasibility of reconstructing curvilinear devices such as catheters and guidewires during endoluminal procedures including intravascular and transbronchial interventions using a noniterative reconstruction approach for CLA fluoroscopy. This approach could improve device navigation in cases where the structure of vessels or airways is complex and includes overlapping branches.

A target containing phantom for accuracy assessment of cone-beam CT-guided histotripsy

PURPOSE

Histotripsy is a nonionizing, noninvasive, and nonthermal focal tumor therapy. Cone-beam computed tomography (CBCT) guidance was developed for targeting tumors not visible on ultrasound. This approach assumes cavitation is formed at the geometrical focal point of the therapy transducer. In practice, the exact location might vary slightly between transducers. In this study, we present a phantom with an embedded target to evaluate CBCT-guided histotripsy accuracy and assess the completeness of treatments.

METHODS

Spherical (2.8 cm) targets with alternating layers of agar and radiopaque barium were embedded in larger phantoms with similar layers. The layer geometry was designed so that targets were visible on pre-treatment CBCT scans. The actual histotripsy treatment zone was visualized via the mixing of adjacent barium and agar layers in post-treatment CBCT images. CBCT-guided histotripsy treatments of the targets were performed in six phantoms. Offsets between planned and actual treatment zones were measured and used for calibration refinement. To measure targeting accuracy after calibration refinement, six additional phantoms were treated. In a separate investigation, two groups (N = 3) of phantoms were treated to assess visualization of incomplete treatments ("undertreatment" group: 2 cm treatment within 2.8 cm tumor, "mistarget" group: 2.8 cm treatment intentionally shifted laterally). Treatment zones were segmented (3D Slicer 5.0.3), and the centroid distance between the prescribed target and actual treatment zones was quantified.

RESULTS

In the calibration refinement group, a 2 mm offset in the direction of ultrasound propagation (Z) was measured. After calibration refinement, the centroid-to-centroid distance between prescribed and actual treatment volumes was 0.5 ± 0.2 mm. Average difference between the prescribed and measured treatment sizes in the incomplete treatment groups was 0.5 ± 0.7 mm. In the mistarget group, the distance between prescribed and measured shifts was 0.2 ± 0.1 mm.

CONCLUSION

The proposed prototype phantom allowed for accurate measurement of treatment size and location, and the CBCT visible target provided a simple way to detect misalignments for preliminary quality assurance of CBCT-guided histotripsy.

A Multimodal Phantom for Visualization and Assessment of Histotripsy Treatments on Ultrasound and X-Ray Imaging

OBJECTIVE

Histotripsy is an emerging non-invasive, non-ionizing and non-thermal focal tumor therapy. Although histotripsy targeting is currently based on ultrasound (US), other imaging modalities such as cone-beam computed tomography (CBCT) have recently been proposed to enable the treatment of tumors not visible on ultrasound. The objective of this study was to develop and evaluate a multi-modality phantom to facilitate the assessment of histotripsy treatment zones on both US and CBCT imaging.

METHODS

Fifteen red blood cell phantoms composed of alternating layers with and without barium were manufactured. Spherical 25-mm histotripsy treatments were performed, and treatment zone size and location were measured on CBCT and ultrasound. Sound speed, impedance and attenuation were measured for each layer type.

RESULTS

The average ± standard deviation signed difference between measured treatment diameters was 0.29 ± 1.25 mm. The Euclidean distance between measured treatment centers was 1.68 ± 0.63 mm. The sound speed in the different layers ranged from 1491 to 1514 m/s and was within typically reported soft tissue ranges (1480-1560 m/s). In all phantoms, histotripsy resulted in sharply delineated treatment zones, allowing segmentation in both modalities.

CONCLUSION

These phantoms will aid in the development and validation of X-ray-based histotripsy targeting techniques, which promise to expand the scope of treatable lesions beyond only those visible on ultrasound.

An X-Ray C-Arm Guided Automatic Targeting System for Histotripsy

OBJECTIVE

Histotripsy is an emerging noninvasive, nonionizing and nonthermal focal cancer therapy that is highly precise and can create a treatment zone of virtually any size and shape. Current histotripsy systems rely on ultrasound imaging to target lesions. However, deep or isoechoic targets obstructed by bowel gas or bone can often not be treated safely using ultrasound imaging alone. This work presents an alternative x-ray C-arm based targeting approach and a fully automated robotic targeting system.

METHODS

The approach uses conventional cone beam CT (CBCT) images to localize the target lesion and 2D fluoroscopy to determine the 3D position and orientation of the histotripsy transducer relative to the C-arm. The proposed pose estimation uses a digital model and deep learning-based feature segmentation to estimate the transducer focal point relative to the CBCT coordinate system. Additionally, the integrated robotic arm was calibrated to the C-arm by estimating the transducer pose for four preprogrammed transducer orientations and positions. The calibrated system can then automatically position the transducer such that the focal point aligns with any target selected in a CBCT image.

RESULTS

The accuracy of the proposed targeting approach was evaluated in phantom studies, where the selected target location was compared to the center of the spherical ablation zones in post-treatment CBCTs. The mean and standard deviation of the Euclidean distance was 1.4 ±0.5 mm. The mean absolute error of the predicted treatment radius was 0.5 ±0.5 mm.

CONCLUSION

CBCT-based histotripsy targeting enables accurate and fully automated treatment without ultrasound guidance.

SIGNIFICANCE

The proposed approach could considerably decrease operator dependency and enable treatment of tumors not visible under ultrasound.