Biplane US-Guided Real-Time Volumetric Target Pose Estimation Method for Theragnostic HIFU System

Seo, Joonho; Koizumi, Norihiro; Funamoto, Takakazu; Sugita, Naohiko; Yoshinaka, Kiyoshi; Nomiya, Akira; Homma, Yukio; Matsumoto, Yoichiro; Mitsuishi, Mamoru

doi:10.20965/jrm.2011.p0400

Cited by 6 publications

(7 citation statements)

References 14 publications

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“…Overall, and despite the method's performance being interesting when compared to other state-of-the-art solutions using orthogonal acquisitions, the results presented lower accuracy. Seo et al reported a TRE of 1.68 mm in one phantom model (with biplane acquisition at the surface's center using two orthogonal 2D probes), 20 and our study obtained a TRE of 4.08 mm (using a kidney's coverage range of 0°, BP and ICP2, see Table II). However, higher anatomical variability (ten phantoms in total) and higher positional variability before surface-based registration (400 different orientations per assessment, with up to AE90°of rotation per axis) was assumed in the current study.…”

Section: Discussionsupporting

confidence: 62%

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Surface‐based registration between CT and US for image‐guided percutaneous renal access – A feasibility study

et al. 2019

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Purpose As a crucial step in accessing the kidney in several minimally invasive interventions, percutaneous renal access (PRA) practicality and safety may be improved through the fusion of computed tomography (CT) and ultrasound (US) data. This work aims to assess the potential of a surface‐based registration technique and establish an optimal US acquisition protocol to fuse two‐dimensional (2D) US and CT data for image‐guided PRA. Methods Ten porcine kidney phantoms with fiducial markers were imaged using CT and three‐dimensional (3D) US. Both images were manually segmented and aligned. In a virtual environment, 2D contours were extracted by slicing the 3D US kidney surfaces and using usual PRA US‐guided views, while the 3D CT kidney surfaces were transformed to simulate positional variability. Surface‐based registration was performed using two methods of the iterative closest point algorithm (point‐to‐point, ICP1; and point‐to‐plane, ICP2), while four acquisition variants were studied: (a) use of single‐plane (transverse, SPT; or longitudinal, SPL) vs bi‐plane views (BP); (b) use of different kidney's coverage ranges acquired by a probe's sweep; (c) influence of sweep movements; and (d) influence of the spacing between consecutive slices acquired for a specific coverage range. Results BP view showed the best performance (TRE = 2.26 mm) when ICP2 method, a wide kidney coverage range (20°, with slices spaced by 5°), and a large sweep along the central longitudinal view were used, showing a statistically similar performance (P = 0.097) to a full 3D US surface registration (TRE = 2.28 mm). Conclusions An optimal 2D US acquisition protocol was evaluated. Surface‐based registration, using multiple slices and specific sweep movements and views, is here suggested as a valid strategy for intraoperative image fusion using CT and US data, having the potential to be applied to other image modalities and/or interventions.

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Section: Discussionsupporting

confidence: 62%

“…Finally, Seo et al. used two orthogonal 2D US probes to create a biplane US imaging of the kidney and, then, estimate the pose of a preoperative 3D model . The proposed method showed high accuracy and robustness, being tested in different applications .…”

Section: Introductionmentioning

confidence: 99%

Surface‐based registration between CT and US for image‐guided percutaneous renal access – A feasibility study

et al. 2019

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“…In this sense, previous studies have proposed and developed integrated systems capable of delivering US-based motion compensated HIFU therapies. For example, Seo et al designed a system consisting of two US imaging probes integrated with a HIFU transducer (Seo et al 2011a, Seo et al 2011b, Seo et al 2016. One probe was placed at the center of the parabolic transducer, while the second was placed on the edge of the transducer at a 45 • angle with respect to the first one.…”

Section: Introductionmentioning

confidence: 99%

Real-time non-rigid target tracking for ultrasound-guided clinical interventions

et al. 2017

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Biological motion is a problem for non- or mini-invasive interventions when conducted in mobile/deformable organs due to the targeted pathology moving/deforming with the organ. This may lead to high miss rates and/or incomplete treatment of the pathology. Therefore, real-time tracking of the target anatomy during the intervention would be beneficial for such applications. Since the aforementioned interventions are often conducted under B-mode ultrasound (US) guidance, target tracking can be achieved via image registration, by comparing the acquired US images to a separate image established as positional reference. However, such US images are intrinsically altered by speckle noise, introducing incoherent gray-level intensity variations. This may prove problematic for existing intensity-based registration methods. In the current study we address US-based target tracking by employing the recently proposed EVolution registration algorithm. The method is, by construction, robust to transient gray-level intensities. Instead of directly matching image intensities, EVolution aligns similar contrast patterns in the images. Moreover, the displacement is computed by evaluating a matching criterion for image sub-regions rather than on a point-by-point basis, which typically provides more robust motion estimates. However, unlike similar previously published approaches, which assume rigid displacements in the image sub-regions, the EVolution algorithm integrates the matching criterion in a global functional, allowing the estimation of an elastic dense deformation. The approach was validated for soft tissue tracking under free-breathing conditions on the abdomen of seven healthy volunteers. Contact echography was performed on all volunteers, while three of the volunteers also underwent standoff echography. Each of the two modalities is predominantly specific to a particular type of non- or mini-invasive clinical intervention. The method demonstrated on average an accuracy of ∼1.5 mm and submillimeter precision. This, together with a computational performance of 20 images per second make the proposed method an attractive solution for real-time target tracking during US-guided clinical interventions.

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“…In our HIFU system, the end‐effector enables both US imaging and HIFU irradiation by the design shown in Figure . The design of the end‐effector is the same as that presented in our previous research . Two US imaging probes are attached to produce biplane US images.…”

Section: Methodsmentioning

confidence: 99%

“…The 3D model based target tracking method is fast (40 FPS in the developed system) and robust for noisy US image data. The details of the registration algorithm are explained in a previously published paper …”

Section: Methodsmentioning

confidence: 99%

Ultrasound image based visual servoing for moving target ablation by high intensity focused ultrasound

Seo

Koizumi

Mitsuishi

et al. 2016

Robotics Computer Surgery

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BackgroundAlthough high intensity focused ultrasound (HIFU) is a promising technology for tumor treatment, a moving abdominal target is still a challenge in current HIFU systems. In particular, respiratory‐induced organ motion can reduce the treatment efficiency and negatively influence the treatment result. In this research, we present: (1) a methodology for integration of ultrasound (US) image based visual servoing in a HIFU system; and (2) the experimental results obtained using the developed system.Materials and methodsIn the visual servoing system, target motion is monitored by biplane US imaging and tracked in real time (40 Hz) by registration with a preoperative 3D model. The distance between the target and the current HIFU focal position is calculated in every US frame and a three‐axis robot physically compensates for differences. Because simultaneous HIFU irradiation disturbs US target imaging, a sophisticated interlacing strategy was constructed.ResultsIn the experiments, respiratory‐induced organ motion was simulated in a water tank with a linear actuator and kidney‐shaped phantom model. Motion compensation with HIFU irradiation was applied to the moving phantom model. Based on the experimental results, visual servoing exhibited a motion compensation accuracy of 1.7 mm (RMS) on average. Moreover, the integrated system could make a spherical HIFU‐ablated lesion in the desired position of the respiratory‐moving phantom model.ConclusionsWe have demonstrated the feasibility of our US image based visual servoing technique in a HIFU system for moving target treatment.

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Biplane US-Guided Real-Time Volumetric Target Pose Estimation Method for Theragnostic HIFU System

Cited by 6 publications

References 14 publications

Surface‐based registration between CT and US for image‐guided percutaneous renal access – A feasibility study

Surface‐based registration between CT and US for image‐guided percutaneous renal access – A feasibility study

Real-time non-rigid target tracking for ultrasound-guided clinical interventions

Ultrasound image based visual servoing for moving target ablation by high intensity focused ultrasound

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