Guidance Core

Noby hata Jayender Jagadeesan Junichi Tokuda
Nobuhiko Hata, PhD
Core Lead
Jayender Jagadeesan, PhD
Project Lead
Junichi Tokuda, PhD
Project Lead

The long-term goal of Guidance Core is to provide novel guidance methods to improve the outcome of therapies of dynamically deforming and moving organs. This involves developing unique tissue-embedded wireless electromagnetic sensors (EM) and MR-tracked catheters to verify their feasibility and impact on the clinical procedures performed at the Advanced Multimodality Image Guided Operating Room (AMIGO). Projects within this Core are:

Integrated navigation system to accurately localize the tumor and guide the surgical instrument to the optimal resection margin in presence of significant tissue deformation.  We are developing hardware for the integrated navigation system to enable real-time tumor and instrument tracking; a tumor deformation model to estimate the tumor position and optimal resection margin; software for the integrated navigation system to visualize the tumor and surgical instrument. We continue to validate the design and performance of the integrated navigation system in ex-vivo phantoms and in human clinical trials. (Contact: Jayender Jagadeesan)

Verify the ability of active MRI-tracked metallic interventional devices to improve interventions through improved positional accuracy and improved therapy delivery. We are developing a miniature MRI tracking coil array embedded in flexible and rigid metallic stylets and catheters and improving dedicated MR-tracking pulse sequences to locate the devices so as to rapidly and accurately guide insertion of these devices in soft tissue and to monitor the non-rigid deformation of the target tissues. This is expected to enable clinicians to correct the access path based on these data. In addition, motional data provided by the devices is expected to aid in motion-compensated oxygenation imaging for radiation-dose augmentation to hypoxic tumor segments that resist radiation therapy. (Contact: Junichi Tokuda)

Software and Documentation

Links

Full Publication List

In NIH/NLM database and in our Abstracts Database.

Select Recent Publications

Zhou H, Zhang T, Jagadeesan J. Re-weighting and 1-Point RANSAC-Based P nP Solution to Handle Outliers. IEEE Trans Pattern Anal Mach Intell. 2019;41 (12) :3022-33.Abstract
The ability to handle outliers is essential for performing the perspective- n-point (P nP) approach in practical applications, but conventional RANSAC+P3P or P4P methods have high time complexities. We propose a fast P nP solution named R1PP nP to handle outliers by utilizing a soft re-weighting mechanism and the 1-point RANSAC scheme. We first present a P nP algorithm, which serves as the core of R1PP nP, for solving the P nP problem in outlier-free situations. The core algorithm is an optimal process minimizing an objective function conducted with a random control point. Then, to reduce the impact of outliers, we propose a reprojection error-based re-weighting method and integrate it into the core algorithm. Finally, we employ the 1-point RANSAC scheme to try different control points. Experiments with synthetic and real-world data demonstrate that R1PP nP is faster than RANSAC+P3P or P4P methods especially when the percentage of outliers is large, and is accurate. Besides, comparisons with outlier-free synthetic data show that R1PP nP is among the most accurate and fast P nP solutions, which usually serve as the final refinement step of RANSAC+P3P or P4P. Compared with REPP nP, which is the state-of-the-art P nP algorithm with an explicit outliers-handling mechanism, R1PP nP is slower but does not suffer from the percentage of outliers limitation as REPP nP.
Guenette JP, Ben-Shlomo N, Jayender J, Seethamraju RT, Kimbrell V, Tran N-A, Huang RY, Kim CJ, Kass JI, Corrales CE, et al. MR Imaging of the Extracranial Facial Nerve with the CISS Sequence. AJNR Am J Neuroradiol. 2019.Abstract
BACKGROUND AND PURPOSE: MR imaging is not routinely used to image the extracranial facial nerve. The purpose of this study was to determine the extent to which this nerve can be visualized with a CISS sequence and to determine the feasibility of using that sequence for locating the nerve relative to tumor. MATERIALS AND METHODS: Thirty-two facial nerves in 16 healthy subjects and 4 facial nerves in 4 subjects with parotid gland tumors were imaged with an axial CISS sequence protocol that included 0.8-mm isotropic voxels on a 3T MR imaging system with a 64-channel head/neck coil. Four observers independently segmented the 32 healthy subject nerves. Segmentations were compared by calculating average Hausdorff distance values and Dice similarity coefficients. RESULTS: The primary bifurcation of the extracranial facial nerve into the superior temporofacial and inferior cervicofacial trunks was visible on all 128 segmentations. The mean of the average Hausdorff distances was 1.2 mm (range, 0.3-4.6 mm). Dice coefficients ranged from 0.40 to 0.82. The relative position of the facial nerve to the tumor could be inferred in all 4 tumor cases. CONCLUSIONS: The facial nerve can be seen on CISS images from the stylomastoid foramen to the temporofacial and cervicofacial trunks, proximal to the parotid plexus. Use of a CISS protocol is feasible in the clinical setting to determine the location of the facial nerve relative to tumor.
Moreira P, Patel N, Wartenberg M, Li G, Tuncali K, Heffter T, Burdette EC, Iordachita I, Fischer GS, Hata N, et al. Evaluation of Robot-assisted MRI-guided Prostate Biopsy: Needle Path Analysis during Clinical Trials. Phys Med Biol. 2018;63 (20) :20NT02.Abstract
PURPOSE: While the interaction between a needle and the surrounding tissue is known to cause a significant targeting error in prostate biopsy leading to false-negative results, few studies have demonstrated how it impacts in the actual procedure. We performed a pilot study on robot-assisted MRI-guided prostate biopsy with an emphasis on the in-depth analysis of the needle-tissue interaction in-vivo. Methods: The data were acquired during in-bore transperineal prostate biopsies in patients using a 4 degrees-of-freedom (DoF) MRI-compatible robot. The anatomical structures in the pelvic area and the needle path were reconstructed from MR images, and quantitatively analyzed. We analyzed each structure individually and also proposed a mathematical model to investigate the influence of those structures in the targeting error using the mixed-model regression. Results: The median targeting error in 188 insertions (27 patients) was 6.3mm. Both the individual anatomical structure analysis and the mixed-model analysis showed that the deviation resulted from the contact between the needle and the skin as the main source of error. On contrary, needle bending inside the tissue (expressed as needle curvature) did not vary among insertions with targeting errors above and below the average. The analysis indicated that insertions crossing the bulbospongiosus presented a targeting error lower than the average. The mixed-model analysis demonstrated that the distance between the needle guide and the patient skin, the deviation at the entry point, and the path length inside the pelvic diaphragm had a statistically significant contribution to the targeting error (p<0.05). Conclusions: Our results indicate that the errors associated with the elastic contact between the needle and the skin were more prominent than the needle bending along the insertion. Our findings will help to improve the preoperative planning of transperineal prostate biopsies.
Guenette JP, Seethamraju RT, Jayender J, Corrales CE, Lee TC. MR Imaging of the Facial Nerve through the Temporal Bone at 3T with a Noncontrast Ultrashort Echo Time Sequence. AJNR Am J Neuroradiol. 2018;39 (10) :1903-6.Abstract
The pointwise encoding time reduction with radial acquisition (PETRA) ultrashort echo time MR imaging sequence at 3T enables visualization of the facial nerve from the brain stem, through the temporal bone, to the stylomastoid foramen without intravenous contrast. Use of the PETRA sequence, or other ultrashort echo time sequences, should be considered in the MR imaging evaluation of certain skull base tumors and perhaps other facial nerve and temporal bone pathologies.
Gao W, Jiang B, Kacher DF, Fetics B, Nevo E, Lee TC, Jayender J. Real-time Probe Tracking using EM-optical Sensor for MRI-guided Cryoablation . Int J Med Robot. 2018;14 (1).Abstract
BACKGROUND: A method of real-time, accurate probe tracking at the entrance of the MRI bore is developed, which, fused with pre-procedural MR images, will enable clinicians to perform cryoablation efficiently in a large workspace with image guidance. METHODS: Electromagnetic (EM) tracking coupled with optical tracking is used to track the probe. EM tracking is achieved with an MRI-safe EM sensor working under the scanner's magnetic field to compensate the line-of-sight issue of optical tracking. Unscented Kalman filter-based probe tracking is developed to smooth the EM sensor measurements when occlusion occurs and to improve the tracking accuracy by fusing the measurements of two sensors. RESULTS: Experiments with a spine phantom show that the mean targeting errors using the EM sensor alone and using the proposed method are 2.21 mm and 1.80 mm, respectively. CONCLUSION: The proposed method achieves more accurate probe tracking than using an EM sensor alone at the MRI scanner entrance.
Schmidt EJ, Halperin HR. MRI use for Atrial Tissue Characterization in Arrhythmias and for EP Procedure Guidance. Int J Cardiovasc Imaging. 2018;34 (1) :81-95.Abstract
We review the utilization of magnetic resonance imaging methods for classifying atrial tissue properties that act as a substrate for common cardiac arrhythmias, such as atrial fibrillation. We then review state-of-the-art methods for mapping this substrate as a predicate for treatment, as well as methods used to ablate the electrical pathways that cause arrhythmia and restore patients to sinus rhythm.
Jiang B, Gao W, Kacher D, Nevo E, Fetics B, Lee TC, Jayender J. Kalman Filter-based EM-optical Sensor Fusion for Needle Deflection Estimation. Int J Comput Assist Radiol Surg. 2018;13 (4) :573-83.Abstract
PURPOSE: In many clinical procedures such as cryoablation that involves needle insertion, accurate placement of the needle's tip at the desired target is the major issue for optimizing the treatment and minimizing damage to the neighboring anatomy. However, due to the interaction force between the needle and tissue, considerable error in intraoperative tracking of the needle tip can be observed as needle deflects. METHODS: In this paper, measurements data from an optical sensor at the needle base and a magnetic resonance (MR) gradient field-driven electromagnetic (EM) sensor placed 10 cm from the needle tip are used within a model-integrated Kalman filter-based sensor fusion scheme. Bending model-based estimations and EM-based direct estimation are used as the measurement vectors in the Kalman filter, thus establishing an online estimation approach. RESULTS: Static tip bending experiments show that the fusion method can reduce the mean error of the tip position estimation from 29.23 mm of the optical sensor-based approach to 3.15 mm of the fusion-based approach and from 39.96 to 6.90 mm, at the MRI isocenter and the MRI entrance, respectively. CONCLUSION: This work established a novel sensor fusion scheme that incorporates model information, which enables real-time tracking of needle deflection with MRI compatibility, in a free-hand operating setup.
Abayazid M, Kato T, Silverman SG, Hata N. Using Needle Orientation Sensing as Surrogate Signal for Respiratory Motion Estimation in Rercutaneous Interventions. Int J Comput Assist Radiol Surg. 2018;13 (1) :125-33.Abstract
PURPOSE: To develop and evaluate an approach to estimate the respiratory-induced motion of lesions in the chest and abdomen. MATERIALS AND METHODS: The proposed approach uses the motion of an initial reference needle inserted into a moving organ to estimate the lesion (target) displacement that is caused by respiration. The needles position is measured using an inertial measurement unit (IMU) sensor externally attached to the hub of an initially placed reference needle. Data obtained from the IMU sensor and the target motion are used to train a learning-based approach to estimate the position of the moving target. An experimental platform was designed to mimic respiratory motion of the liver. Liver motion profiles of human subjects provided inputs to the experimental platform. Variables including the insertion angle, target depth, target motion velocity and target proximity to the reference needle were evaluated by measuring the error of the estimated target position and processing time. RESULTS: The mean error of estimation of the target position ranged between 0.86 and 1.29 mm. The processing maximum training and testing time was 5 ms which is suitable for real-time target motion estimation using the needle position sensor. CONCLUSION: The external motion of an initially placed reference needle inserted into a moving organ can be used as a surrogate, measurable and accessible signal to estimate in real-time the position of a moving target caused by respiration; this technique could then be used to guide the placement of subsequently inserted needles directly into the target.
Li M, Narayan V, Gill RR, Jagannathan JP, Barile MF, Gao F, Bueno R, Jayender J. Computer-Aided Diagnosis of Ground-Glass Opacity Nodules Using Open-Source Software for Quantifying Tumor Heterogeneity. AJR Am J Roentgenol. 2017;209 (6) :1216-27.Abstract
OBJECTIVE: The purposes of this study are to develop quantitative imaging biomarkers obtained from high-resolution CTs for classifying ground-glass nodules (GGNs) into atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC); to evaluate the utility of contrast enhancement for differential diagnosis; and to develop and validate a support vector machine (SVM) to predict the GGN type. MATERIALS AND METHODS: The heterogeneity of 248 GGNs was quantified using custom software. Statistical analysis with a univariate Kruskal-Wallis test was performed to evaluate metrics for significant differences among the four GGN groups. The heterogeneity metrics were used to train a SVM to learn and predict the lesion type. RESULTS: Fifty of 57 and 51 of 57 heterogeneity metrics showed statistically significant differences among the four GGN groups on unenhanced and contrast-enhanced CT scans, respectively. The SVM predicted lesion type with greater accuracy than did three expert radiologists. The accuracy of classifying the GGNs into the four groups on the basis of the SVM algorithm was 70.9%, whereas the accuracy of the radiologists was 39.6%. The accuracy of SVM in classifying the AIS and MIA nodules was 73.1%, and the accuracy of the radiologists was 35.7%. For indolent versus invasive lesions, the accuracy of the SVM was 88.1%, and the accuracy of the radiologists was 60.8%. We found that contrast enhancement does not significantly improve the differential diagnosis of GGNs. CONCLUSION: Compared with the GGN classification done by the three radiologists, the SVM trained regarding all the heterogeneity metrics showed significantly higher accuracy in classifying the lesions into the four groups, differentiating between AIS and MIA and between indolent and invasive lesions. Contrast enhancement did not improve the differential diagnosis of GGNs.
Mallory MA, Sagara Y, Aydogan F, Desantis S, Jayender J, Caragacianu D, Gombos E, Vosburgh KG, Jolesz FA, Golshan M. Feasibility of Intraoperative Breast MRI and the Role of Prone Versus Supine Positioning in Surgical Planning for Breast-Conserving Surgery. Breast J. 2017;23 (6) :713-7.Abstract
We assessed the feasibility of supine intraoperative MRI (iMRI) during breast-conserving surgery (BCS), enrolling 15 patients in our phase I trial between 2012 and 2014. Patients received diagnostic prone MRI, BCS, pre-excisional supine iMRI, and postexcisional supine iMRI. Feasibility was assessed based on safety, sterility, duration, and image-quality. Twelve patients completed the study; mean duration = 114 minutes; all images were adequate; no complications, safety, or sterility issues were encountered. Substantial tumor-associated changes occurred (mean displacement = 67.7 mm, prone-supine metric, n = 7). We have demonstrated iMRI feasibility for BCS and have identified potential limitations of prone breast MRI that may impact surgical planning.