Accuracy of 3-D Planning and Navigation in Bone Tumor Resection

Ritacco, Lucas E.; Milano, Federico; Farfalli, Germán L.; Ayerza, Miguel A.; Múscolo, D. Luis; Aponte-Tinao, Luis A.

doi:10.3928/01477447-20130624-27

Cited by 77 publications

(65 citation statements)

References 18 publications

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“…The use of computer-assisted navigation technologies might help surgeons perform more accurate resections [2,11,15]. However, some papers have reported problems related to the use of navigation, including increased operative time as a result of the additional technological complexity; in addition, there is no evidence of which we are aware suggesting that navigation decreases the risk of local recurrence [7,16].…”

Section: Discussionmentioning

confidence: 99%

“…Several factors could be related to local recurrences [5], but in general, surgical margin is a major factor related to this problem [10]. Computer-assisted surgery has shown that it provides accuracy in oncological resection [15]. However, the surgeon can perform a misreading of preoperative images, making inadequate cuts that could lead to inadequate margins.…”

Section: Discussionmentioning

confidence: 99%

“…3). The directions of the bone cuts were determined with the pointer and the osteotomies performed with an oscillating saw [15].…”

Section: Methodsmentioning

confidence: 99%

“…This surgical assistance is becoming more frequently used in limb salvage surgery to preserve as much host tissue as possible without compromising tumor margins and may help surgeons perform more accurate resections [11,15,16,18]. However, previous reports about navigation in trauma and arthroplasty have suggested that computer assistance techniques do not improve patient-reported outcomes and that these techniques add surgical time [6,8,13,20].…”

Section: Introductionmentioning

confidence: 99%

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What Is the Expected Learning Curve in Computer-assisted Navigation for Bone Tumor Resection?

Farfalli

Albergo

Ritacco

et al. 2017

Clinical Orthopaedics &Amp; Related Research

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Background Computer navigation during surgery can help oncologic surgeons perform more accurate resections. However, some navigation studies suggest that this tool may result in unique intraoperative problems and increased surgical time. The degree to which these problems might diminish with experience-the learning curve-has not, to our knowledge, been evaluated for navigation-assisted tumor resections. Questions/purposes (1) What intraoperative technical problems were observed during the first 2 years using navigation? (2) What was the mean time for navigation procedures and the time improvement during the learning curve? (3) Have there been any differences in the accuracy of the registration technique that occurred over time? (4) Did navigation achieve the goal of achieving a wide bone margin? Methods All patients who underwent preoperative virtual planning for tumor bone resections and operated on with navigation assistance from 2010 to 2012 were prospectively collected. Two surgeons (GLF, LAA-T) performed the intraoperative navigation assistance. Both surgeons had more than 5 years of experience in orthopaedic oncology with more than 60 oncology cases per year per surgeon. This study includes from the very first patients performed with navigation. Although they did not take any formal training in orthopaedic oncology navigation, both surgeons were trained in navigation for knee prostheses. Between 2010 and 2012, we performed 124 bone tumor resections; of these, 78 (63%) cases were resected using intraoperative navigation assistance. During this period, our general indications for use of navigation included pelvic and sacral tumors and those tumors that were reconstructed with massive bone allografts to obtain precise matching of the host and allograft osteotomies. Seventy-eight patients treated with this technology were included in the study. Technical problems (crashes) and time for the navigation procedure were reported after surgery. Accuracy of the registration technique was defined and the surgical margins of the removed specimen were determined by an experienced bone pathologist after the surgical procedure as intralesional, marginal, or wide margins. To obtain these One of the authors certifies that he (LAA-T) or a member of his immediate family, has or may receive payments or benefits, during the study period, an amount of USD 10,000 to USD 100,000 from Stryker Americas (Miramar, FL, USA 123 Clin Orthop Relat Res (2017) 475:668-675 DOI 10.1007/s11999-016-4761-z Clinical Orthopaedics and Related Research ® A Publication of The Association of Bone and Joint Surgeons® data, we performed a chart review and review of operative notes.Results In four patients (of 78 [5%]), the navigation was not completed as a result of technical problems; all occurred during the first 20 cases of the utilization of this technology. The mean time for navigation procedures during the operation was 31 minutes (range, 11-61 minutes), and the early navigations took more time (the regression analysis shielded R 2 = 0.35 ...

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

“…3). The directions of the bone cuts were determined with the pointer and the osteotomies performed with an oscillating saw [15].…”

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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What Is the Expected Learning Curve in Computer-assisted Navigation for Bone Tumor Resection?

Farfalli

Albergo

Ritacco

et al. 2017

Clinical Orthopaedics &Amp; Related Research

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“…12 The previous method had several limitations in its efficacy to find good planar fits in noisy images. Also, there were no data of nonassisted surgery available at the time to compare with IGS data.…”

Section: Clinical Background and Related Workmentioning

confidence: 99%

Transfer accuracy and precision scoring in planar bone cutting validated with ex vivo data

Milano

Ritacco

Farfalli

et al. 2015

Journal Orthopaedic Research

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The use of interactive surgical scenarios for virtual preoperative planning of osteotomies has increased in the last 5 years. As it has been reported by several authors, this technology has been used in tumor resection osteotomies, knee osteotomies, and spine surgery with good results. A digital three-dimensional preoperative plan makes possible to quantitatively evaluate the transfer process from the virtual plan to the anatomy of the patient. We introduce an exact definition of accuracy and precision of this transfer process for planar bone cutting. We present a method to compute these properties from ex vivo data. We also propose a clinical score to assess the goodness of a cut. A computer simulation is used to characterize the definitions and the data generated by the measurement method Keywords: osteotomy; cut; accuracy; precision; clinical score Clinical Background and Related WorkComputer-Assisted Preoperative Planning in bone surgery is becoming more common everyday. Its use has been reported in knee osteotomy, 1 mandibular reconstruction, 2 spine surgery, 3 foot and ankle surgery, 4 and tumor resection. 5 The existence of virtual osteotomy planning opens the possibility of measuring the discrepancies that occur in the transfer from the target to the executed osteotomies. These discrepancies are very common since many factors add random variations and biases to the surgical process: CT/MR imaging errors, three-dimensional modeling and segmentation omissions and the inherent inaccuracies of surgical tools and actions. Even though the evaluation of transfer accuracy (ACC) and precision (PRC) in bone cutting is a key application in orthopedics, there is no consensus about their definition in the field of planar osteotomies, neither there is an established method to measure them nor a score to assess them. 6 In recent years, several research groups have approached the accuracy and precision estimation problem in bone cutting. Barrera et al. 7 introduced a way to evaluate planar osteotomies in total knee replacement using translational and rotational errors of the executed plane measured against the target plane. More recently, Cartiaux et al. 8 proposed a method based in the ISO 1101:2004 standard for geometrical tolerancing to evaluate differences between a cutting plane and a target plane. Their work shows that it is possible to express the most significant translational and rotational errors using only the location parameter (L) defined in the mentioned ISO standard. For experimental data gathering, a test bed with a block simulating bone tissue is used, and errors are estimated with a coordinate measuring machine set in the same frame of reference. Dobbe et al. 9 propose a method to measure and estimate the normal of an executed plane. This normal is used to compute the dihedral angle with the target plane, that is decomposed in sagittal and coronal plane angles. Then a distance error between the target and executed plane is computed taking the Euler distance between the centroids of the cross ...

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Image Registration in Medical Robotics and Intelligent Systems: Fundamentals and Applications

Liu

Singh

Al’Aref

et al. 2019

Advanced Intelligent Systems

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Medical image registration, by transforming two or more sets of imaging data into one coordinate system, plays a central role in medical robotics and intelligent systems from diagnostics and surgical planning to real‐time guidance and postprocedural assessment. Recent advances in medical image registration have made a significant impact in orthopedic, neurological, cardiovascular, and oncological applications.The recent literature in medical image registration is reviewed, providing a discussion of their fundamentals and applications. Within each section, the registration techniques are introduced, classifying each method based on their working mechanisms, and discussing their benefits and limitations are discussed. Recently, machine learning has had an important impact on the field of image registration, yielding novel methods and unprecedented speed. The validation of registration methods, however, remains a challenge due to the lack of reliable ground truth. Medical image registration will continue to make significant impacts in the area of advanced medical imaging, as the fusion/combination of multimodal images and advanced visualization technology become more widespread.

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Accuracy of 3-D Planning and Navigation in Bone Tumor Resection

Cited by 77 publications

References 18 publications

What Is the Expected Learning Curve in Computer-assisted Navigation for Bone Tumor Resection?

What Is the Expected Learning Curve in Computer-assisted Navigation for Bone Tumor Resection?

Transfer accuracy and precision scoring in planar bone cutting validated with ex vivo data

Image Registration in Medical Robotics and Intelligent Systems: Fundamentals and Applications

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