Dataset Information

No Longer a Pain in the Neck: Use of Operating Microscope for Palatoplasty.

ABSTRACT: For craniofacial surgeons, cleft palate repair is an intricate and difficult operation positionally. Historically, use of loupe magnification and a headlight can cause significant strain to the surgeon's neck and, at times, subpar optics for both the operator and the assistant. The use of an operating microscope was first advocated by Sommerlad in 2003. By using the operating microscope for cleft palate closure, there are improved ergonomics for the surgeon and assistant by allowing for straight in-line back and neck posture with excellent visualization of the surgical field for the entire surgical team. The available zoom and focus improve the ability to isolate and repair the levator veli palatini muscle. Proper posture with a neutral cervical spine will help prolong a surgeon's career and ability to care for their patients.

SUBMITTER: Tanaka SA

PROVIDER: S-EPMC7647538 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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No Longer a Pain in the Neck: Use of Operating Microscope for Palatoplasty.

Tanaka Shoichiro A SA Patel Nilesh M NM Murthy Ananth S AS

Plastic and reconstructive surgery. Global open 20201029 10

For craniofacial surgeons, cleft palate repair is an intricate and difficult operation positionally. Historically, use of loupe magnification and a headlight can cause significant strain to the surgeon's neck and, at times, subpar optics for both the operator and the assistant. The use of an operating microscope was first advocated by Sommerlad in 2003. By using the operating microscope for cleft palate closure, there are improved ergonomics for the surgeon and assistant by allowing for straight ...[more]

PMID: 33173699

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Project description:One of the major challenges impeding advancement in image-guided surgical (IGS) systems is the soft-tissue deformation during surgical procedures. These deformations reduce the utility of the patient's preoperative images and may produce inaccuracies in the application of preoperative surgical plans. Solutions to compensate for the tissue deformations include the acquisition of intraoperative tomographic images of the whole organ for direct displacement measurement and techniques that combines intraoperative organ surface measurements with computational biomechanical models to predict subsurface displacements. The later solution has the advantage of being less expensive and amenable to surgical workflow. Several modalities such as textured laser scanners, conoscopic holography, and stereo-pair cameras have been proposed for the intraoperative 3D estimation of organ surfaces to drive patient-specific biomechanical models for the intraoperative update of preoperative images. Though each modality has its respective advantages and disadvantages, stereo-pair camera approaches used within a standard operating microscope is the focus of this article. A new method that permits the automatic and near real-time estimation of 3D surfaces (at 1 Hz) under varying magnifications of the operating microscope is proposed. This method has been evaluated on a CAD phantom object and on full-length neurosurgery video sequences (?1 h) acquired intraoperatively by the proposed stereovision system. To the best of our knowledge, this type of validation study on full-length brain tumor surgery videos has not been done before. The method for estimating the unknown magnification factor of the operating microscope achieves accuracy within 0.02 of the theoretical value on a CAD phantom and within 0.06 on 4 clinical videos of the entire brain tumor surgery. When compared to a laser range scanner, the proposed method for reconstructing 3D surfaces intraoperatively achieves root mean square errors (surface-to-surface distance) in the 0.28-0.81 mm range on the phantom object and in the 0.54-1.35 mm range on 4 clinical cases. The digitization accuracy of the presented stereovision methods indicate that the operating microscope can be used to deliver the persistent intraoperative input required by computational biomechanical models to update the patient's preoperative images and facilitate active surgical guidance.

Project description:There have been few anatomical structure segmentation studies using deep learning. Numbers of training and ground truth images applied were small and the accuracies of which were low or inconsistent. For a surgical video anatomy analysis, various obstacles, including a variable fast-changing view, large deformations, occlusions, low illumination, and inadequate focus occur. In addition, it is difficult and costly to obtain a large and accurate dataset on operational video anatomical structures, including arteries. In this study, we investigated cerebral artery segmentation using an automatic ground-truth generation method. Indocyanine green (ICG) fluorescence intraoperative cerebral videoangiography was used to create a ground-truth dataset mainly for cerebral arteries and partly for cerebral blood vessels, including veins. Four different neural network models were trained using the dataset and compared. Before augmentation, 35,975 training images and 11,266 validation images were used. After augmentation, 260,499 training and 90,129 validation images were used. A Dice score of 79% for cerebral artery segmentation was achieved using the DeepLabv3+ model trained using an automatically generated dataset. Strict validation in different patient groups was conducted. Arteries were also discerned from the veins using the ICG videoangiography phase. We achieved fair accuracy, which demonstrated the appropriateness of the methodology. This study proved the feasibility of operating field view of the cerebral artery segmentation using deep learning, and the effectiveness of the automatic blood vessel ground truth generation method using ICG fluorescence videoangiography. Using this method, computer vision can discern blood vessels and arteries from veins in a neurosurgical microscope field of view. Thus, this technique is essential for neurosurgical field vessel anatomy-based navigation. In addition, surgical assistance, safety, and autonomous surgery neurorobotics that can detect or manipulate cerebral vessels would require computer vision to identify blood vessels and arteries.

Dataset Information

No Longer a Pain in the Neck: Use of Operating Microscope for Palatoplasty.

Publications

No Longer a Pain in the Neck: Use of Operating Microscope for Palatoplasty.

Similar Datasets

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