Letter: Image Segmentation in Neurosurgery: An Undervalued Skill Set?

Ann, Chu Ning; Luo, Nianhe; Pandit, Anand

doi:10.1227/neu.0000000000002018

Neurosurgery

2022

DOI: 10.1227/neu.0000000000002018

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Letter: Image Segmentation in Neurosurgery: An Undervalued Skill Set?

Chu Ning Ann

Nianhe Luo

Anand Pandit

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Cited by 2 publications

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“…8,9 The overarching goal of this research is to augment certain elements of surgical planning and decision-making with the hope of benefiting both the surgeon and patients alike. 10 When examining the landscape of segmentation within spine surgery, there is a clear delineation in the volume of segmentation research and the scope of its usage intraoperatively. Most focus has been placed on vertebral body segmentation and pedicle screw placement, with studies showing that deep learning can assist both the preoperative planning and intraoperative autonomous placement of pedicle screws with high levels of accuracy.…”

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confidence: 99%

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Using Novel Segmentation Technology to Define Safe Corridors for Minimally Invasive Posterior Lumbar Interbody Fusion

Tabarestani,

Salven,

Sykes

et al. 2023

Operative Neurosurgery

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BACKGROUND AND OBJECTIVES: There has been a rise in minimally invasive methods to access the intervertebral disk space posteriorly given their decreased tissue destruction, lower blood loss, and earlier return to work. Two such options include the percutaneous lumbar interbody fusion through the Kambin triangle and the endoscopic transfacet approach. However, without accurate preoperative visualization, these approaches carry risks of damaging surrounding structures, especially the nerve roots. Using novel segmentation technology, our goal was to analyze the anatomic borders and relative sizes of the safe triangle, trans-Kambin, and the transfacet corridors to assist surgeons in planning a safe approach and determining cannula diameters. METHODS: The areas of the safe triangle, Kambin, and transfacet corridors were measured using commercially available software (BrainLab, Munich, Germany). For each approach, the exiting nerve root, traversing nerve roots, theca, disk, and vertebrae were manually segmented on 3-dimensional T2-SPACE magnetic resonance imaging using a region-growing algorithm. The triangles' borders were delineated ensuring no overlap between the area and the nerves. RESULTS: A total of 11 patients (65.4 ± 12.5 years, 33.3% female) were retrospectively reviewed. The Kambin, safe, and transfacet corridors were measured bilaterally at the operative level. The mean area (124.1 ± 19.7 mm2 vs 83.0 ± 11.7 mm2 vs 49.5 ± 11.4 mm2) and maximum permissible cannula diameter (9.9 ± 0.7 mm vs 6.8 ± 0.5 mm vs 6.05 ± 0.7 mm) for the transfacet triangles were significantly larger than Kambin and the traditional safe triangles, respectively (P < .001). CONCLUSION: We identified, in 3-dimensional, the borders for the transfacet corridor: the traversing nerve root extending inferiorly until the caudal pedicle, the theca medially, and the exiting nerve root superiorly. These results illustrate the utility of preoperatively segmenting anatomic landmarks, specifically the nerve roots, to help guide decision-making when selecting the optimal operative approach.

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mentioning

confidence: 99%

“…8,9 The overarching goal of this research is to augment certain elements of surgical planning and decision-making with the hope of benefiting both the surgeon and patients alike. 10…”

mentioning

confidence: 99%

Using Novel Segmentation Technology to Define Safe Corridors for Minimally Invasive Posterior Lumbar Interbody Fusion

Tabarestani,

Salven,

Sykes

et al. 2023

Operative Neurosurgery

View full text Add to dashboard Cite

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A Practical Guide to Manual and Semi-Automated Neurosurgical Brain Lesion Segmentation

Jain,

Lee,

Luo

et al. 2024

NeuroSci

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The purpose of the article is to provide a practical guide for manual and semi-automated image segmentation of common neurosurgical cranial lesions, namely meningioma, glioblastoma multiforme (GBM) and subarachnoid haemorrhage (SAH), for neurosurgical trainees and researchers. Materials and Methods: The medical images used were sourced from the Medical Image Computing and Computer Assisted Interventions Society (MICCAI) Multimodal Brain Tumour Segmentation Challenge (BRATS) image database and from the local Picture Archival and Communication System (PACS) record with consent. Image pre-processing was carried out using MRIcron software (v1.0.20190902). ITK-SNAP (v3.8.0) was used in this guideline due to its availability and powerful built-in segmentation tools, although others (Seg3D, Freesurfer and 3D Slicer) are available. Quality control was achieved by employing expert segmenters to review. Results: A pipeline was developed to demonstrate the pre-processing and manual and semi-automated segmentation of patient images for each cranial lesion, accompanied by image guidance and video recordings. Three sample segmentations were generated to illustrate potential challenges. Advice and solutions were provided within both text and video. Conclusions: Semi-automated segmentation methods enhance efficiency, increase reproducibility, and are suitable to be incorporated into future clinical practise. However, manual segmentation remains a highly effective technique in specific circumstances and provides initial training sets for the development of more advanced semi- and fully automated segmentation algorithms.

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Letter: Image Segmentation in Neurosurgery: An Undervalued Skill Set?

Cited by 2 publications

References 26 publications

Using Novel Segmentation Technology to Define Safe Corridors for Minimally Invasive Posterior Lumbar Interbody Fusion

Using Novel Segmentation Technology to Define Safe Corridors for Minimally Invasive Posterior Lumbar Interbody Fusion

A Practical Guide to Manual and Semi-Automated Neurosurgical Brain Lesion Segmentation

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