Comparison of laser surface scanning and fiducial marker–based registration in frameless stereotaxy

Schicho, Kurt; Figl, Michael; Seemann, Rudolf; Donat, Markus; Pretterklieber, Michael L.; Birkfellner, Wolfgang; Reichwein, Astrid; Wanschitz, Felix; Kainberger, Franz; Bergmann, Helmar; Wagner, A.; Ewers, Rolf

doi:10.3171/jns.2007.106.4.704

Cited by 70 publications

(48 citation statements)

References 14 publications

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“…For the STN-DBS patients, the mean preoperative L -dopa response was 52.55% and the mean L -dopa response status was 14.25 [4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19]. The mean UPDRS III improvement at 6 months was 75% (mean ‘off med' score before surgery = 30.8 [13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45], mean score ‘on stim/on med' = 7.8 [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17], mean ‘on stim/off med' score after 6 months = 14.15 [5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26]). There was neither mortality nor morbidity (permanent nor transient) related to the DBS surgeries.…”

Section: Resultsmentioning

confidence: 99%

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The Impact of the Reference Imaging Modality, Registration Method and Intraoperative Flat-Panel Computed Tomography on the Accuracy of the ROSA® Stereotactic Robot

Lefranc

Capel²,

Pruvot³

et al. 2014

Stereotact Funct Neurosurg

103

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Objective: To establish the impact of the imaging modality, registration method and use of intraoperative computed tomography (CT) scan on the accuracy of the ROSA® stereotactic robot. Methods: Using a dedicated phantom device, we measured the accuracy of the stereotactic robot for 20 targets as a function of the registration method (frameless, FL, or frame-based, FB) and the reference imaging modality (3T magnetic resonance imaging, MRI, CT scanner or flat-panel CT, fpCT). We performed a retrospective study of the accuracy of the first 26 FB and 31 FL robotized stereotactic surgeries performed in our department. Results: In a phantom study, the mean target accuracy was 1.59 mm for 3T MRI-guided FL surgery, 0.3 mm for fpCT-guided FL surgery and 0.3 mm for CT-guided FB surgery. In our retrospective series, the mean accuracy was 0.81 mm for FB stereotactic surgery, 1.22 mm for our 24 stereotactic surgery procedures with FL (surface recognition) registration and 0.7 mm for our 7 stereotactic surgery procedures with FL fiducial marker registration. Intraoperative fpCT fully corrected all the registration errors. Conclusions: The ROSA stereotactic robot is highly accurate. Robotized FB stereotactic surgery is more accurate than robotized FL stereotactic surgery.

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Section: Resultsmentioning

confidence: 99%

“…The patients were in the same operative position and under general anesthesia when the imaging and registration were realized. FB procedures are subject only to the geometric quality of the image acquired, whereas FL procedures also depend on the quality of head reconstruction during surfacing [16], [25]. …”

Section: Discussionmentioning

confidence: 99%

The Impact of the Reference Imaging Modality, Registration Method and Intraoperative Flat-Panel Computed Tomography on the Accuracy of the ROSA® Stereotactic Robot

Lefranc

Capel²,

Pruvot³

et al. 2014

Stereotact Funct Neurosurg

103

View full text Add to dashboard Cite

show abstract

“…The results showed a higher state of accuracy with FM registration than surface registration, compared to Schicho's study (14), yet there was no statistically significant difference. The current research used the touch surface registration on the lateral side of the head (mastoid to temporal area).…”

Section: Discussionmentioning

confidence: 53%

Accuracy Assessment of Different Registration and Imaging Methods on Image-Guided Surgery of Lateral Skull Base

et al. 2018

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Background: The use of Image Guided Surgery (IGS) systems at lateral skull base surgery is controversial due to the limitation of the accuracy of the systems. The intraoperative accuracy of the IGS is dependent on deferent parameters, mainly the precision of the system, resolution of utilized imaging, rigidity of the reference frame/adaptor, registration method, calibration of the utilized instruments, and intraoperative movement of the reference markers. Objectives: In this study the researchers examined the target registration error of an electromagnetic IGS system on different important structures of lateral skull base through different approaches. This study compared two registration methods and two scanning systems. Methods: In 10 formaldehyde-fixed human cadaver heads, 69 target points were marked with titanium screws for determining target registration errors. The target points were facial nerve, lateral semi-circular canal, geniculate ganglion, superior semi-circular canal, internal auditory canal, and the foramen rotundum. Seven heads were scanned using a Cone Beam CT Scanner (CBCT) and three heads were scanned using a CT scanner. Three screws were implanted around the mastoidectomy cavity as Fiducial Markers (FM). Two different registration methods were applied, including point based registration using the FM versus surface registration. All samples were dissected via the middle cranial fossa approach, retrosigmoid approach, and transmastoid approaches. Results: The overall accuracy of the IGS-system was 1.2 mm and plusmn; 0.15 mm. Optimum accuracy was reached with CBCT-scan and the FM registration marker. Navigation using CT scans with the surface registration method, using CT scans with FM registration method, and using CBCT-scans with surface registration method had lower accuracy, respectively, yet their difference was not statistically significant (P > 0.5). The best accuracy was noted on the facial nerve in the mastoid approach (mean 0.8 mm). Conclusions:The feasibility of the use of an electromagnetic IGS system in lateral skull base, surgery using Cone Beam CT as well as conventional CT scanner with fiducial marker registration as well as surface registration were evaluated. The accuracy was best at the lateral region of the temporal bone and decreased on further medial targets, such as lower cranial nerve and trigeminal ganglion.

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“…One type was a line scanning device, such as the z-touch (BrainLAB, Feldkirchen, Germany) [9,14] or Fazer (Medtronic, Inc.) [10], which was usually included as part of a commercial neuronavigation system. The other type was a surface scanning device that scanned a 3D surface as a whole instead of several lines, such as the VI 900 (Minolta, Osaka, Japan) [16] or faceSCAN II (Breuckmann, Meersburg, Germany) [15].…”

Section: Methodsmentioning

confidence: 99%

“…Usually, the image space and patient space were registered by these two approaches then the TRE was measured at a small number of anatomical or artificial landmarks for each method. In some studies the TRE calculated for these two registration methods was similar [5][6][7], while in others the TRE for point matching was smaller than that for surface matching [8][9][10]. According to the research on TRE distribution in point matching [11,12], the TRE varies at different points in the same registration.…”

Section: Introductionmentioning

confidence: 99%

Properties of the target registration error for surface matching in neuronavigation

Wang

Song

2011

Computer Aided Surgery

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Objective: Surface matching is a relatively new method of spatial registration in neuronavigation. Compared to the traditional point matching method, surface matching does not use fiducial markers that must be fixed to the surface of the head before image scanning, and therefore does not require an image acquisition specifically dedicated for navigation purposes. However, surface matching is not widely used clinically, mainly because there is still insufficient knowledge about its application accuracy. This study aimed to explore the properties of the Target Registration Error (TRE) of surface matching in neuronavigation. Materials and Methods: The surface matching process was simulated in the image space of a neuronavigation system so that the TRE could be calculated at any point in that space. For each registration, two point clouds were generated to represent the surface extracted from preoperative images (PC image ) and the surface obtained intraoperatively by laser scanning (PC laser ). The properties of the TRE were studied by performing multiple registrations with PC laser point clouds at different positions and generated by adding different types of error. Results: For each registration, the TRE had a minimal value at a point in the image space, and the iso-valued surface of the TRE was approximately ellipsoid with smaller TRE on the inner surfaces. The position of the point with minimal TRE and the shape of the iso-valued surface were highly random across different registrations, and the surface registration error between the two point clouds was irrelevant to the TRE at a specific point. The overall TRE tended to increase with the increase in errors in PC laser , and a larger PC laser made it less sensitive to these errors. With the introduction of errors in PC laser , the points with minimal TRE tended to be concentrated in the anterior and inferior part of the head. Conclusion:The results indicate that the alignment between the two surfaces could not provide reliable information about the registration accuracy at an arbitrary target point. However, according to the spatial distribution of the target registration error of a single registration, enough application accuracy could be guaranteed by proper visual verification after registration. In addition, surface matching tends to achieve high accuracy in the inferior and anterior part of the head, and a relatively large scanning area is preferable.

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Comparison of laser surface scanning and fiducial marker–based registration in frameless stereotaxy

Cited by 70 publications

References 14 publications

The Impact of the Reference Imaging Modality, Registration Method and Intraoperative Flat-Panel Computed Tomography on the Accuracy of the ROSA® Stereotactic Robot

The Impact of the Reference Imaging Modality, Registration Method and Intraoperative Flat-Panel Computed Tomography on the Accuracy of the ROSA® Stereotactic Robot

Accuracy Assessment of Different Registration and Imaging Methods on Image-Guided Surgery of Lateral Skull Base

Properties of the target registration error for surface matching in neuronavigation

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