Sensitivity analysis and automation for intraoperative implementation of the atlas-based method for brain shift correction

ABSTRACT The use of biomechanical models to correct the misregistration due to deformation in image guided neurosurgical systems has been a growing area of investigation. In previous work, an atlas-based inverse model was developed to account for soft-tissue deformations during image-guided surgery. Central to that methodology is a considerable amount of pre-computation and planning. The goal of this work is to evaluate techniques that could potentially reduce that burden. Distinct from previous manual techniques, an automated segmentation technique is described for the cerebrum and dural septa. The shift correction results using this automated segmentation method were compared to those using the manual methods. In addition, the extent and distribution of the surgical parameters associated with the deformation atlas were investigated by a sensitivity analysis using simulation experiments and clinical data. The shift correction results did not change significantly using the automated method (correction of 73±13% ) as compared to the semi-automated method from previous work (correction of 76±13%). The results of the sensitivity analysis show that the atlas could be constructed by coarser sampling (six fold reduction) without substantial degradation in the shift reconstruction, a decrease in preoperative computational time from 13.1±3.5 hours to 2.2±0.6 hours. The automated segmentation technique and the findings of the sensitivity study have significant impact on the reduction of pre-operative computational time, improving the utility of the atlas-based method. The work in this paper suggests that the atlas-based technique can become a 'time of surgery' setup procedure rather than a pre-operative computing strategy

MRI-only radiotherapy treatment planning of the brain

Advancements in imaging methods have made it possible to create synthetic computed tomography (sCT) images from magnetic resonance imaging (MRI) data. MRI-based methods enable computed tomography (CT) to be omitted from the radiotherapy (RT) workflow and transitioning into MRI-only radiotherapy planning (RTP) of the brain. Geometric distortions in magnetic resonance (MR) images and the resulting image quality of generated sCTs are a challenge for the accuracy requirements of RT compared with CT-based methods of RTP. The current dissertation evaluated the suitability of the latest MRI scanners for MRI-only RTP, and the clinical feasibility of present quality assurance methods for measuring geometric accuracy. The clinical feasibility of MRI-only brain RTP of two different sCT generation methods was also investigated. The magnetic resonance attenuation correction (MRAC) based sCT generation method was evaluated for dosimetric accuracy. Additionally, the clinical feasibility of a commercially available deep learning based sCT generation algorithm was evaluated in terms of dosimetric and patient positioning accuracy. Based on the results of the current dissertation, the geometric accuracy of stateof-the-art MRI scanners were shown to meet the requirements of MRI-only based brain RTP. The results also showed that the sCT images generated by the MRAC method are useful for performing dose calculation in the brain. The sCTs generated using a commercial method demonstrated clinical feasibility of dose calculation and patient positioning for MRI-only brain RTP.Magneettikuvauspohjainen sädehoidon suunnittelu aivojen alueella Kuvantamismenetelmien kehitys on mahdollistanut pelkästään magneettikuvauksesta (MK) saatavaan informaatioon perustuen ns. synteettisten tietokonetomografiakuvien (sTT) muodostamisen aivojen alueella. MK-pohjaisten menetelmien avulla on mahdollista luopua kokonaan tietokonetomografiasta (TT) osana sädehoidon suunnitteluketjua ja siirtyä aivojen alueella kokonaan MKpohjaiseen sädehoidon suunnitteluun. Magneettikuvissa esiintyvät geometriset vääristymät, sekä niiden pohjalta muodostettavien sTT-kuvien laatu ovat mahdollinen haaste sädehoidon tarkkuusvaatimusten kannalta verrattuna TTkuvaukseen pohjautuviin menetelmiin. Tässä väitöstutkimuksessa arvioitiin nykyisin käytössä olevien MKlaitteiden soveltuvuutta MK-pohjaiseen sädehoidon suunnitteluun, ja nykyisin käytössä olevien geometrisen tarkkuuden laadunvarmistusmenetelmien soveltuvuutta kliiniseen laadunvalvontaan sädehoidossa. MK-pohjaisen sädehoidon suunnittelun kliinistä soveltuvuutta aivojen alueelle tutkittiin kahdella eri menetelmällä. MK-pohjaiseen vaimennuskorjausmenetelmään perustuvan sTTgenerointimallin soveltuvuutta arvioitiin annoslaskennan tarkkuuden osalta. Lisäksi tutkittiin kaupallisen, syväoppimiseen pohjautuvan algoritmin tuottamien sTTkuvien soveltuvuutta kliiniseen käyttöön annoslaskennan ja potilasasettelun verifioinnin tarkkuuden osalta. Väitöstutkimuksen tulosten perusteella voitiin osoittaa, että nykyaikaiset MK-laitteet täyttävät geometrisen tarkkuuden osalta vaatimukset MK-pohjaiseen sädehoidon suunnittelukuvantamiseen pään alueella. Lisäksi tulokset osoittivat, että MK-pohjaiseen vaimennuskorjaukseen pohjautuvalla menetelmällä luodut sTTkuvat soveltuvat sädehoidon annoslaskennan toteuttamiseen aivojen alueella. Kaupallisella menetelmällä luodut sTT-kuvat voitiin todeta soveltuviksi kliiniseen käyttöön sädehoidon suunnittelussa aivojen alueella annoslaskennan ja potilasasettelun verifioinnin tarkkuuden osalta

Atlas-based segmentation of the brain for 3-dimensional treatment planning in children with infratentorial ependymoma

This paper presents a fully automated brain segmentation method that has been applied to a group of patients with infratentorial ependymoma. The purpose of the study was to test the hypothesis that fully-automated atlas-based segmentation methods provide useful normal tissue dosimetry from which dose-volume modeling may be performed in a manner equivalent to dose-volume data obtained from manual contouring. To test this hypothesis, we compared the integrated average dose for three small (chiasm, pituitary, hypothalamus) and three large (temporal lobes and total brain) normal tissue structures from ten patients using automated and manual contouring. There was no significant difference in the calculated average dose for the structures of interest. The greatest difference was noted for smaller structures which were located along the midline and in the gradient of dose. The results of this study form the basis of an ongoing larger study involving similar patients to evaluate automated and manual contouring as well as the clinical significance of any differences using dose-volume modeling