Literature DB >> 12873691

Validation of a method for automatic image fusion (BrainLAB System) of CT data and 11C-methionine-PET data for stereotactic radiotherapy using a LINAC: first clinical experience.

Anca-Ligia Grosu1, Rainer Lachner, Nicole Wiedenmann, Sibylle Stärk, Reinhard Thamm, Peter Kneschaurek, Markus Schwaiger, Michael Molls, Wolfgang A Weber.   

Abstract

PURPOSE: (a) To implement a fully automatic method to integrate (11)C-methionine positron emission tomography (MET-PET) data into stereotactic radiation treatment planning using the commercially available BrainLAB System, by means of CT/MET-PET image fusion. (b) To validate the fully automatic CT/MET-PET image fusion technique with respect to accuracy and robustness. (c) To give a short glance at the clinical consequences for patients with brain tumors. METHODS AND MATERIALS: In 12 patients with brain tumors (9 meningeomas, 3 gliomas), CT, MRI, and MET-PET were performed for stereotactic fractionated radiation treatment planning. The CT and MET-PET investigations were performed using a relocatable mask for head fixation. Fifteen external reference markers (5 on each lateral and 5 on the frontal localizer plate) that could be identified in CT and MET-PET were applied on the stereotactic localizer frame; the marker positions were exactly defined for both investigations. The MRI/CT fusion was done completely automatically. The CT/MET-PET fusion was performed using two different methods: The gold standard was the CT/PET fusion based on the reference markers, and the test method was the automatic, intensity-based CT/PET fusion, independent of the external markers. The markers visible on CT and transmission PET were matched using a point-to-line matching algorithm. To quantify the amount of misregistration, the two fusion methods were compared by calculating the mean value of deviation between corresponding points inside a cubic volume of interest of > or =512 cm(3) defined within the cranial cavity. The gross tumor volume (CT/MRI) outlined on CT and T1-MRI with contrast medium was compared with the gross tumor volume (PET) defined in the reoriented MET-PET data sets. The clinical impact of MET-PET in tumor volume definition for stereotactic radiotherapy will be discussed.
RESULTS: The fully automatic integration of MET-PET into stereotactic radiation treatment planning was successfully realized in all patients investigated. Mean deviation of the intensity-based automatic CT/PET fusion compared with the external marker-based gold standard was 2.4 mm; the standard deviation was 0.5. The algorithm's robustness was evaluated, and the discrepancy of fusion results due to different initial image alignments was determined to be below 1 mm inside the test volume of interest. In patients with meningiomas and gliomas, MET-PET was shown to deliver additional information concerning tumor extension.
CONCLUSION: The precision of the automatic CT/PET image fusion was high. A mean deviation of 2.4 mm is acceptable, considering that it is approximately equal to the pixel size of the PET data sets. MET-PET improves target volume definition for stereotactic fractionated radiotherapy of meningiomas and gliomas.

Entities:  

Mesh:

Substances:

Year:  2003        PMID: 12873691     DOI: 10.1016/s0360-3016(03)00279-7

Source DB:  PubMed          Journal:  Int J Radiat Oncol Biol Phys        ISSN: 0360-3016            Impact factor:   7.038


  31 in total

1.  From anatomical to biological target volumes: the role of PET in radiation treatment planning.

Authors:  D A X Schinagl; J H A M Kaanders; W J G Oyen
Journal:  Cancer Imaging       Date:  2006-10-31       Impact factor: 3.909

2.  [PET/CT in radiotherapy].

Authors:  M Weckesser; S Könemann; M Brinkmann; N Willich; O Schober
Journal:  Radiologe       Date:  2004-11       Impact factor: 0.635

3.  Anatomy of data integration.

Authors:  Olga Brazhnik; John F Jones
Journal:  J Biomed Inform       Date:  2006-09-24       Impact factor: 6.317

4.  Image coregistration: quantitative processing framework for the assessment of brain lesions.

Authors:  Hannu Huhdanpaa; Darryl H Hwang; Gregory G Gasparian; Michael T Booker; Yong Cen; Alexander Lerner; Orest B Boyko; John L Go; Paul E Kim; Anandh Rajamohan; Meng Law; Mark S Shiroishi
Journal:  J Digit Imaging       Date:  2014-06       Impact factor: 4.056

5.  Computed tomography and magnetic resonance fusion imaging in cholesteatoma preoperative assessment.

Authors:  Agustín Campos; Federico Mata; Rosa Reboll; María Luisa Peris; Jorge Basterra
Journal:  Eur Arch Otorhinolaryngol       Date:  2016-12-05       Impact factor: 2.503

6.  Peeking into the Black Box of Coregistration in Clinical fMRI: Which Registration Methods Are Used and How Well Do They Perform?

Authors:  F D Raslau; L Y Lin; A H Andersen; D K Powell; C D Smith; E J Escott
Journal:  AJNR Am J Neuroradiol       Date:  2018-10-25       Impact factor: 3.825

Review 7.  Vision 20/20: perspectives on automated image segmentation for radiotherapy.

Authors:  Gregory Sharp; Karl D Fritscher; Vladimir Pekar; Marta Peroni; Nadya Shusharina; Harini Veeraraghavan; Jinzhong Yang
Journal:  Med Phys       Date:  2014-05       Impact factor: 4.071

Review 8.  11C-L-methionine positron emission tomography in the clinical management of cerebral gliomas.

Authors:  Tarun Singhal; Tanjore K Narayanan; Viney Jain; Jogeshwar Mukherjee; Joseph Mantil
Journal:  Mol Imaging Biol       Date:  2007-10-24       Impact factor: 3.488

9.  Potential impact of (68)Ga-DOTATOC PET/CT on stereotactic radiotherapy planning of meningiomas.

Authors:  Fonyuy Nyuyki; Michail Plotkin; Reinhold Graf; Roger Michel; Ingo Steffen; Timm Denecke; Lilli Geworski; Daniel Fahdt; Winfried Brenner; Reinhard Wurm
Journal:  Eur J Nucl Med Mol Imaging       Date:  2009-09-18       Impact factor: 9.236

10.  Simultaneous integrated boost technique by helical tomotherapy for the treatment of glioblastoma multiforme with 11C-methionine PET: report of three cases.

Authors:  Kazuhiro Miwa; Masayuki Matsuo; Jun Shinoda; Naoki Oka; Takayuki Kato; Ayumi Okumura; Tatsuya Ueda; Kazutoshi Yokoyama; Jitsuhiro Yamada; Hirohito Yano; Shinichi Yoshimura; Toru Iwama
Journal:  J Neurooncol       Date:  2008-01-24       Impact factor: 4.130

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.