Radiation treatment planning in brain tumours

2008 ◽  
Vol 47 (05) ◽  
pp. 200-204 ◽  
Author(s):  
H. Alheit ◽  
L. Oehme ◽  
C. Winkler ◽  
F. Füchtner ◽  
A. Hoepping ◽  
...  
Keyword(s):  
Amino Acid ◽  
Treatment Planning ◽  
Radiation Treatment ◽  
Tumour Volume ◽  
Tracer Uptake ◽  
Tumour Tissue ◽  
Subtotal Resection ◽  
High Dose ◽  
Radiation Treatment Planning ◽  
Amino Acid Pet

Summary Aim: Amino acid PET has become an important diagnostic tool for brain tumour imaging. In this data analysis, the potential impact of amino acid PET with 3-O-methyl- 6-[18F]fluoro-L-DOPA ([18F]OMFD) on radiation treatment planning is addressed by the following questions: 1. Was tumour tissue identified with OMFD-PET which was not covered by the conventionally derived planning target volume (PTV)? 2. Would the PTV have been changed incorporating OMFD-PET? Patients, methods: OMFD-PET of 25 patients after subtotal resection of malignant glioma was evaluated. The region of elevated tracer uptake of PET and of contrast enhancing masses on MRI were outlined as separate gross tumour volumes (GTVMRI and GTVOMFD) and reconstructed in the planning CT for comparison with the conventionally drawn GTVconv. A PTVnew based on GTVconv+MRI was calculated. Pairwise differential volumes were calculated to estimate overlap and differential volumes delineation by each image modality and the PTVconv and PTVnew respectively. Results: Differential volume analysis showed > 10 cm3 of GTVOMFD outside GTVconv and GTVMRI in 5/25 patients respectively. From GTVMRI >10 cm3 were found outside GTVOMFD in 8/25 patients. Although all tumour areas indicated by [18F]OMFD were covered by the conventionally derived PTV, based on a GTVOMFD+MRI, the PTVnew would have been enlarged >20% in seven patients. In seven patients the PTVnew would have been reduced. Conclusion: OMFD-PET indicated tumour tissue outside the tumour region identified with MRI, adding valuable information for the delineation of the GTV in radiation treatment planning. OMFD-PET contains the potential to tailor the high dose radiation to the appropriate tumour volume, especially if dose escalation is desired.

scholarly journals The Emerging Role of Amino Acid PET in Neuro-Oncology

2018 ◽  
Vol 5 (4) ◽  
pp. 104 ◽  
Author(s):  
Amer Najjar ◽  
Jason Johnson ◽  
Dawid Schellingerhout
Keyword(s):  
Amino Acid ◽  
Treatment Planning ◽  
Radiation Treatment ◽  
Critical Role ◽  
Therapy Response ◽  
Response Assessment ◽  
Early Therapy ◽  
Contrast Enhanced ◽  
Amino Acid Pet ◽  
Cns Malignancies

Imaging plays a critical role in the management of the highly complex and widely diverse central nervous system (CNS) malignancies in providing an accurate diagnosis, treatment planning, response assessment, prognosis, and surveillance. Contrast-enhanced magnetic resonance imaging (MRI) is the primary modality for CNS disease management due to its high contrast resolution, reasonable spatial resolution, and relatively low cost and risk. However, defining tumor response to radiation treatment and chemotherapy by contrast-enhanced MRI is often difficult due to various factors that can influence contrast agent distribution and perfusion, such as edema, necrosis, vascular alterations, and inflammation, leading to pseudoprogression and pseudoresponse assessments. Amino acid positron emission tomography (PET) is emerging as the method of resolving such equivocal lesion interpretations. Amino acid radiotracers can more specifically differentiate true tumor boundaries from equivocal lesions based on their specific and active uptake by the highly metabolic cellular component of CNS tumors. These therapy-induced metabolic changes detected by amino acid PET facilitate early treatment response assessments. Integrating amino acid PET in the management of CNS malignancies to complement MRI will significantly improve early therapy response assessment, treatment planning, and clinical trial design.

Stereotactic radiation treatment planning and follow-up studies involving fused multimodality imaging

2004 ◽  
Vol 101 (Supplement3) ◽  
pp. 326-333 ◽  
Author(s):  
Klaus D. Hamm ◽  
Gunnar Surber ◽  
Michael Schmücking ◽  
Reinhard E. Wurm ◽  
Rene Aschenbach ◽  
...  
Keyword(s):  
Image Fusion ◽  
Treatment Planning ◽  
Radiation Treatment ◽  
Data Sets ◽  
Slice Thickness ◽  
Radiation Treatment Planning ◽  
Content Type ◽  
Follow Up Studies ◽  
Fine Print

Object. Innovative new software solutions may enable image fusion to produce the desired data superposition for precise target definition and follow-up studies in radiosurgery/stereotactic radiotherapy in patients with intracranial lesions. The aim is to integrate the anatomical and functional information completely into the radiation treatment planning and to achieve an exact comparison for follow-up examinations. Special conditions and advantages of BrainLAB's fully automatic image fusion system are evaluated and described for this purpose. Methods. In 458 patients, the radiation treatment planning and some follow-up studies were performed using an automatic image fusion technique involving the use of different imaging modalities. Each fusion was visually checked and corrected as necessary. The computerized tomography (CT) scans for radiation treatment planning (slice thickness 1.25 mm), as well as stereotactic angiography for arteriovenous malformations, were acquired using head fixation with stereotactic arc or, in the case of stereotactic radiotherapy, with a relocatable stereotactic mask. Different magnetic resonance (MR) imaging sequences (T1, T2, and fluid-attenuated inversion-recovery images) and positron emission tomography (PET) scans were obtained without head fixation. Fusion results and the effects on radiation treatment planning and follow-up studies were analyzed. The precision level of the results of the automatic fusion depended primarily on the image quality, especially the slice thickness and the field homogeneity when using MR images, as well as on patient movement during data acquisition. Fully automated image fusion of different MR, CT, and PET studies was performed for each patient. Only in a few cases was it necessary to correct the fusion manually after visual evaluation. These corrections were minor and did not materially affect treatment planning. High-quality fusion of thin slices of a region of interest with a complete head data set could be performed easily. The target volume for radiation treatment planning could be accurately delineated using multimodal information provided by CT, MR, angiography, and PET studies. The fusion of follow-up image data sets yielded results that could be successfully compared and quantitatively evaluated. Conclusions. Depending on the quality of the originally acquired image, automated image fusion can be a very valuable tool, allowing for fast (∼ 1–2 minute) and precise fusion of all relevant data sets. Fused multimodality imaging improves the target volume definition for radiation treatment planning. High-quality follow-up image data sets should be acquired for image fusion to provide exactly comparable slices and volumetric results that will contribute to quality contol.

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