Systematic analysis on the achievable accuracy of PT-PET through automated evaluation techniques

Helmbrecht, S.; Kueß, Peter; Birkfellner, Wolfgang; Enghardt, W.; Stützer, Kristin; Georg, Dietmar; Fiedler, F.

doi:10.1016/j.zemedi.2014.08.004

Cited by 7 publications

(6 citation statements)

References 31 publications

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“…In general, to handle problems occurring from single spots, one has to think about a dedicated post-processing of the detected range deviations. This requires the use of a threedimensional range deviation matrix, as has been proposed, for example, for PT-PET data (Helmbrecht et al 2014). By simple visual inspection of all the range deviation information gathered by this matrix, one can obtain a first clue on possible treatment deviations.…”

Section: Discussionmentioning

confidence: 99%

Measurement of prompt gamma profiles in inhomogeneous targets with a knife-edge slit camera during proton irradiation

Priegnitz¹,

Helmbrecht²,

Janssens³

et al. 2015

Phys. Med. Biol.

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Proton and ion beam therapies become increasingly relevant in radiation therapy. To fully exploit the potential of this irradiation technique and to achieve maximum target volume conformality, the verification of particle ranges is highly desirable. Many research activities focus on the measurement of the spatial distributions of prompt gamma rays emitted during irradiation. A passively collimating knife-edge slit camera is a promising option to perform such measurements. In former publications, the feasibility of accurate detection of proton range shifts in homogeneous targets could be shown with such a camera. We present slit camera measurements of prompt gamma depth profiles in inhomogeneous targets. From real treatment plans and their underlying CTs, representative beam paths are selected and assembled as one-dimensional inhomogeneous targets built from tissue equivalent materials. These phantoms have been irradiated with monoenergetic proton pencil beams. The accuracy of range deviation estimation as well as the detectability of range shifts is investigated in different scenarios. In most cases, range deviations can be detected within less than 2 mm. In close vicinity to low-density regions, range detection is challenging. In particular, a minimum beam penetration depth of 7 mm beyond a cavity is required for reliable detection of a cavity filling with the present setup. Dedicated data post-processing methods may be capable of overcoming this limitation.

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Section: Discussionmentioning

confidence: 99%

Measurement of prompt gamma profiles in inhomogeneous targets with a knife-edge slit camera during proton irradiation

Priegnitz¹,

Helmbrecht²,

Janssens³

et al. 2015

Phys. Med. Biol.

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“…Patient positioning variations, gain or loss of weight during treatment, with resultant changes in subcutaneous fat depths, tumour shrinkage, can all critically affect particle range, dose and LET distribution, with implications for tumour control and toxicities. Imaging of the BP position is improving, for example with proton activated PET signal detection to an accuracy of 2 mm [ 19 ].…”

Section: Introductionmentioning

confidence: 99%

“…Recent work by Schuemann et al [ 18 ] considers the accuracy of obtaining the physician defined target volume margins and provides recommended tolerances for different anatomical sites. A recent review of Proton radiography and PET, or prompt gamma ray imaging, using small test doses of radiation or actual treatments respectively may also improve overall quality assurance [ 19 , 20 , 21 , 22 ]. The inaccuracies associated with algorithms in proton planning, which can vary with anatomical site, can be improved by application of Monte Carlo planning methods [ 17 , 18 ].…”

Section: Introductionmentioning

confidence: 99%

Towards Achieving the Full Clinical Potential of Proton Therapy by Inclusion of LET and RBE Models

Jones

2015

Cancers

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Despite increasing use of proton therapy (PBT), several systematic literature reviews show limited gains in clinical outcomes, with publications mostly devoted to recent technical developments. The lack of randomised control studies has also hampered progress in the acceptance of PBT by many oncologists and policy makers. There remain two important uncertainties associated with PBT, namely: (1) accuracy and reproducibility of Bragg peak position (BPP); and (2) imprecise knowledge of the relative biological effect (RBE) for different tissues and tumours, and at different doses. Incorrect BPP will change dose, linear energy transfer (LET) and RBE, with risks of reduced tumour control and enhanced toxicity. These interrelationships are discussed qualitatively with respect to the ICRU target volume definitions. The internationally accepted proton RBE of 1.1 was based on assays and dose ranges unlikely to reveal the complete range of RBE in the human body. RBE values are not known for human (or animal) brain, spine, kidney, liver, intestine, etc. A simple efficiency model for estimating proton RBE values is described, based on data of Belli et al. and other authors, which allows linear increases in α and β with LET, with a gradient estimated using a saturation model from the low LET α and β radiosensitivity parameter input values, and decreasing RBE with increasing dose. To improve outcomes, 3-D dose-LET-RBE and bio-effectiveness maps are required. Validation experiments are indicated in relevant tissues. Randomised clinical studies that test the invariant 1.1 RBE allocation against higher values in late reacting tissues, and lower tumour RBE values in the case of radiosensitive tumours, are also indicated.

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“…On the other hand, it is very difficult to interpret the information: It is not feasible to estimate the location and cause of the change in the PET signal. It must be noted that simply subtracting the expected PET images from an observed PET image is not appealing, as shown already in various works 48,49 . Since the significant differences in PET signal are often located in regions where the activity is only moderate, statistical fluctuations cause the highlighted regions to appear all over the activated zone, mostly uncorrelated with the region where morphological changes occurred.…”

Section: Resultsmentioning

confidence: 96%

“…It must be noted that simply subtracting the expected PET images from an observed PET image is not appealing, as shown already in various works. 48,49 Since the significant differences in PET signal are often located in regions where the activity is only moderate, statistical fluctuations cause the highlighted regions to appear all over the activated zone, mostly In Figure 7 we show three different slices of the pvalue maps overlaid on the planning CT, resulting from the statistical analysis of the control sample PET obs,0 (Figure 7(a), (e), and (i)), and three intermediate PET images, PET obs,j for j =2, 4, and 6, corresponding to emptied volumes of 3.8 mL (Figure 7(b), (f), and (j)), 7.3 mL (Figure 7(c), (g), (k)), and 13.1 mL (Figure 7(d), (h), and (l)), respectively. First of all, we observe that the region of morphological changes was well identified through the blue zones (lack of activity), and corresponded well to the regions that were actually emptied in the CT scan.The latter can be seen from the small insets in the left bottom of the slices, showing the corresponding region in the artificially modified CT scan.…”

Section: Identification Of Regions With Morphological Changes: Qualit...mentioning

confidence: 99%

Localization of anatomical changes in patients during proton therapy with in‐beam PET monitoring: A voxel‐based morphometry approach exploiting Monte Carlo simulations

et al. 2021

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In-beam positron emission tomography (PET) is one of the modalities that can be used for in vivo noninvasive treatment monitoring in proton therapy. Although PET monitoring has been frequently applied for this purpose, there is still no straightforward method to translate the information obtained from the PET images into easy-to-interpret information for clinical personnel. The purpose of this work is to propose a statistical method for analyzing in-beam PET monitoring images that can be used to locate, quantify, and visualize regions with possible morphological changes occurring over the course of treatment. Methods: We selected a patient treated for squamous cell carcinoma (SCC) with proton therapy, to perform multiple Monte Carlo (MC) simulations of the expected PET signal at the start of treatment, and to study how the PET signal may change along the treatment course due to morphological changes. We performed voxel-wise two-tailed statistical tests of the simulated PET images, resembling the voxel-based morphometry (VBM) method commonly used in neuroimaging data analysis, to locate regions with significant morphological changes and to quantify the change. Results: The VBM resembling method has been successfully applied to the simulated in-beam PET images, despite the fact that such images suffer from image artifacts and limited statistics. Three dimensional probability maps were obtained, that allowed to identify interfractional morphological changes and to visualize them superimposed on the computed tomography (CT) scan. In particular, the characteristic color patterns resulting from the two-tailed statistical tests lend themselves to trigger alarms in case of morphological changes along the course of treatment. Conclusions:The statistical method presented in this work is a promising method to apply to PET monitoring data to reveal interfractional morphological changes in patients, occurring over the course of treatment. Based on simulated in-beam PET treatment monitoring images, we showed that with our method it was possible to correctly identify the regions that changed. Moreover we could quantify the changes, and visualize them superimposed on the CT scan. The proposed method can possibly help clinical personnel in the replanning procedure in adaptive proton therapy treatments. K E Y W O R D Sin-beam PET monitoring, proton therapy, voxel-based morphometry

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Systematic analysis on the achievable accuracy of PT-PET through automated evaluation techniques

Cited by 7 publications

References 31 publications

Measurement of prompt gamma profiles in inhomogeneous targets with a knife-edge slit camera during proton irradiation

Measurement of prompt gamma profiles in inhomogeneous targets with a knife-edge slit camera during proton irradiation

Towards Achieving the Full Clinical Potential of Proton Therapy by Inclusion of LET and RBE Models

Localization of anatomical changes in patients during proton therapy with in‐beam PET monitoring: A voxel‐based morphometry approach exploiting Monte Carlo simulations

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