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| Home > Publications database > Detectability of anatomical changes with prompt-gamma imaging: First systematic evaluation of clinical application during prostate-cancer proton therapy: Detectability of anatomical changes with PGI. |
| Home > Publications database > Detectability of anatomical changes with prompt-gamma imaging: First systematic evaluation of clinical application during prostate-cancer proton therapy: Detectability of anatomical changes with PGI. |
| Journal Article | DKFZ-2023-00947 |
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2023
Elsevier Science
Amsterdam [u.a.]
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Please use a persistent id in citations: doi:10.1016/j.ijrobp.2023.05.002
Abstract: The development of online-adaptive proton therapy (PT) is an essential requirement to overcome limitations encountered by day-to-day variations of the patient anatomy. Range verification could play an essential role in an online feedback loop for the detection of treatment deviations such as anatomical changes. Here, we present results of the first systematic patient study regarding the detectability of anatomical changes by a prompt-gamma imaging (PGI) slit-camera system.For 15 prostate-cancer patients, PGI measurements were performed during 105 fractions (201 fields) with in-room control CT acquisitions. Field-wise doses on control CT scans were manually classified whether showing relevant or non-relevant anatomical changes. This manual classification of the treatment fields was then used to establish an automatic field-wise ground truth based on spot-wise dosimetric range shifts which were retrieved from integrated depth-dose (IDD) profiles. In order to determine the detection capability of anatomical changes with PGI, spot-wise PGI-based range shifts were initially compared to corresponding dosimetric IDD range shifts. As final endpoint, the agreement of a developed field-wise PGI classification model with the field-wise ground truth was determined. Therefore, the PGI model was optimized and tested for a sub-cohort of 131 and 70 treatment fields, respectively.The correlation between PGI and IDD range shifts was high, ρpearson = 0.67 (p<0.01). Field-wise binary PGI-classification resulted in an area under the curve (AUC) of 0.72 and 0.80 for training and test cohort, respectively. The model detected relevant anatomical changes in the independent test cohort with a sensitivity and specificity of 74% and 79%, respectively.For the first time, evidence of the detection capability of anatomical changes in prostate-cancer PT from clinically acquired PGI data is shown. This emphasizes the benefit of PGI-based range verification and demonstrates its potential for online-adaptive PT.
Keyword(s): automated classification ; inter-fractional changes ; prompt-gamma imaging ; prostate cancer ; proton therapy ; range verification ; treatment verification
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