Clinical validation of a novel thermophysical bladder model designed to improve the accuracy of hyperthermia treatment planning in the pelvic region

Schooneveldt, G.; Kok, H. Petra; Bakker, A.; Geijsen, Elisabeth D.; Rasch, Coen R. N.; Rosette, Jean J.M.C.H. de la; Hulshof, Maarten C.C.M.; Reijke, Theo M. de; Crezee, J.

doi:10.1080/02656736.2018.1506164

Cited by 13 publications

(24 citation statements)

References 55 publications

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“…In the bladder, for example, more realistic and homogeneous temperatures were predicted by the complete fluid thermodynamic model. Compared to the default model, in which the bladder was modelled as a solid perfused (muscle) tissue, mean deviations between temperature predictions and measurements during treatment reduced from 4 • C to 0.6 • C [200].…”

Section: Introductionmentioning

confidence: 90%

“…Both empty and full bladder cases were included in the dataset. Empty bladders (present in 70/210 dielectric models) were given muscle eps, as commonly adopted in hyperthermia treatment planning studies [131,200]. Full bladders were assigned bladder content eps [102].…”

Section: Construction Of Dielectric Modelsmentioning

confidence: 99%

“…A dedicated modelling approach was adopted for the bladder. Recent studies have shown that modelling fluid convection has a large impact on the final temperature distribution, yielding more accurate hyperthermia treatment planning [200,249,250,272]. However, modelling convective heat transfer is computationally time-consuming at this moment, which makes it impractical for routine clinical use.…”

Section: Electrical Properties Of Tissuesmentioning

confidence: 99%

“…Subsequently, automatic optimization techniques [225,[230][231][232][233] predict the phase-amplitude settings for the individual antennas to realize optimal heat deposition in the tumour while preventing overheating of normal tissue. Notwithstanding various studies reported good qualitative agreement between htp simulations and clinical observations during treatment [234][235][236][237], present hyperthermia treatment plans lack quantitative accuracy because of uncertainties in dielectric [174,185,238] and thermal [233] parameters and because of approximate heat transport modelling of blood flow and heat convection in fluids [200,239,240]. Furthermore, these hyperthermia treatment plans report only power and temperature distributions, but do not allow easy interpretation of the increased radiosensitization and therefore of the added clinical benefit to the primary treatment.…”

Section: Introductionmentioning

confidence: 99%

“…urine and cerebrospinal fluid, are present in the heated region, convection will influence the temperature distribution. Schooneveldt et al developed convective fluid models of the bladder [200,249] and cerebrospinal fluid [250] to accurately represent the fluid dynamics during hyperthermia. In the bladder, for example, more realistic and homogeneous temperatures were predicted by the complete fluid thermodynamic model.…”

Section: Introductionmentioning

confidence: 99%

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Technical developments for MR-based electrical property mapping

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Purpose: To demonstrate the feasibility of transceive phase mapping with the planet method and its application for conductivity reconstruction in the brain. Methods: Accuracy and precision of transceive phase (φ ±) estimation with planet, an ellipse fitting approach to phase-cycled balanced steady state free precession (bssfp) data, were assessed with simulations and measurements and compared to standard bssfp. Measurements were conducted on a homogeneous phantom and in the brain of healthy volunteers at 3T. Conductivity maps were reconstructed with Helmholtz-based electrical properties tomography (ept). In measurements, planet was also compared to a reference technique for transceive phase mapping, i.e. spin echo (se). Results: Accuracy and precision of φ ± estimated with planet depended on the chosen flip angle (FA) and TR. planet-based φ ± was less sensitive to perturbations induced by off-resonance effects and partial volume (e.g. white matter + myelin) than bssfp-based φ ±. For FA = 25 • and TR = 4.6 ms, planet showed an accuracy comparable to that of reference se but a higher precision than bssfp and se (factor of 2 and 3, respectively). The acquisition time for planet was 5 min; 2 min faster than se and 8 times slower than bssfp. However, planet simultaneously reconstructed T 1 , T 2 , B 0 maps besides mapping φ ±. In the phantom, planet-based conductivity matched the true value and had the smallest spread of the three methods. In vivo, planet-based conductivity was similar to se-based conductivity. Conclusion: Provided that appropriate sequence parameters are used, planet delivers accurate and precise φ ± maps, which can be used to reconstruct brain tissue conductivity while simultaneously recovering T 1 , T 2 and B 0 maps.

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Section: Introductionmentioning

confidence: 90%

Section: Construction Of Dielectric Modelsmentioning

confidence: 99%

Section: Electrical Properties Of Tissuesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Technical developments for MR-based electrical property mapping

Gavazzi¹

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Deep learning‐based reconstruction of in vivo pelvis conductivity with a 3D patch‐based convolutional neural network trained on simulated MR data

Gavazzi

Berg

Savenije

et al. 2020

Magnetic Resonance in Med

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Purpose To demonstrate that mapping pelvis conductivity at 3T with deep learning (DL) is feasible. Methods 210 dielectric pelvic models were generated based on CT scans of 42 cervical cancer patients. For all dielectric models, electromagnetic and MR simulations with realistic accuracy and precision were performed to obtain and transceive phase ( ϕ ± ). Simulated and ϕ ± served as input to a 3D patch‐based convolutional neural network, which was trained in a supervised fashion to retrieve the conductivity. The same network architecture was retrained using only ϕ ± in input. Both network configurations were tested on simulated MR data and their conductivity reconstruction accuracy and precision were assessed. Furthermore, both network configurations were used to reconstruct conductivity maps from a healthy volunteer and two cervical cancer patients. DL‐based conductivity was compared in vivo and in silico to Helmholtz‐based (H‐EPT) conductivity. Results Conductivity maps obtained from both network configurations were comparable. Accuracy was assessed by mean error (ME) with respect to ground truth conductivity. On average, ME < 0.1 Sm −1 for all tissues. Maximum MEs were 0.2 Sm −1 for muscle and tumour, and 0.4 Sm −1 for bladder. Precision was indicated with the difference between 90 th and 10 th conductivity percentiles, and was below 0.1 Sm −1 for fat, bone and muscle, 0.2 Sm −1 for tumour and 0.3 Sm −1 for bladder. In vivo, DL‐based conductivity had median values in agreement with H‐EPT values, but a higher precision. Conclusion Anatomically detailed, noise‐robust 3D conductivity maps with good sensitivity to tissue conductivity variations were reconstructed in the pelvis with DL.

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