Purpose To investigate the sequence‐specific impact of amplitude mapping on the accuracy and precision of permittivity reconstruction at 3T in the pelvic region. Methods maps obtained with actual flip angle imaging (AFI), Bloch–Siegert (BS), and dual refocusing echo acquisition mode (DREAM) sequences, set to a clinically feasible scan time of 5 minutes, were compared in terms of accuracy and precision with electromagnetic and Bloch simulations and MR measurements. Permittivity maps were reconstructed based on these maps with Helmholtz‐based electrical properties tomography. Accuracy and precision in permittivity were assessed. A 2‐compartment phantom with properties and size similar to the human pelvis was used for both simulations and measurements. Measurements were also performed on a female volunteer’s pelvis. Results Accuracy was evaluated with noiseless simulations on the phantom. The maximum bias relative to the true distribution was 1% for AFI and BS and 6% to 15% for DREAM. This caused an average permittivity bias relative to the true permittivity of 7% to 20% for AFI and BS and 12% to 35% for DREAM. Precision was assessed in MR experiments. The lowest standard deviation in permittivity, found in the phantom for BS, measured 22.4 relative units and corresponded to a standard deviation in of 0.2% of the average value. As regards precision, in vivo and phantom measurements were comparable. Conclusions Our simulation framework quantitatively predicts the different impact of mapping techniques on permittivity reconstruction and shows high sensitivity of permittivity reconstructions to sequence‐specific bias and noise perturbation in the map. These findings are supported by the experimental results.
This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. Purpose:To demonstrate 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 3 tesla. Conductivity maps were reconstructed with Helmholtz-based electrical properties tomography. In measurements, PLANET was also compared to a reference technique for transceive phase mapping, i.e., spin echo. Results: Accuracy and precision of ϕ ± estimated with PLANET depended on the chosen flip angle and TR. PLANET-based ϕ ± was less sensitive to perturbations induced by offresonance effects and partial volume (e.g., white matter + myelin) than bSSFP-based ϕ ± .For flip angle = 25° and TR = 4.6 ms, PLANET showed an accuracy comparable to that of reference spin echo but a higher precision than bSSFP and spin echo (factor of 2 and 3, respectively). The acquisition time for PLANET was ~5 min; 2 min faster than spin echo 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 spin echo-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. K E Y W O R D Saccuracy, conductivity mapping, ellipse fitting, phase-cycled bSSFP, precision, transceive phase mapping | 591 GAVAZZI et Al.
Hyperthermia treatment planning (HTP) is valuable to optimize tumor heating during thermal therapy delivery. Yet, clinical hyperthermia treatment plans lack quantitative accuracy due to uncertainties in tissue properties and modeling, and report tumor absorbed power and temperature distributions which cannot be linked directly to treatment outcome. Over the last decade, considerable progress has been made to address these inaccuracies and therefore improve the reliability of hyperthermia treatment planning. Patient-specific electrical tissue conductivity derived from MR measurements has been introduced to accurately model the power deposition in the patient. Thermodynamic fluid modeling has been developed to account for the convective heat transport in fluids such as urine in the bladder. Moreover, discrete vasculature trees have been included in thermal models to account for the impact of thermally significant large blood vessels. Computationally efficient optimization strategies based on SAR and temperature distributions have been established to calculate the phase-amplitude settings that provide the best tumor thermal dose while avoiding hot spots in normal tissue. Finally, biological modeling has been developed to quantify the hyperthermic radiosensitization effect in terms of equivalent radiation dose of the combined radiotherapy and hyperthermia treatment. In this paper, we review the present status of these developments and illustrate the most relevant advanced elements within a single treatment planning example of a cervical cancer patient. The resulting advanced HTP workflow paves the way for a clinically feasible and more reliable patient-specific hyperthermia treatment planning.
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.
The aim of this work was to investigate whether there are differences in electromagnetic properties between normal and variously pathological human thyroid tissues. Dielectric properties of normal, diseased and malignant human thyroid tissues have been investigated at microwave frequencies from 200 MHz to 10 GHz; diseased tissues involved goiters, thyroiditis and adenomatous nodules. Measurements were carried out on freshly excised thyroid samples from 14 surgery patients within less than one hour from excision, using the open-ended coaxial probe technique. Complex permittivity values of each measured specimen were fitted to a 2-pole Cole-Cole model. Thyroid samples were classified into five categories according to their final histological examination: normal, struma (nodular goiter), thyroiditis, adenoma and cancer. Data analysis showed that the dielectric constant of a normal thyroid is on average 10% lower than relative permittivity of cancer and less than 8% lower than that of goiter over the entire frequency band. Conductivity for normal samples is from 21% to 8% lower than that for malignant lesions and from 14% to 7% lower than conductivity of goiter (struma) in the band ranging from 0.2 to 2.45 GHz. Above this frequency range no significant difference is found in terms of electrical conductivity. No significant contrast has, however, been found between dielectric properties of cancer and other benign pathologies affecting the gland. These findings are relevant for microwave diagnosis endeavours and for all biomedical applications involving the electrical properties of human tissues.
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