Accuracy and precision of electrical permittivity mapping at 3T: the impact of three mapping techniques

Abstract

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.

Opening a new window on MR-based Electrical Properties Tomography with deep learning

“…In-vivo measurements are affected by artifacts such as pulsation and motion, which are not present in simulations. MRI measurements of the ̃ field are also corrupted by noise propagation and systematic errors which depend on the adopted ̃ measurement technique 35 . These artifacts and variations in ̃ fields may play a crucial role, resulting in less quality DL-EPT reconstructions from in-vivo MRI measurements compared to DL-EPT reconstructions from simulated data.…”

Demonstration and suppression of respiration‐related artifacts in Bloch–Siegert shift‐based B1+ maps of the human brain

“…The purpose of acquiring maps forms the basis for deciding which method to use. For example, the magnetic resonance electrical properties tomography (MREPT) technique requires high SNR maps to reconstruct dielectric permittivity and conductivity distribution accurately 22–24 . For such high SNR applications, Bloch–Siegert shift (BSS)‐based mapping appears to be an ideal candidate because of its superior SNR performance 24–26 .…”

“…For example, the magnetic resonance electrical properties tomography (MREPT) technique requires high SNR maps to reconstruct dielectric permittivity and conductivity distribution accurately 22–24 . For such high SNR applications, Bloch–Siegert shift (BSS)‐based mapping appears to be an ideal candidate because of its superior SNR performance 24–26 . Indeed, BSS mapping offers flexibility to choose between SNR or acquisition time when adjusting the magnitude of the off‐resonance RF pulse that is applied after excitation to induce phase shifts proportional to 27 With high magnitudes, SNR is increased at the expense of a longer TR and imaging time due to SAR limitations and vice versa.…”

Technical developments for MR-based electrical property mapping

“…Direct ept techniques were employed in recent clinical studies evaluating the potential value of ept-based conductivity in discriminating tumours [127,129] and in hyperthermia treatment planning [131]. Reconstructing good quality permittivity maps with clinical scanners and within acceptable times remains challenging: the necessary high precision requirements [88] are unmet with standard B + 1 mapping techniques [199].…”

“…Our dl-ept method employs a novel 3D patch-based cnn which was trained exclusively on simulated B 1 fields with realistic accuracy and precision. Realistic accuracy and precision in B 1 fields were reproduced by implementing the framework developed in our previous study [199] which combines em and mr simulations. This enables training on realistic measurable datasets for which ground truth eps are available, and stands as a valid alternative to training on in vivo mr measurements for which the true ep values are not available.…”