Deep learning based correction of RF field induced inhomogeneities for T2w prostate imaging at 7 T.

At ultrahigh field strengths images of the body are hampered by B1 -field inhomogeneities. These present themselves as inhomogeneous signal intensity and contrast, which is regarded as a "bias field" to the ideal image. Current bias field correction methods, such as the N4 algorithm, assume a low frequency bias field, which is not sufficiently valid for T2w images at 7 T. In this work we propose a deep learning based bias field correction method to address this issue for T2w prostate images at 7 T. By combining simulated B1 -field distributions of a multi-transmit setup at 7 T with T2w prostate images at 1.5 T, we generated artificial 7 T images for which the homogeneous counterpart was available. Using these paired data, we trained a neural network to correct the bias field. We predicted either a homogeneous image (t-Image neural network) or the bias field (t-Biasf neural network). In addition, we experimented with the single-channel images of the receive array and the corresponding sum of magnitudes of this array as the input image. Testing was carried out on four datasets: the test split of the synthetic training dataset, volunteer and patient images at 7 T, and patient images at 3 T. For the test split, the performance was evaluated using the structural similarity index measure, Wasserstein distance, and root mean squared error. For all other test data, the features Homogeneity and Energy derived from the gray level co-occurrence matrix (GLCM) were used to quantify the improvement. For each test dataset, the proposed method was compared with the current gold standard: the N4 algorithm. Additionally, a questionnaire was filled out by two clinical experts to assess the homogeneity and contrast preservation of the 7 T datasets. All four proposed neural networks were able to substantially reduce the B1 -field induced inhomogeneities in T2w 7 T prostate images. By visual inspection, the images clearly look more homogeneous, which is confirmed by the increase in Homogeneity and Energy in the GLCM, and the questionnaire scores from two clinical experts. Occasionally, changes in contrast within the prostate were observed, although much less for the t-Biasf network than for the t-Image network. Further, results on the 3 T dataset demonstrate that the proposed learning based approach is on par with the N4 algorithm. The results demonstrate that the trained networks were capable of reducing the B1 -field induced inhomogeneities for prostate imaging at 7 T. The quantitative evaluation showed that all proposed learning based correction techniques outperformed the N4 algorithm. Of the investigated methods, the single-channel t-Biasf neural network proves most reliable for bias field correction.

Transceive phase mapping using the PLANET method and its application for conductivity mapping in the brain.

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 off-resonance 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 T1 , T2 , B0 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 T1 , T2 , and B0 maps.

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

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 B1+ and transceive phase (ϕ± ). Simulated B1+ 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 90th and 10th 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.

Untangling the diffusion signal using the phasor transform.

Separating the decay signal from diffusion-weighted scans into two or more components can be challenging. The phasor technique is well established in the field of optical microscopy for visualization and separation of fluorescent dyes with different lifetimes. The use of the phasor technique for separation of diffusion-weighted decay signals was recently proposed. In this study, we investigate the added value of this technique for fitting decay models and visualization of decay rates. Phasor visualization was performed in five glioblastoma patients. Using simulations, the influence of incorrect diffusivity values and of the number of b-values on fitting a three-component model with fixed diffusivities (dubbed "unmixing") was investigated for both a phasor-based fit and a linear least squares (LLS) fit. Phasor-based intravoxel incoherent motion (IVIM) fitting was compared with nonlinear least squares (NLLS) and segmented fitting (SF) methods in terms of accuracy and precision. The distributions of the parameter estimates of simulated data were compared with those obtained in a healthy volunteer. In the phasor visualizations of two glioblastoma patients, a cluster of points was observed that was not seen in healthy volunteers. The identified cluster roughly corresponded to the enhanced edge region of the tumor of two glioblastoma patients visible on fluid-attenuated inversion recovery (FLAIR) images. For fitting decay models the usefulness of the phasor transform is less pronounced, but the additional knowledge gained from the geometrical configuration of phasor space can aid fitting routines. This has led to slightly improved fitting results for the IVIM model: phasor-based fitting yielded parameter maps with higher precision than the NLLS and SF methods for parameters f and D (interquartile range [IQR] for f: NLLS 27, SF 12, phasor 5.7%; IQR for D: NLLS 0.28, SF 0.18, phasor 0.10 µm2 /s). For unmixing, LLS fitting slightly but consistently outperformed phasor-based fitting in all of the tested scenarios.

Optimal timing for prediction of pathologic complete response to neoadjuvant chemoradiotherapy with diffusion-weighted MRI in patients with esophageal cancer.

OBJECTIVE: This study was conducted in order to determine the optimal timing of diffusion-weighted magnetic resonance imaging (DW-MRI) for prediction of pathologic complete response (pCR) to neoadjuvant chemoradiotherapy (nCRT) for esophageal cancer. METHODS: Patients with esophageal adenocarcinoma or squamous cell carcinoma who planned to undergo nCRT followed by surgery were enrolled in this prospective study. Patients underwent six DW-MRI scans: one baseline scan before the start of nCRT and weekly scans during 5 weeks of nCRT. Relative changes in mean apparent diffusion coefficient (ADC) values between the baseline scans and the scans during nCRT (ΔADC(%)) were compared between pathologic complete responders (pCR) and non-pCR (tumor regression grades 2-5). The discriminative ability of ΔADC(%) was determined based on the c-statistic. RESULTS: A total of 24 patients with 142 DW-MRI scans were included. pCR was observed in seven patients (29%). ΔADC(%) from baseline to week 2 was significantly higher in patients with pCR versus non-pCR (median [IQR], 36% [30%, 41%] for pCR versus 16% [14%, 29%] for non-pCR, p = 0.004). The ΔADC(%) of the second week in combination with histology resulted in the highest c-statistic for the prediction of pCR versus non-pCR (0.87). The c-statistic of this model increased to 0.97 after additional exclusion of patients with a small tumor volume (< 7 mL, n = 3) and tumor histology of the resection specimen other than adenocarcinoma or squamous cell carcinoma (n = 1). CONCLUSION: The relative change in tumor ADC (ΔADC(%)) during the first 2 weeks of nCRT is the most predictive for pathologic complete response to nCRT in esophageal cancer patients. KEY POINTS: • DW-MRI during the second week of neoadjuvant chemoradiotherapy is most predictive for pathologic complete response in esophageal cancer. • A model including ΔADCweek 2was able to discriminate between pathologic complete responders and non-pathologic complete responders in 87%. • Improvements in future MRI studies for esophageal cancer may be obtained by incorporating motion management techniques.

Tumor volume regression during neoadjuvant chemoradiotherapy for esophageal cancer: a prospective study with weekly MRI.

Background: Neoadjuvant chemoradiotherapy (nCRT) for esophageal cancer causes tumor regression during treatment. Tumor regression can induce changes in the thoracic anatomy, with smaller target volumes and displacement of organs at risk (OARs) surrounding the tumor as a result. Adaptation of the radiotherapy treatment plan according to volumetric changes during treatment might reduce radiation dose to the OARs, while maintaining adequate target coverage. Data on the magnitude of the volumetric changes and its impact on the thoracic anatomy is scarce. The aim of this study was to assess the volumetric changes in the primary tumor during nCRT for esophageal cancer based on weekly MRI scans.Material and methods: In this prospective study, patients with adeno- or squamous cell carcinoma of the esophagus treated with neoajduvant chemoradiotherapy according to the CROSS regimen (carboplatin + paclitaxel + 23 × 1.8 Gy) were included. Of each patient, six sequential MRI scans were acquired: one prior to nCRT, and five in each subsequent week during nCRT. Tumor volumes were delineated on the transversal T2 weighted images by two radiation oncologists. Volumetric changes were analyzed using linear mixed effects models.Results: A total of 170 MRI scans from 29 individual patients were included. The mean (± standard deviation (SD)) tumor volume at baseline was 45 cm3 (± 23). Tumor volume regression started after the first week of nCRT with a significant decrease in tumor volumes every subsequent week. A decrease to 42 cm3 (91% of initial volume), 38 cm3 (81%), 35 cm3 (77%), and 32 cm3 (72%) was observed in the second, third, fourth and fifth week of nCRT, respectively.Conclusion: Based on weekly MRI scanning during nCRT for esophageal cancer, a considerable decrease in tumor volume was observed during treatment. Volume regression and consequential anatomical changes suggest the possible benefit of adaptive radiotherapy.

Advanced patient-specific hyperthermia treatment planning.

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.

Accuracy and precision of electrical permittivity mapping at 3T: the impact of three B1+ mapping techniques.

PURPOSE: To investigate the sequence-specific impact of B1+ amplitude mapping on the accuracy and precision of permittivity reconstruction at 3T in the pelvic region. METHODS: B1+ 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 B1+ 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 B1+ bias relative to the true B1+ 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 B1+ of 0.2% of the B1+ average value. As regards B1+ precision, in vivo and phantom measurements were comparable. CONCLUSIONS: Our simulation framework quantitatively predicts the different impact of B1+ mapping techniques on permittivity reconstruction and shows high sensitivity of permittivity reconstructions to sequence-specific bias and noise perturbation in the B1+ map. These findings are supported by the experimental results.

DW-MRI and DCE-MRI are of complementary value in predicting pathologic response to neoadjuvant chemoradiotherapy for esophageal cancer.

PURPOSE: To explore the potential benefit and complementary value of a multiparametric approach using diffusion-weighted (DW-) and dynamic contrast-enhanced (DCE-) magnetic resonance imaging (MRI) for prediction of response to neoadjuvant chemoradiotherapy (nCRT) in esophageal cancer. MATERIAL AND METHODS: Forty-five patients underwent both DW-MRI and DCE-MRI prior to nCRT (pre), during nCRT (week 2-3) (per) and after completion of nCRT, but prior to esophagectomy (post). Subsequently, histopathologic tumor regression grade (TRG) was assessed. Tumor apparent diffusion coefficient (ADC) and area-under-the-concentration time curve (AUC) were calculated for DW-MRI and DCE-MRI, respectively. The ability of these parameters to predict pathologic complete response (pCR, TRG1) or good response (GR, TRG ≤ 2) to nCRT was assessed. Furthermore the complementary value of DW-MRI and DCE-MRI was investigated. RESULTS: GR was found in 22 (49%) patients, of which 10 (22%) patients showed pCR. For DW-MRI, the 75th percentile (P75) ΔADCpost-pre was most predictive for GR (c-index = 0.75). For DCE-MRI, P90 ΔAUCper-pre was most predictive for pCR (c-index = 0.79). Multivariable logistic regression analyses showed complementary value when combining DW-MRI and DCE-MRI for pCR prediction (c-index = 0.89). CONCLUSIONS: Both DW-MRI and DCE-MRI are promising in predicting response to nCRT in esophageal cancer. Combining both modalities provides complementary information, resulting in a higher predictive value.

A geometrical shift results in erroneous appearance of low frequency tissue eddy current induced phase maps.

PURPOSE: Knowledge on low frequency (LF) tissue conductivity is relevant for various biomedical purposes. To obtain this information, LF phase maps arising from time-varying imaging gradients have been demonstrated to create a LF conductivity contrast. Essential in this methodology is the subtraction of phase images acquired with opposite gradient polarities to separate LF and RF phase effects. Here we demonstrate how sensitive these subtractions are with respect to geometrical distortions. THEORY AND METHODS: The effect of geometrical distortions on LF phase maps is mathematically defined. After quantifying typical geometrical distortions, their effects on LF phase maps are evaluated using conductive phantoms. For validation, electromagnetic simulations of LF phase maps were performed. RESULTS: Even sub-voxel distortions of 10% of the voxel size, measured for a typical LF MR sequence, cause leakage of RF phase into LF phase of several milli-radians, leading to a misleading pattern of LF phase maps. This leakage is mathematically confirmed, while simulations indicate that the expected LF phase should be in order of micro-radians. CONCLUSION: The conductivity scaling of LF phase maps is attributable to the RF phase leakage, thus dependent on the RF conductivity. In fact, simulations show that the LF phase is not measurable. Magn Reson Med 76:905-912, 2016. © 2015 Wiley Periodicals, Inc.

Local specific absorption rate in brain tumors at 7 tesla.

PURPOSE: MR safety at 7 Tesla relies on accurate numerical simulations of transmit electromagnetic fields to fully assess local specific absorption rate (SAR) safety. Numerical simulations for SAR safety are currently performed using models of healthy patients. These simulations might not be useful for estimating SAR in patients who have large lesions with potentially abnormal dielectric properties, e.g., brain tumors. THEORY AND METHODS: In this study, brain tumor patient models are constructed based on scans of four patients with high grade brain tumors. Dielectric properties for the modeled tumors are assigned based on electrical properties tomography data for the same patients. Simulations were performed to determine SAR. RESULTS: Local SAR increases in the tumors by as much as 30%. However, the location of the maximum 10-gram averaged SAR typically occurs outside of the tumor, and thus does not increase. In the worst case, if the tumor model is moved to the location of maximum electric field intensity, then we do observe an increase in the estimated peak 10-gram SAR directly related to the tumor. CONCLUSION: Peak local SAR estimation made on the results of a healthy patient model simulation may underestimate the true peak local SAR in a brain tumor patient.

Hyperthermia treatment planning for cervical cancer patients based on electrical conductivity tissue properties acquired in vivo with EPT at 3 T MRI.

Introduction The reliability of hyperthermia treatment planning (HTP) is strongly dependent on the accuracy of the electric properties of each tissue. The values currently used are mostly based on ex vivo measurements. In this study, in vivo conductivity of human muscle, bladder content and cervical tumours, acquired with magnetic resonance-based electric properties tomography (MR-EPT), are exploited to investigate the effect on HTP for cervical cancer patients. Methods Temperature-based optimisation of five different patients was performed using literature-based conductivity values yielding certain antenna settings, which are then used to compute the temperature distribution of the patient models with EPT-based conductivity values. Furthermore, the effects of altered bladder and muscle conductivity were studied separately. Finally, the temperature-based optimisation was performed with patient models based on EPT conductivity values. Results The tumour temperatures for all EPT-based dielectric patient models were lower compared to the optimal tumour temperatures based on literature values. The largest deviation was observed for patient 1 with ΔT90 = -1.37 °C. A negative impact was also observed when the treatment was optimised based on the EPT values. For four patients ΔT90 was less than 0.6 °C; for one patient it was 1.5 °C. Conclusions Electric conductivity values acquired by EPT are higher than commonly used from literature. This difference has a substantial impact on cervical tumour temperatures achieved during hyperthermia. A higher conductivity in the bladder and in the muscle tissue surrounding the tumour leads to higher power dissipation in the bladder and muscle, and therefore to lower tumour temperatures.

Feasibility of electric property tomography of pelvic tumors at 3T.

PURPOSE: Investigation of the validity of the "transceive phase assumption" for Electric Property Tomography of pelvic tumors at 3T. The acquired electric conductivities of pelvic tumors are beneficial for improved specific absorption rate determination in hyperthermia treatment planning. METHODS: Electromagnetic simulations and magnetic resonance imaging measurements of a pelvic-sized phantom and the human pelvis of a volunteer and a cervix cancer patient. RESULTS: The reconstructed conductivity values of the phantom tumor model are in good quantitative agreement (mean deviation: 1-10%) with the probe measurements. Furthermore, the average reconstructed conductivity of a pelvic tumor model was in close agreement with the input conductivity (0.86 S/m vs. 0.90 S/m). The reconstructed tumor conductivity of the presented patient (cervical carcinoma, Stage: IVA) was 1.16 ± 0.40 S/m. CONCLUSION: This study demonstrates the feasibility of electric property tomography to measure quantitatively the conductivity of centrally located tumors in a pelvic-sized phantom and human pelvis with a standard magnetic resonance (MR) system and MR sequences. A good quantitative agreement was found between the reconstructed σ-values and probe measurements for a wide range of σ-values and for off-axis located spherical compartment. As most pelvic tumors are located in the central region of the pelvis, these results can be exploited in hyperthermia treatment planning systems.

Electrical properties tomography in the human brain at 1.5, 3, and 7T: a comparison study.

PURPOSE: To investigate the effect of magnetic field strength on the validity of two assumptions (namely, the "transceive phase assumption" and the "phase-only reconstruction") for electrical properties tomography (EPT) at 1.5, 3, and 7T. THEORY: Electrical properties tomography is a method to map the conductivity and permittivity using MRI; the B1 (+) amplitude and phase is required as input. The B1 (+) phase, however, cannot be measured and is therefore deduced from the measurable transceive phase using the transceive phase assumption. Also, earlier studies showed that the B1 (+) amplitude is not always required for a reliable conductivity reconstruction; this is the so-called "phase-only conductivity reconstruction." METHODS: Electromagnetic simulations and MRI measurements of phantoms and the human head. RESULTS: Reconstructed conductivity and permittivity maps based on B1 (+) distributions at 1.5, 3, and 7T were compared to the expected dielectric properties. The noise level of measurements was also determined. CONCLUSION: The transceive phase assumption is most accurate for low-field strengths and low permittivity and in symmetric objects. The phase-only conductivity reconstruction is only applicable at 1.5 and 3T for the investigated geometries. The measurement precision was found to benefit from a higher field strength, which is related to increased signal-to-noise ratio (SNR) and increased curvature of the B1 (+) field.

Imaging strategies in the management of oesophageal cancer: what's the role of MRI?

OBJECTIVES: To outline the current role and future potential of magnetic resonance imaging (MRI) in the management of oesophageal cancer regarding T-staging, N-staging, tumour delineation for radiotherapy (RT) and treatment response assessment. METHODS: PubMed, Embase and the Cochrane library were searched identifying all articles related to the use of MRI in oesophageal cancer. Data regarding the value of MRI in the areas of interest were extracted in order to calculate sensitivity, specificity, predictive values and accuracy for group-related outcome measures. RESULTS: Although historically poor, recent improvements in MRI protocols and techniques have resulted in better imaging quality and the valuable addition of functional information. In recent studies, similar or even better results have been achieved using optimised MRI compared with other imaging strategies for T- and N-staging. No studies clearly report on the role of MRI in oesophageal tumour delineation and real-time guidance for RT so far. Recent pilot studies showed that functional MRI might be capable of predicting pathological response to treatment and patient prognosis. CONCLUSIONS: In the near future MRI has the potential to bring improvement in staging, tumour delineation and real-time guidance for RT and assessment of treatment response, thereby complementing the limitations of currently used imaging strategies. KEY POINTS: • MRI's role in oesophageal cancer has been somewhat limited to date. • However MRI's ability to depict oesophageal cancer is continuously improving. • Optimising TN-staging, radiotherapy planning and response assessment ultimately improves individualised cancer care. • MRI potentially complements the limitations of other imaging strategies regarding these points.

Intrafraction motion analysis in online adaptive radiotherapy for esophageal cancer.

Intrafraction motion during magnetic resonance (MR)-guided dose delivery of esophageal cancer tumors was retrospectively analyzed. Deformable image registration of cine-MR series resulted in gross tumor volume motion profiles in all directions, which were subsequently filtered to isolate respiratory and drift motion. A large variability in intrafraction motion patterns was observed between patients. Median 95% peak-to-peak motion was 7.7 (3.7 - 18.3) mm, 2.1 (0.7 - 5.7) mm and 2.4 (0.5 - 5.6) mm in cranio-caudal, left-right and anterior-posterior directions, relatively. Furthermore, intrafraction drift was generally modest (<5mm). A patient specific approach could lead to very small margins (<3mm) for most patients.

Gating and intrafraction drift correction on a 1.5 T MR-Linac: Clinical dosimetric benefits for upper abdominal tumors.

This work reports on the first seven patients treated with gating and baseline drift correction on the high-field MR-Linac system. Dosimetric analysis showed that the active motion management system improved congruence to the planned dose, efficiently mitigating detrimental effects of intrafraction motion in the upper abdomen.

Recommendations for improved reproducibility of ADC derivation on behalf of the Elekta MRI-linac consortium image analysis working group.

BACKGROUND AND PURPOSE: The apparent diffusion coefficient (ADC), a potential imaging biomarker for radiotherapy response, needs to be reproducible before translation into clinical use. The aim of this study was to evaluate the multi-centre delineation- and calculation-related ADC variation and give recommendations to minimize it. MATERIALS AND METHODS: Nine centres received identical diffusion-weighted and anatomical magnetic resonance images of different cancerous tumours (adrenal gland, pelvic oligo metastasis, pancreas, and prostate). All centres delineated the gross tumour volume (GTV), clinical target volume (CTV), and viable tumour volume (VTV), and calculated ADCs using both their local calculation methods and each of the following calculation conditions: b-values 0-500 vs. 150-500 s/mm2, region-of-interest (ROI)-based vs. voxel-based calculation, and mean vs. median. ADC variation was assessed using the mean coefficient of variation across delineations (CVD) and calculation methods (CVC). Absolute ADC differences between calculation conditions were evaluated using Friedman's test. Recommendations for ADC calculation were formulated based on observations and discussions within the Elekta MRI-linac consortium image analysis working group. RESULTS: The median (range) CVD and CVC were 0.06 (0.02-0.32) and 0.17 (0.08-0.26), respectively. The ADC estimates differed 18% between b-value sets and 4% between ROI/voxel-based calculation (p-values < 0.01). No significant difference was observed between mean and median (p = 0.64). Aligning calculation conditions between centres reduced CVC to 0.04 (0.01-0.16). CVD was comparable between ROI types. CONCLUSION: Overall, calculation methods had a larger impact on ADC reproducibility compared to delineation. Based on the results, significant sources of variation were identified, which should be considered when initiating new studies, in particular multi-centre investigations.

B1(+) phase mapping at 7 T and its application for in vivo electrical conductivity mapping.

In this study, a new approach to measure local electrical conductivity in tissue is presented, which is based on the propagating B1(+) phase and the homogeneous Helmholtz equation. This new MRI technique might open future opportunities for tumor and lesion characterization based on conductivity differences, while it may also find application in radio frequency safety assessment. Prerequisites for conductivity mapping using only the B1(+) phase (instead of the complex B1(+) field) are addressed. Furthermore it was found that the B1(+) phase can be derived directly from the measurable transceive phase arg(B1(+)B1(-)) in the head. Validation for a human head excited by a 7 T-birdcage coil using simulations and measurements showed that it is possible to measure in vivo conductivity patterns in the brain using B1(+) phase information only. Conductivity contrast between different brain tissues is clearly observed. The measured mean values for white matter, gray matter and cerebrospinal fluid differed 54%, 26%, and -13% respectively from literature values. The proposed method for B1(+) phase measurements is very suited for in vivo applications, as the measurement is short (less than a minute per imaged slice) and exposes the patient to low RF power, contrary to earlier proposed approaches.

Radiofrequency heating induced by 7T head MRI: thermal assessment using discrete vasculature or Pennes' bioheat equation.

PURPOSE: To evaluate and compare the maximum temperature (T(max) ) in the head after exposure to a 300 MHz radiofrequency (RF) field induced by a magnetic resonance imaging (MRI) coil using two thermal simulation methods: Pennes' bioheat equation (PBHE) and discrete vasculature (DIVA). MATERIALS AND METHODS: The electromagnetic field induced in the head by a 7T birdcage coil was simulated using finite-difference time-domain (FDTD) and validated by MRI. The specific absorption rate (SAR) distributions normalized to the 10-gram maximum or the whole-head average were used for PBHE and DIVA simulations. RESULTS: For all cases, the T(max) in PBHE was slightly higher than in DIVA. The T(max) was 37.9-38.4°C, depending on the simulation method or perfusion rate. CONCLUSION: In some situations, RF exposure limited to SAR(max,10g) led to a T(max) higher than allowed by International Electrotechnical Commission (IEC) regulations. Therefore, it is advisable to use thermal simulations to evaluate RF safety of MRI. The simulation method used only slightly influenced the observed maximum temperature; the observed temperature with PBHE was higher in all situations. So PBHE is an appropriate method for RF safety assessment of MRI in the head. Using DIVA simulations, it was found unlikely that the body temperature increases significantly due to energy deposited by a head coil under normal circumstances.