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.

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.

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.

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.

Feasibility of cardiac-synchronized quantitative T1 and T2 mapping on a hybrid 1.5 Tesla magnetic resonance imaging and linear accelerator system.

Background and Purpose: The heart is important in radiotherapy either as target or organ at risk. Quantitative T1 and T2 cardiac magnetic resonance imaging (qMRI) may aid in target definition for cardiac radioablation, and imaging biomarker for cardiotoxicity assessment. Hybrid MR-linac devices could facilitate daily cardiac qMRI of the heart in radiotherapy. The aim of this work was therefore to enable cardiac-synchronized T1 and T2 mapping on a 1.5 T MR-linac and test the reproducibility of these sequences on phantoms and in vivo between the MR-linac and a diagnostic 1.5 T MRI scanner. Materials and methods: Cardiac-synchronized MRI was performed on the MR-linac using a wireless peripheral pulse-oximeter unit. Diagnostically used T1 and T2 mapping sequences were acquired twice on the MR-linac and on a 1.5 T MR-simulator for a gel phantom and 5 healthy volunteers in breath-hold. Phantom T1 and T2 values were compared to gold-standard measurements and percentage errors (PE) were computed, where negative/positive PE indicate underestimations/overestimations. Manually selected regions-of-interest were used for in vivo intra/inter scanner evaluation. Results: Cardiac-synchronized T1 and T2 qMRI was enabled after successful hardware installation on the MR-linac. From the phantom experiments, the measured T1/T2 relaxation times had a maximum percentage error (PE) of -4.4%/-8.8% on the MR-simulator and a maximum PE of -3.2%/+8.6% on the MR-linac. Mean T1/T2 of the myocardium were 1012 ± 34/51 ± 2 ms on the MR-simulator and 1034 ± 42/51 ± 1 ms on the MR-linac. Conclusions: Accurate cardiac-synchronized T1 and T2 mapping is feasible on a 1.5 T MR-linac and might enable novel plan adaptation workflows and cardiotoxicity assessments.

Comparison of Library of Plans with two daily adaptive strategies for whole bladder radiotherapy.

BACKGROUND AND PURPOSE: Whole bladder radiotherapy is challenging due to inter- and intrafraction size and shape changes. To account for these changes, currently a Library of Plans (LoP) technique is often applied, but daily adaptive radiotherapy is also increasingly becoming available. The aim of this study was to compare LoP with two magnetic resonance imaging guided radiotherapy (MRgRT) strategies by comparing target coverage and volume of healthy tissue inside the planning target volume (PTV) for whole bladder treatments. METHODS AND MATERIALS: Data from 25 MRgRT lymph node oligometastases treatments (125 fractions) were used, with three MRI scans acquired at each fraction at 0, 15 and 30 min. Bladders were delineated and used to evaluate three strategies: 1) LoP with two plans for a 15 min fraction, 2) MRgRT15min for a 15 min fraction and 3) MRgRT30min for a 30 min fraction. The volumes of healthy tissue inside and bladder outside the PTV were analyzed on the simulated post-treatment images. RESULTS: MRgRT30min had 120% and 121% more healthy tissue inside the PTV than LoP and MRgRT15min. For LoP slightly more target outside the PTV was found than for MRgRT30min and MRgRT15min, with median 0% (range 0-23%) compared to 0% (0-20%) and 0% (0-10%), respectively. CONCLUSIONS: Taking into account both target coverage and volume of healthy tissue inside the PTV, MRgRT15min performed better than LoP and MRgRT30min for whole bladder treatments. A 15 min daily adaptive radiotherapy workflow is needed to potentially benefit from replanning compared to LoP.

Influence of eye movement on lens dose and optic nerve target coverage during craniospinal irradiation.

PURPOSE: Optic nerves are part of the craniospinal irradiation (CSI) target volume. Modern radiotherapy techniques achieve highly conformal target doses while avoiding organs-at-risk such as the lens. The magnitude of eye movement and its influence on CSI target- and avoidance volumes are unclear. We aimed to evaluate the movement-range of lenses and optic nerves and its influence on dose distribution of several planning techniques. METHODS: Ten volunteers underwent MRI scans in various gaze directions (neutral, left, right, cranial, caudal). Lenses, orbital optic nerves, optic discs and CSI target volumes were delineated. 36-Gy cranial irradiation plans were constructed on synthetic CT images in neutral gaze, with Volumetric Modulated Arc Therapy, pencil-beam scanning proton therapy, and 3D-conventional photons. Movement-amplitudes of lenses and optic discs were analyzed, and influence of gaze direction on lens and orbital optic nerve dose distribution. RESULTS: Mean eye structures' shift from neutral position was greatest in caudal gaze; -5.8±1.2 mm (±SD) for lenses and 7.0±2.0 mm for optic discs. In 3D-conventional plans, caudal gaze decreased Mean Lens Dose (MLD). In VMAT and proton plans, eye movements mainly increased MLD and diminished D98 orbital optic nerve (D98OON) coverage; mean MLD increased up to 5.5 Gy [total ΔMLD range -8.1 to 10.0 Gy], and mean D98OON decreased up to 3.3 Gy [total ΔD98OON range -13.6 to 1.2 Gy]. VMAT plans optimized for optic disc Internal Target Volume and lens Planning organ-at-Risk Volume resulted in higher MLD over gaze directions. D98OON became ≥95% of prescribed dose over 95/100 evaluated gaze directions, while all-gaze bilateral D98OON significantly changed in 1 of 10 volunteers. CONCLUSION: With modern CSI techniques, eye movements result in higher lens doses and a mean detriment for orbital optic nerve dose coverage of <10% of prescribed dose.

Integration of quantitative imaging biomarkers in clinical trials for MR-guided radiotherapy: Conceptual guidance for multicentre studies from the MR-Linac Consortium Imaging Biomarker Working Group.

Quantitative imaging biomarkers (QIBs) derived from MRI techniques have the potential to be used for the personalised treatment of cancer patients. However, large-scale data are missing to validate their added value in clinical practice. Integrated MRI-guided radiotherapy (MRIgRT) systems, such as hybrid MRI-linear accelerators, have the unique advantage that MR images can be acquired during every treatment session. This means that high-frequency imaging of QIBs becomes feasible with reduced patient burden, logistical challenges, and costs compared to extra scan sessions. A wealth of valuable data will be collected before and during treatment, creating new opportunities to advance QIB research at large. The aim of this paper is to present a roadmap towards the clinical use of QIBs on MRIgRT systems. The most important need is to gather and understand how the QIBs collected during MRIgRT correlate with clinical outcomes. As the integrated MRI scanner differs from traditional MRI scanners, technical validation is an important aspect of this roadmap. We propose to integrate technical validation with clinical trials by the addition of a quality assurance procedure at the start of a trial, the acquisition of in vivo test-retest data to assess the repeatability, as well as a comparison between QIBs from MRIgRT systems and diagnostic MRI systems to assess the reproducibility. These data can be collected with limited extra time for the patient. With integration of technical validation in clinical trials, the results of these trials derived on MRIgRT systems will also be applicable for measurements on other MRI systems.

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.

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.

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.

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.

Preoperative Prediction of Pathologic Response to Neoadjuvant Chemoradiotherapy in Patients With Esophageal Cancer Using 18F-FDG PET/CT and DW-MRI: A Prospective Multicenter Study.

PURPOSE: Accurate preoperative prediction of pathologic response to neoadjuvant chemoradiotherapy (nCRT) in patients with esophageal cancer could enable omission of esophagectomy in patients with a pathologic complete response (pCR). This study aimed to evaluate the individual and combined value of 18F-fluorodeoxyglucose positron emission tomography with integrated computed tomography (18F-FDG PET/CT) and diffusion-weighted magnetic resonance imaging (DW-MRI) during and after nCRT to predict pathologic response in patients with esophageal cancer. METHODS AND MATERIALS: In this multicenter prospective study, patients scheduled to receive nCRT followed by esophagectomy for esophageal cancer underwent 18F-FDG PET/CT and DW-MRI scanning before the start of nCRT, during nCRT, and before esophagectomy. Response to nCRT was based on histopathologic evaluation of the resection specimen. Relative changes in 18F-FDG PET/CT and DW-MRI parameters were compared between patients with pCR and non-pCR groups. Multivariable ridge regression analyses with bootstrapped c-indices were performed to evaluate the individual and combined value of 18F-FDG PET/CT and DW-MRI. RESULTS: pCR was found in 26.1% of 69 patients. Relative changes in 18F-FDG PET/CT parameters after nCRT (Δ standardized uptake value [SUV]mean,postP = .016, and Δ total lesion glycolysis postP = .024), as well as changes in DW-MRI parameters during nCRT (Δ apparent diffusion coefficient [ADC]duringP = .008) were significantly different between pCR and non-pCR. A c-statistic of 0.84 was obtained for a model with ΔADCduring, ΔSUVmean,post, and histology in classifying patients as pCR (versus 0.82 for ΔADCduring and 0.79 for ΔSUVmean,post alone). CONCLUSIONS: Changes on 18F-FDG PET/CT after nCRT and early changes on DW-MRI during nCRT can help identify pCR to nCRT in esophageal cancer. Moreover, 18F-FDG PET/CT and DW-MRI might be of complementary value in the assessment of pCR.

Does an immobilization mask have added value during planning magnetic resonance imaging for stereotactic radiotherapy of brain tumours?

BACKGROUND AND PURPOSE: When using an immobilization mask, a magnetic resonance imaging (MRI) head receive coil cannot be used and patients may experience discomfort during the examination. We therefore wish to assess the added value of an immobilization mask during all MRI scans intended for cranial stereotactic radiotherapy (SRT) planning. MATERIALS AND METHODS: An MRI was acquired with and without a thermoplastic immobilization mask in ten patients eligible for SRT. A planning computed tomography (CT) scan was also made, to which the two MRIs were independently registered. Additionally, the MRI without immobilization was registered to the MRI in mask. On each sequence, gross tumour volume (GTV), the right eye, brain stem and chiasm were delineated. The absolute differences in centre-of-gravity coordinates and Dice coefficients of the volumes of the delineated structures between the two MRIs were compared. RESULTS: Differences in GTV volume between the two MRIs were low, with median Dice coefficients between 0.88 and 0.91. Similarly, the median absolute differences in centre-of-gravity coordinates between the GTVs, organs at risk and landmarks delineated on the two MRIs were within 0.5 mm. The 95% confidence intervals of the median absolute differences in the three GTV coordinates was within 1 mm, which corresponds to the target volume safety margin used to account for possible errors during the SRT treatment chain. CONCLUSIONS: The effect of scanning a patient without the immobilization mask falls within acceptable bounds of error for the geometrical accuracy of the SRT treatment chain. Consequently, placing the head in treatment position during all MRI scans for patients undergoing radiotherapy of brain metastasis is deemed unnecessary.

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.

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.

Gross Tumor Delineation in Esophageal Cancer on MRI Compared With 18F-FDG-PET/CT.

PURPOSE: Current delineation of the gross tumor volume (GTV) in esophageal cancer relies on computed tomography (CT) and combination with 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET). There is increasing interest in integrating magnetic resonance imaging (MRI) in radiation treatment, which can potentially obviate CT- or FDG-PET/CT-based delineation. The aim of this study is to evaluate the feasibility of target delineation on T2-weighted (T2W) MRI and T2W including diffusion-weighted MRI (T2W + DW-MRI) compared with current-practice FDG-PET/CT. METHODS: Ten observers delineated primary esophageal tumor GTVs of 6 patients on FDG-PET/CT, T2W-MRI, and T2W + DW-MRI. GTVs, generalized conformity indices, in-slice delineation variation (root mean square), and standard deviations in the position of the most cranial and caudal delineated slice were calculated. RESULTS: Delineations on MRI showed smaller GTVs compared with FDG-PET/CT-based delineations. The main variation was seen at the cranial and caudal border. No differences were observed in conformity indices (FDG-PET/CT, 0.68; T2W-MRI, 0.66; T2W + DW-MRI, 0.68) and in-slice variation (root mean square, 0.13 cm on FDG-PET/CT; 0.10 cm on T2W-MRI; 0.14 cm on T2W + DW-MRI). In the 2 tumors involving the gastroesophageal junction, addition of DW-MRI to T2W-MRI significantly decreased caudal border variation. CONCLUSIONS: MRI-based target delineation of the esophageal tumor is feasible with interobserver variability comparable to that with FDG-PET/CT, despite limited experience with delineation on MRI. Most variation was seen at cranial-caudal borders, and addition of DW-MRI to T2W-MRI may reduce caudal delineation variation of gastroesophageal junction tumors.

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.

Quantification of variations in intra-fraction motion of esophageal tumors over the course of neoadjuvant chemoradiotherapy based on cine-MRI.

To noninvasively quantify variation in intra-fraction motion of esophageal tumors over the course of neoadjuvant chemoradiotherapy (nCRT) using 2D cine-magnetic resonance imaging (MRI) series. Patients treated with nCRT for esophageal cancer underwent six MRI scans. Scans were acquired prior to the start of nCRT, followed by weekly MRI scans during nCRT. Cine-MRI series were acquired in the coronal and sagittal plane (≈1.6 Hz). To be able to quantify intra-fraction motion over a longer time period, a second cine-MRI series was performed after 10 min. Tumor motion was assessed in cranio-caudal (CC), anterior-posterior (AP) and left-right (LR) direction. Motion patterns were analyzed for the presence of deep inhales and tumor drift. A total of 232 cine-MRI series of 20 patients were analyzed. The largest tumor motion was found in CC direction, with a mean peak-to-peak motion of 12.7 mm (standard deviation [SD] 5.6), followed by a mean peak-to peak motion in AP direction of 3.8 mm (SD 2.0) and in LR direction of 2.7 mm (SD 1.3). The CC intra-fraction tumor motion can differ extensively between and within patients. Deep inhales were present in six of 232 scans (3%). After exclusion of these scans, mean CC peak-to-peak motion was12.3 mm (SD 5.2). Correction for tumor drift showed a further reduction to 11.0 mm (SD 4.6). Despite correction for tumor drift, a large variation in tumor motion occurred within patients during treatment. Mean tumor drift during the 10 min interval between the two series was 1.5 mm (SD 1.8), with a maximum of 11.6 mm. Intra-fraction tumor motion was found to be highly variable between and within patients with esophageal cancer over the course of nCRT. Correction for deep inhales and tumor drift reduced peak-to-peak motion. The stochastic nature of both deep inhales and tumor drift indicates that real-time tumor motion management during radiotherapy is a prerequisite to safely reduce treatment margins.

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.