Clinical applications for diffusion magnetic resonance imaging in radiotherapy

Assessing tumor microstructure with time-dependent diffusion imaging: Considerations and feasibility on clinical MRI and MRI-Linac

BACKGROUND

Quantitative imaging biomarkers (QIBs) can characterize tumor heterogeneity and provide information for biological guidance in radiotherapy (RT). Time-dependent diffusion MRI (TDD-MRI) derived parameters are promising QIBs, as they describe tissue microstructure with more specificity than traditional diffusion-weighted MRI (DW-MRI). Specifically, TDD-MRI can provide information about both restricted diffusion and diffusional exchange, which are the two time-dependent effects affecting diffusion in tissue, and relevant in tumors. However, exhaustive modeling of both effects can require long acquisitions and complex model fitting. Furthermore, several introduced TDD-MRI measurements can require high gradient strengths and/or complex gradient waveforms that are possibly not available in RT settings.

PURPOSE

In this study, we investigated the feasibility of a simple analysis framework for the detection of restricted diffusion and diffusional exchange effects in the TDD-MRI signal. To promote the clinical applicability, we use standard gradient waveforms on a conventional 1.5 T MRI system with moderate gradient strength (Gmax = 45 mT/m), and on a hybrid 1.5 T MRI-Linac system with low gradient strength (Gmax = 15 mT/m).

METHODS

Restricted diffusion and diffusional exchange were simulated in geometries mimicking tumor microstructure to investigate the DW-MRI signal behavior and to determine optimal experimental parameters. TDD-MRI was implemented using pulsed field gradient spin echo with the optimized parameters on a conventional MRI system and a MRI-Linac. Experiments in green asparagus and 10 patients with brain lesions were performed to evaluate the time-dependent diffusion (TDD) contrast in the source DW-images.

RESULTS

Simulations demonstrated how the TDD contrast was able to differentiate only dominating diffusional exchange in smaller cells from dominating restricted diffusion in larger cells. The maximal TDD contrast in simulations with typical cancer cell sizes and in asparagus measurements exceeded 5% on the conventional MRI but remained below 5% on the MRI-Linac. In particular, the simulated TDD contrast in typical cancer cell sizes (r = 5-10 µm) remained below or around 2% with the MRI-Linac gradient strength. In patients measured with the conventional MRI, we found sub-regions reflecting either dominating restricted diffusion or dominating diffusional exchange in and around brain lesions compared to the noisy appearing white matter.

CONCLUSIONS

On the conventional MRI system, the TDD contrast maps showed consistent tumor sub-regions indicating different dominating TDD effects, potentially providing information on the spatial tumor heterogeneity. On the MRI-Linac, the available TDD contrast measured in asparagus showed the same trends as with the conventional MRI but remained close to typical measurement noise levels when simulated in common cancer cell sizes. On conventional MRI systems with moderate gradient strengths, the TDD contrast could potentially be used as a tool to identify which time-dependent effects to include when choosing a biophysical model for more specific tumor characterization.

Tumor hypoxia unveiled: insights into microenvironment, detection tools and emerging therapies

Hypoxia is one of the defining characteristics of the tumor microenvironment (TME) in solid cancers. It has a major impact on the growth and spread of malignant cells as well as their resistance to common treatments like radiation and chemotherapy. Here, we explore the complex functions of hypoxia in the TME and investigate its effects on angiogenesis, immunological evasion, and cancer cell metabolism. For prognostic and therapeutic reasons, hypoxia identification is critical, and recent developments in imaging and molecular methods have enhanced our capacity to precisely locate underoxygenated areas inside tumors. Furthermore, targeted therapies that take advantage of hypoxia provide a potential new direction in the treatment of cancer. Therapeutic approaches that specifically target hypoxic conditions in tumors without causing adverse effects are being led by hypoxia-targeted nanocarriers and hypoxia-activated prodrugs (HAPs). This review provides an extensive overview of this dynamic and clinically significant area of oncology research by synthesizing current knowledge about the mechanisms of hypoxia in cancer, highlighting state-of-the-art detection methodologies, and assessing the potential and efficacy of hypoxia-targeted therapies.

Validation of daily 0.35 T diffusion-weighted MRI for MRI-guided glioblastoma radiotherapy

BACKGROUND

MRI-Linac systems enable daily diffusion-weighed imaging (DWI) MRI scans for assessing glioblastoma tumor changes with radiotherapy treatment.

PURPOSE

Our study assessed the image quality of echoplanar imaging (EPI)-DWI scans compared with turbo spin echo (TSE)-DWI scans at 0.35 Tesla (T) and compared the apparent diffusion coefficient (ADC) values and distortion of EPI-DWI on 0.35 T MRI-Linac compared to high-field diagnostic MRI scanners.

METHODS

The calibrated National Institute of Standards and Technology (NIST)/Quantitative Imaging Biomarkers Alliance (QIBA) Diffusion Phantom was scanned on a 0.35 T MRI-Linac, and 1.5 T and 3 T MRI with EPI-DWI. Five patients were scanned on a 0.35 T MRI-Linac with a TSE-DWI sequence, and five other patients were scanned with EPI-DWI on a 0.35 T MRI-Linac and a 3 T MRI. The quality of images was compared between the TSE-DWI and EPI-DWI on the 0.35 T MRI-Linac assessing signal-to-noise ratios and presence of artifacts. EPI-DWI ADC values and distortion magnitude were measured and compared between 0.35 T MRI-Linac and high-field MRI for both phantom and patient studies.

RESULTS

The average ADC differences between EPI-DWI acquired on the 0.35 T MRI-Linac, 1.5 T and 3 T MRI scanners and published references in the phantom study were 1.7%, 0.4% and 1.0%, respectively. Comparing the ADC values based on EPI-DWI in glioblastoma tumors, there was a 3.36% difference between 0.35 and 3 T measurements. Susceptibility-induced distortions in the EPI-DWI phantoms were 0.46 ± 1.51 mm for 0.35 MRI-Linac, 0.98 ± 0.51 mm for 1.5 T MRI and 1.14 ± 1.88 mm for 3 T MRI; for patients -0.47 ± 0.78 mm for 0.35 T and 1.73 ± 2.11 mm for 3 T MRIs. The mean deformable registration distortion for a phantom was 1.1 ± 0.22 mm, 3.5 ± 0.39 mm and 4.7 ± 0.37 mm for the 0.35 T MRI-Linac, 1.5 T MRI, and 3 T MRI scanners, respectively; for patients this distortion was -0.46 ± 0.57 mm for 0.35 T and 4.2 ± 0.41 mm for 3 T. EPI-DWI 0.35 T MRI-Linac images showed higher SNR and lack of artifacts compared with TSE-DWI, especially at higher b-values up to 1000 s/mm2.

CONCLUSION

EPI-DWI on a 0.35 T MRI-Linac showed superior image quality compared with TSE-DWI, minor and less distortions than high-field diagnostic scanners, and comparable ADC values in phantoms and glioblastoma tumors. EPI-DWI should be investigated on the 0.35 T MRI-Linac for prediction of early response in patients with glioblastoma.

Exploring the Impact of Irradiation on Glioblastoma Blood-Brain-Barrier Permeability: Insights from Dynamic-Contrast-Enhanced-MRI and Histological Analysis

(1) Background: Glioblastoma (GB) presents a formidable challenge in neuro-oncology due to its aggressive nature, limited treatment options, and poor prognosis. The blood-brain barrier (BBB) complicates treatment by hindering drug delivery to the tumor site, particularly to the infiltrative cells in the margin of the tumor, which are mainly responsible for tumor recurrence. Innovative strategies are therefore needed to enhance drug delivery in the margins of the tumor. This study explores whether irradiation can enhance BBB permeability by assessing hemodynamic changes and the distribution of contrast agents in the core and the margins of GB tumors. (2) Methods: Mice grafted with U-87MG cells were exposed to increasing irradiation doses. The distribution of contrast agents and hemodynamic parameters was evaluated using both non-invasive magnetic resonance imaging (MRI) techniques with gadolinium-DOTA as a contrast agent and invasive histological analysis with Evans blue, a fluorescent vascular leakage marker. Diffusion-MRI was also used to assess cytotoxic effects. (3) Results: The histological study revealed a complex dose-dependent effect of irradiation on BBB integrity, with increased vascular leakage at 5 Gy but reduced leakage at higher doses (10 and 15 Gy). However, there was no significant increase in the diffusion of Gd-DOTA outside the tumor area by MRI. (4) Conclusions: The increase in BBB permeability could be an interesting approach to enhance drug delivery in glioblastoma margins for low irradiation doses. In this model, DCE-MRI analysis was of limited value in assessing the BBB opening in glioblastoma after irradiation.

Correlation between rCBV Delineation Similarity and Overall Survival in a Prospective Cohort of High-Grade Gliomas Patients: The Hidden Value of Multimodal MRI?

PURPOSE

The accuracy of target delineation in radiation treatment planning of high-grade gliomas (HGGs) is crucial to achieve high tumor control, while minimizing treatment-related toxicity. Magnetic resonance imaging (MRI) represents the standard imaging modality for delineation of gliomas with inherent limitations in accurately determining the microscopic extent of tumors. The purpose of this study was to assess the survival impact of multi-observer delineation variability of multiparametric MRI (mpMRI) and [18F]-FET PET/CT.

MATERIALS AND METHODS

Thirty prospectively included patients with histologically confirmed HGGs underwent a PET/CT and mpMRI including diffusion-weighted imaging (DWI: b0, b1000, ADC), contrast-enhanced T1-weighted imaging (T1-Gado), T2-weighted fluid-attenuated inversion recovery (T2Flair), and perfusion-weighted imaging with computation of relative cerebral blood volume (rCBV) and K2 maps. Nine radiation oncologists delineated the PET/CT and MRI sequences. Spatial similarity (Dice similarity coefficient: DSC) was calculated between the readers for each sequence. Impact of the DSC on progression-free survival (PFS) and overall survival (OS) was assessed using Kaplan-Meier curves and the log-rank test.

RESULTS

The highest DSC mean values were reached for morphological sequences, ranging from 0.71 +/- 0.18 to 0.84 +/- 0.09 for T2Flair and T1Gado, respectively, while metabolic volumes defined by PET/CT achieved a mean DSC of 0.75 +/- 0.11. rCBV variability (mean DSC0.32 +/- 0.20) significantly impacted PFS (p = 0.02) and OS (p = 0.002).

CONCLUSIONS

Our data suggest that the T1-Gado and T2Flair sequences were the most reproducible sequences, followed by PET/CT. Reproducibility for functional sequences was low, but rCBV inter-reader similarity significantly impacted PFS and OS.

How Imaging Advances Are Defining the Future of Precision Radiation Therapy

Radiation therapy is fundamental in the treatment of cancer. Imaging has always played a central role in radiation oncology. Integrating imaging technology into irradiation devices has increased the precision and accuracy of dose delivery and decreased the toxic effects of the treatment. Although CT has become the standard imaging modality in radiation therapy, the development of recently introduced next-generation imaging techniques has improved diagnostic and therapeutic decision making in radiation oncology. Functional and molecular imaging techniques, as well as other advanced imaging modalities such as SPECT, yield information about the anatomic and biologic characteristics of tumors for the radiation therapy workflow. In clinical practice, they can be useful for characterizing tumor phenotypes, delineating volumes, planning treatment, determining patients' prognoses, predicting toxic effects, assessing responses to therapy, and detecting tumor relapse. Next-generation imaging can enable personalization of radiation therapy based on a greater understanding of tumor biologic factors. It can be used to map tumor characteristics, such as metabolic pathways, vascularity, cellular proliferation, and hypoxia, that are known to define tumor phenotype. It can also be used to consider tumor heterogeneity by highlighting areas at risk for radiation resistance for focused biologic dose escalation, which can impact the radiation planning process and patient outcomes. The authors review the possible contributions of next-generation imaging to the treatment of patients undergoing radiation therapy. In addition, the possible roles of radio(geno)mics in radiation therapy, the limitations of these techniques, and hurdles in introducing them into clinical practice are discussed. ©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material.

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.

Multi-parametric MRI for radiotherapy simulation

Magnetic resonance imaging (MRI) has become an important imaging modality in the field of radiotherapy (RT) in the past decade, especially with the development of various novel MRI and image-guidance techniques. In this review article, we will describe recent developments and discuss the applications of multi-parametric MRI (mpMRI) in RT simulation. In this review, mpMRI refers to a general and loose definition which includes various multi-contrast MRI techniques. Specifically, we will focus on the implementation, challenges, and future directions of mpMRI techniques for RT simulation.

Improving liver tumor image contrast and synthesizing novel tissue contrasts by adaptive multiparametric MRI fusion

Purpose

Multiparametric MRI contains rich and complementary anatomical and functional information, which is often utilized separately. This study aims to propose an adaptive multiparametric MRI (mpMRI) fusion method and examine its capability in improving tumor contrast and synthesizing novel tissue contrasts among liver cancer patients.

Methods

An adaptive mpMRI fusion method was developed with five components: image pre-processing, fusion algorithm, database, adaptation rules, and fused MRI. Linear-weighted summation algorithm was used for fusion. Weight-driven and feature-driven adaptations were designed for different applications. A clinical-friendly graphic-user-interface (GUI) was developed in Matlab and used for mpMRI fusion. Twelve liver cancer patients and a digital human phantom were included in the study. Synthesis of novel image contrast and enhancement of image signal and contrast were examined in patient cases. Tumor contrast-to-noise ratio (CNR) and liver signal-to-noise ratio (SNR) were evaluated and compared before and after mpMRI fusion.

Results

The fusion platform was applicable in both XCAT phantom and patient cases. Novel image contrasts, including enhancement of soft-tissue boundary, vertebral body, tumor, and composition of multiple image features in a single image were achieved. Tumor CNR improved from -1.70 ± 2.57 to 4.88 ± 2.28 (p < 0.0001) for T1-w, from 3.39 ± 1.89 to 7.87 ± 3.47 (p < 0.01) for T2-w, and from 1.42 ± 1.66 to 7.69 ± 3.54 (p < 0.001) for T2/T1-w MRI. Liver SNR improved from 2.92 ± 2.39 to 9.96 ± 8.60 (p < 0.05) for DWI. The coefficient of variation (CV) of tumor CNR lowered from 1.57, 0.56, and 1.17 to 0.47, 0.44, and 0.46 for T1-w, T2-w and T2/T1-w MRI, respectively.

Conclusion

A multiparametric MRI fusion method was proposed and a prototype was developed. The method showed potential in improving clinically relevant features such as tumor contrast and liver signal. Synthesis of novel image contrasts including the composition of multiple image features into single image set was achieved.

Radiomic Features From Diffusion-Weighted MRI of Retroperitoneal Soft-Tissue Sarcomas Are Repeatable and Exhibit Change After Radiotherapy

Background

Size-based assessments are inaccurate indicators of tumor response in soft-tissue sarcoma (STS), motivating the requirement for new response imaging biomarkers for this rare and heterogeneous disease. In this study, we assess the test-retest repeatability of radiomic features from MR diffusion-weighted imaging (DWI) and derived maps of apparent diffusion coefficient (ADC) in retroperitoneal STS and compare baseline repeatability with changes in radiomic features following radiotherapy (RT).

Materials and Methods

Thirty patients with retroperitoneal STS received an MR examination prior to treatment, of whom 23/30 were investigated in our repeatability analysis having received repeat baseline examinations and 14/30 patients were investigated in our post-treatment analysis having received an MR examination after completing pre-operative RT. One hundred and seven radiomic features were extracted from the full manually delineated tumor region using PyRadiomics. Test-retest repeatability was assessed using an intraclass correlation coefficient (baseline ICC), and post-radiotherapy variance analysis (post-RT-IMS) was used to compare the change in radiomic feature value to baseline repeatability.

Results

For the ADC maps and DWI images, 101 and 102 features demonstrated good baseline repeatability (baseline ICC > 0.85), respectively. Forty-three and 2 features demonstrated both good baseline repeatability and a high post-RT-IMS (>0.85), respectively. Pearson correlation between the baseline ICC and post-RT-IMS was weak (0.432 and 0.133, respectively).

Conclusions

The ADC-based radiomic analysis shows better test-retest repeatability compared with features derived from DWI images in STS, and some of these features are sensitive to post-treatment change. However, good repeatability at baseline does not imply sensitivity to post-treatment change.

Evaluation of DIR schemes on tumor/organ with progressive shrinkage: accuracy of tumor/organ internal tissue tracking during the radiation treatment

PURPOSE

Accuracy of intratumoral treatment dose accumulation and response assessment highly depends on the accuracy of a DIR method. However, achievable accuracy of the existing DIR methods for tumor/organ with large and progressive shrinkage during the radiotherapy course have not been explored. This study aimed to use a bio-tissue phantom to quantify the achievable accuracy of different DIR schemes.

MATERIALS /METHODS

A fresh porcine liver was used for phantom material. Sixty gold markers were implanted on the surface and inside of the liver. To simulate the progressive radiation-induced tumor/organ shrinkage, the phantom was heated using a microwave oven incrementally from 30s to 200s in 8 phases. For each phase, the phantom was scanned by CT. Two extra image sets were generated from the original images: 1) the image set with overriding the high-density gold markers (feature image); 2) the image set with overriding the entire phantom to the mean soft tissue intensity (featureless image). Ten DIR schemes were evaluated to mimic clinical treatment situations of tumor/critical organ with respect to their surface and internal condition of image features, availability of intermediate feedback images and DIR methods. The internal marker's positions were utilized to evaluate DIR accuracy quantified by target registration error (TRE).

RESULTS

Volume reduction was about 20% ∼ 40% of the initial volume after 90s ∼ 200s of the heating. Without image features on the surface and inside of the phantom, the hybrid-DIR (image-based DIR followed by biomechanical model-based refinement) with the surface constraint achieved the registration TRE from 2.6 ± 1.2mm to 5.3 ± 2.6mm proportional to the %volume shrinkage. Meanwhile, the hybrid-DIR with the surface-marker constraint achieved the TRE from 2.4 ± 1.2mm to 2.6 ± 1.0mm. If both the surface and internal image features would be viable on the feedback images, the achievable accuracy could be minimal with the TRE from 1.6±0.9mm to 1.9 ± 1.2mm.

CONCLUSIONS

Standard DIR methods cannot guarantee intratumoral tissue registration accuracy for tumor/organ with large progressive shrinkage. Achievable accuracy with using the hybrid DIR method is highly dependent on the surface registration accuracy. If the surface registration mean TRE can be controlled within 2mm, the mean TRE of internal tissue can be controlled within 3mm.

Multi-parametric PET/MRI for enhanced tumor characterization of patients with cervical cancer

Aim

The concept of personalized medicine has brought increased awareness to the importance of inter- and intra-tumor heterogeneity for cancer treatment. The aim of this study was to explore simultaneous multi-parametric PET/MRI prior to chemoradiotherapy for cervical cancer for characterization of tumors and tumor heterogeneity.

Methods

Ten patients with histologically proven primary cervical cancer were examined with multi-parametric 68Ga-NODAGA-E[c(RGDyK)]2-PET/MRI for radiation treatment planning after diagnostic 18F-FDG-PET/CT. Standardized uptake values (SUV) of RGD and FDG, diffusion weighted MRI and the derived apparent diffusion coefficient (ADC), and pharmacokinetic maps obtained from dynamic contrast-enhanced MRI with the Tofts model (iAUC60, Ktrans, ve, and kep) were included in the analysis. The spatial relation between functional imaging parameters in tumors was examined by a correlation analysis and joint histograms at the voxel level. The ability of multi-parametric imaging to identify tumor tissue classes was explored using an unsupervised 3D Gaussian mixture model-based cluster analysis.

Results

Functional MRI and PET of cervical cancers appeared heterogeneous both between patients and spatially within the tumors, and the relations between parameters varied strongly within the patient cohort. The strongest spatial correlation was observed between FDG uptake and ADC (median r =  − 0.7). There was moderate voxel-wise correlation between RGD and FDG uptake, and weak correlations between all other modalities. Distinct relations between the ADC and RGD uptake as well as the ADC and FDG uptake were apparent in joint histograms. A cluster analysis using the combination of ADC, FDG and RGD uptake suggested tissue classes which could potentially relate to tumor sub-volumes.

Conclusion

A multi-parametric PET/MRI examination of patients with cervical cancer integrated with treatment planning and including estimation of angiogenesis and glucose metabolism as well as MRI diffusion and perfusion parameters is feasible. A combined analysis of functional imaging parameters indicates a potential of multi-parametric PET/MRI to contribute to a better characterization of tumor heterogeneity than the modalities alone. However, the study is based on small patient numbers and further studies are needed prior to the future design of individually adapted treatment approaches based on multi-parametric functional imaging.

Integration of functional imaging in brachytherapy

Functional imaging allows the evaluation of numerous biological properties that could be considered at all steps of the therapeutic management of patients treated with brachytherapy. Indeed, it enables better initial staging of the disease, and some parameters may also be used as predictive biomarkers for treatment response, allowing better selection of patients eligible for brachytherapy. It may also improve the definition of target volumes with the aim of dose escalations by dose-painting. Finally, it could be useful during the follow-up to assess response to treatment. In this review, we report how functional imaging is integrated at the present time during the brachytherapy procedure, and what are its potential future contributions in the main tumour locations where brachytherapy is recommended. Functional imaging has great potential in the contact of brachytherapy, but still, several issues remain to be resolved before integrating it into clinical practice, especially as a biomarker or in dose painting strategies.

Image-based personalization of computational models for predicting response of high-grade glioma to chemoradiation

High-grade gliomas are an aggressive and invasive malignancy which are susceptible to treatment resistance due to heterogeneity in intratumoral properties such as cell proliferation and density and perfusion. Non-invasive imaging approaches can measure these properties, which can then be used to calibrate patient-specific mathematical models of tumor growth and response. We employed multiparametric magnetic resonance imaging (MRI) to identify tumor extent (via contrast-enhanced T1-weighted, and T2-FLAIR) and capture intratumoral heterogeneity in cell density (via diffusion-weighted imaging) to calibrate a family of mathematical models of chemoradiation response in nine patients with unresected or partially resected disease. The calibrated model parameters were used to forecast spatially-mapped individual tumor response at future imaging visits. We then employed the Akaike information criteria to select the most parsimonious member from the family, a novel two-species model describing the enhancing and non-enhancing components of the tumor. Using this model, we achieved low error in predictions of the enhancing volume (median: - 2.5%, interquartile range: 10.0%) and a strong correlation in total cell count (Kendall correlation coefficient 0.79) at 3-months post-treatment. These preliminary results demonstrate the plausibility of using multiparametric MRI data to inform spatially-informative, biologically-based predictive models of tumor response in the setting of clinical high-grade gliomas.

Computed Tomography Radiomics Kinetics as Early Imaging Correlates of Osteoradionecrosis in Oropharyngeal Cancer Patients

Osteoradionecrosis (ORN) is a major side-effect of radiation therapy in oropharyngeal cancer (OPC) patients. In this study, we demonstrate that early prediction of ORN is possible by analyzing the temporal evolution of mandibular subvolumes receiving radiation. For our analysis, we use computed tomography (CT) scans from 21 OPC patients treated with Intensity Modulated Radiation Therapy (IMRT) with subsequent radiographically-proven ≥ grade II ORN, at three different time points: pre-IMRT, 2-months, and 6-months post-IMRT. For each patient, radiomic features were extracted from a mandibular subvolume that developed ORN and a control subvolume that received the same dose but did not develop ORN. We used a Multivariate Functional Principal Component Analysis (MFPCA) approach to characterize the temporal trajectories of these features. The proposed MFPCA model performs the best at classifying ORN vs. Control subvolumes with an area under curve (AUC) = 0.74 [95% confidence interval (C.I.): 0.61–0.90], significantly outperforming existing approaches such as a pre-IMRT features model or a delta model based on changes at intermediate time points, i.e., at 2- and 6-month follow-up. This suggests that temporal trajectories of radiomics features derived from sequential pre- and post-RT CT scans can provide markers that are correlates of RT-induced mandibular injury, and consequently aid in earlier management of ORN.

Heterogeneity analysis of MRI T2 maps for measurement of early tumor response to radiotherapy

External beam radiotherapy (XRT) is a widely used cancer treatment, yet responses vary dramatically among patients. These differences are not accounted for in clinical practice, partly due to a lack of sensitive early response biomarkers. We hypothesize that quantitative magnetic resonance imaging (MRI) measures reflecting tumor heterogeneity can provide a sensitive and robust biomarker of early XRT response. MRI T2 mapping was performed every 72 hours following 10 Gy dose XRT in two models of pancreatic cancer propagated in the hind limb of mice. Interquartile range (IQR) of tumor T2 was presented as a potential biomarker of radiotherapy response compared with tumor growth kinetics, and biological validation was performed through quantitative histology analysis. Quantification of tumor T2 IQR showed sensitivity for detection of XRT-induced tumor changes 72 hours after treatment, outperforming T2-weighted and diffusion-weighted MRI, with very good robustness. Histological comparison revealed that T2 IQR provides a measure of spatial heterogeneity in tumor cell density, related to radiation-induced necrosis. Early IQR changes were found to correlate to subsequent tumor volume changes, indicating promise for treatment response prediction. Our preclinical findings indicate that spatial heterogeneity analysis of T2 MRI can provide a translatable method for early radiotherapy response assessment. We propose that the method may in future be applied for personalization of radiotherapy through adaptive treatment paradigms.

A simulation study of cell size and volume fraction mapping for tissue with two underlying cell populations using diffusion-weighted MRI

PURPOSE

To propose a method for voxel-wise estimation of cell radii and volume fractions of two cell populations when they coexist in the same MR voxel using the combination of diffusion-weighted MRI and microstructural modeling.

METHOD

Microstructure models were investigated using diffusion data simulated with the matrix method for a range of microstructures mimicking tumor tissue with two cell populations, using acquisition parameters available on preclinical scanners. The effect of noise was investigated for a subset of these microstructures. The accuracy and precision of the estimated radii and volume fractions for large and small cells R l , R s , v i n , l , v i n , s were evaluated by comparing the estimates to their true values. The stability of model fitting was characterized by the percentage of accepted fits.

RESULTS

The estimation accuracy and precision, and thus the ability to robustly distinguish the two cell populations, depended on the microstructural properties and SNR. For a SNR of 50, a minimum difference of 3 μm between the radius of the large and small cell populations was required for differentiation. Proposed modifications to the two cell population microstructure model, including constrained fits, improved the stability of fits.

CONCLUSIONS

This proof-of-concept study proposed a diffusion MRI-based method for voxel-wise estimation of cell radii and volume fractions of two cell populations when they coexist in the same MR voxel. The ability to reliably characterize tissue with two cell populations opens exciting avenues of potential applications in both tumor diagnosis and treatment monitoring.

Accuracy of an MR-only workflow for prostate radiotherapy using semi-automatically burned-in fiducial markers

BACKGROUND

The benefit of MR-only workflow compared to current CT-based workflow for prostate radiotherapy is reduction of systematic errors in the radiotherapy chain by 2-3 mm. Nowadays, MRI is used for target delineation while CT is needed for position verification. In MR-only workflows, MRI based synthetic CT (sCT) replaces CT. Intraprostatic fiducial markers (FMs) are used as a surrogate for the position of the prostate improving targeting. However, FMs are not visible on sCT. Therefore, a semi-automatic method for burning-in FMs on sCT was developed. Accuracy of MR-only workflow using semi-automatically burned-in FMs was assessed and compared to CT/MR workflow.

METHODS

Thirty-one prostate cancer patients receiving radiotherapy, underwent an additional MR sequence (mDIXON) to create an sCT for MR-only workflow simulation. Three sources of accuracy in the CT/MR- and MR-only workflow were investigated. To compare image registrations for target delineation, the inter-observer error (IOE) of FM-based CT-to-MR image registrations and soft-tissue-based MR-to-MR image registrations were determined on twenty patients. Secondly, the inter-observer variation of the resulting FM positions was determined on twenty patients. Thirdly, on 26 patients CBCTs were retrospectively registered on sCT with burned-in FMs and compared to CT-CBCT registrations.

RESULTS

Image registration for target delineation shows a three times smaller IOE for MR-only workflow compared to CT/MR workflow. All observers agreed in correctly identifying all FMs for 18 out of 20 patients (90%). The IOE in CC direction of the center of mass (COM) position of the markers was within the CT slice thickness (2.5 mm), the IOE in AP and RL direction were below 1.0 mm and 1.5 mm, respectively. Registrations for IGRT position verification in MR-only workflow compared to CT/MR workflow were equivalent in RL-, CC- and AP-direction, except for a significant difference for random error in rotation.

CONCLUSIONS

MR-only workflow using sCT with burned-in FMs is an improvement compared to the current CT/MR workflow, with a three times smaller inter observer error in CT-MR registration and comparable CBCT registration results between CT and sCT reference scans. Trial registry Medical Research Involving Human Subjects Act (WMO) does apply to this study and was approved by the Medical Ethics review Committee of the Academic Medical Center. Registration number: NL65414.018.18. Date of registration: 21-08-2018.

Quantitative Magnetic Resonance Imaging for Biological Image-Guided Adaptive Radiotherapy

MRI-guided radiotherapy systems have the potential to bring two important concepts in modern radiotherapy together: adaptive radiotherapy and biological targeting. Based on frequent anatomical and functional imaging, monitoring the changes that occur in volume, shape as well as biological characteristics, a treatment plan can be updated regularly to accommodate the observed treatment response. For this purpose, quantitative imaging biomarkers need to be identified that show changes early during treatment and predict treatment outcome. This review provides an overview of the current evidence on quantitative MRI measurements during radiotherapy and their potential as an imaging biomarker on MRI-guided radiotherapy systems.

Evaluation of diffusion-weighted MRI and geometric distortion on a 0.35T MR-LINAC at multiple gantry angles

Diffusion-weighted imaging (DWI) provides a valuable diagnostic tool for tumor evaluation. Yet, it is difficult to acquire daily MRI data sets in the traditional radiotherapy clinical setting due to patient burden and limited resources. However, integrated MRI radiotherapy treatment systems facilitate daily functional MRI acquisitions like DWI during treatment exams. Before ADC values from MR-RT systems can be used clinically their reproducibility and accuracy must be quantified. This study used a NIST traceable DWI phantom to verify ADC values acquired on a 0.35 T MR-LINAC system at multiple gantry angles. A diffusion-weighted echo planar imaging sequence was used for all image acquisitions, with b-values of 0, 500, 900, 2000 s/mm² for the 1.5 T and 3.0 T systems and 0, 200, 500, 800 s/mm² for the 0.35 T system. Images were acquired at multiple gantry angles on the MR-LINAC system from 0° to 330° in 30° increments to assess the impact of gantry angle on geometric distortion and ADC values. CT images, and three fiducial markers were used as ground truth for geometric distortion measurements. The distance between fiducial markers increased by as much as 7.2 mm on the MR-LINAC at gantry angle 60°. ADC values of deionized water vials from the 1.5 T and 3.0 T systems were 8.30 × 10^-6  mm² /s and -0.85 × 10^-6  mm² /s off, respectively, from the expected value of 1127 × 10^-6  mm² /s. The MR-LINAC system provided an ADC value of the pure water vials that was -116.63 × 10^-6  mm² /s off from the expected value of 1127 × 10^-6  mm² /s. The MR-LINAC also showed a variation in ADC across all gantry angles of 33.72 × 10^-6  mm² /s and 20.41 × 10^-6  mm² /s for the vials with expected values of 1127 × 10^-6  mm² /s and 248 × 10^-6  mm² /s, respectively. This study showed that variation of the ADC values and geometric information on the 0.35 T MR-LINAC system was dependent on the gantry angle at acquisition.

Gradient waveform design for tensor-valued encoding in diffusion MRI

Diffusion encoding along multiple spatial directions per signal acquisition can be described in terms of a b-tensor. The benefit of tensor-valued diffusion encoding is that it unlocks the 'shape of the b-tensor' as a new encoding dimension. By modulating the b-tensor shape, we can control the sensitivity to microscopic diffusion anisotropy which can be used as a contrast mechanism; a feature that is inaccessible by conventional diffusion encoding. Since imaging methods based on tensor-valued diffusion encoding are finding an increasing number of applications we are prompted to highlight the challenge of designing the optimal gradient waveforms for any given application. In this review, we first establish the basic design objectives in creating field gradient waveforms for tensor-valued diffusion MRI. We also survey additional design considerations related to limitations imposed by hardware and physiology, potential confounding effects that cannot be captured by the b-tensor, and artifacts related to the diffusion encoding waveform. Throughout, we discuss the expected compromises and tradeoffs with an aim to establish a more complete understanding of gradient waveform design and its impact on accurate measurements and interpretations of data.

Comparison and evaluation of distortion correction techniques on an MR-guided radiotherapy system

PURPOSE

To evaluate two distortion correction techniques for diffusion-weighted single-shot echo-planar imaging (DW-ssEPI) on a 0.35 T magnetic resonance-guided radiotherapy (MRgRT) system.

METHODS

The effects of sequence optimization through enabling parallel imaging (PI) and selecting appropriate bandwidth on spatial distortion were first evaluated on the 0.35 T MRgRT system using a spatial integrity phantom. Field map (FM) and reversed gradient (RG) corrections were then performed on the optimized protocol to further reduce distortion. An open-source toolbox was used to quantify the spatial displacement before and after distortion correction. To evaluate ADC accuracy and repeatability of the optimized protocol, as well as impacts of distortion correction on ADC values, the optimized protocol was scanned twice on a diffusion phantom. The calculated ADC values were compared with reference ADCs using paired t-test. Intraclass correlation coefficient (ICC) between the two repetitions, as well as between before and after FM/RG correction was calculated to evaluate ADC repeatability and effects of distortion correction. Six patients were recruited to assess the in-vivo performance. The optimal distortion correction technique was identified by visual assessment. To quantify distortion reduction, tumor and critical structures were contoured on the turbo spin echo (TSE) image (reference image), the DW-ssEPI image, and the distortion corrected images independently by two radiation oncologists. Mean distance to agreement (MDA) and DICE coefficient between contours on the reference images and the diffusion images were calculated. Tumor apparent diffusion coefficient (ADC) values from the original DW-ssEPI images and the distortion corrected images were compared using Bland-Altman analysis.

RESULTS

Sequence optimization played a vital role in improving the spatial integrity, and spatial distortion was proportional to the total readout time. Before the correction, distortion of the optimized protocol (PI and high bandwidth) was 1.50 ± 0.89 mm in a 100 mm radius and 2.21 ± 1.39 mm in a 175 mm radius for the central plane. FM corrections reduced the distortions to 0.42 ± 0.27 mm and 0.67 ± 0.49 mm respectively, and RG reduced distortion to 0.40 ± 0.22 mm and 0.64 ± 0.47 mm, respectively. The optimized protocol provided accurate and repeatable ADC quantification on the diffusion phantom. The calculated ADC values were consistent before and after FM/RG correction. For the patient study, the FM correction was unable to reduce chemical shift artifacts whereas the RG method successfully mitigated the chemical shift. MDA reduced from 2.52 ± 1.29 mm to 1.11 ± 0.72 mm after the RG correction. The DICE coefficient increased from 0.80 ± 0.13 to 0.91 ± 0.06. A Bland-Altman plot showed that there was a good agreement between ADC measurements before and after application of the RG correction.

CONCLUSION

Two distortion correction techniques were evaluated on a commercial low-field MRgRT system. Overall, the RG correction was able to drastically improve spatial distortion and preserve ADC accuracy.

B0 field homogeneity recommendations, specifications, and measurement units for MRI in radiation therapy

PURPOSE

The purpose is: (a) Relate magnetic resonance imaging (MRI) quality recommendations for radiation therapy (RT) to B₀ field homogeneity; (b) Evaluate manufacturer specifications of B₀ homogeneity for 34 commercial whole-body MRI systems based on the MRI quality recommendations and RT application; (c) Measure field homogeneity in five commercial MRI systems and one commercial MRI-Linac used in RT and compare the results with their B₀ homogeneity specifications.

METHODS

Magnetic resonance imaging quality recommendations for spatial integrity, image blurring, fat saturation, and null banding in RT were developed based on the literature. Guaranteed (maximum) and typical B₀ field homogeneity specifications for various diameter spherical volumes (DSVs) were provided by GE, Philips, Siemens, and Canon. For each system, the DSV that conforms to each MRI quality recommendation and anatomical RT application was estimated based on the manufacturer specifications. B₀ field homogeneity was measured on six MRI systems including Philips (1.5 T), Siemens (1.5 and 3 T), and ViewRay MRI (0.35 T) systems using 24 and 35 cm DSV spherical phantoms. Two measurement techniques were used: (a) MRI using phase contrast field mapping to measure peak-to-peak (pk-pk), volume root mean square (VRMS), and standard deviation (SD); and (b) Magnetic resonance (MR) spectroscopy by acquiring a volumetric free induction decay (FID) to measure full width at half maximum (FWHM). The measurements were used to assess: (a) conformance with the manufacturer specifications; and (b) the relationship between the various field homogeneity measurement units. Measurements were made with and without gradient shimming (gradshim) or second-order active shimming. Multiple comparisons, analysis of variance (ANOVA), and Pearson correlations were performed to assess the dependence of pk-pk, VRMS, SD, and FWHM measurements of field homogeneity on shim volume, level of shim, and MRI system.

RESULTS

For a 40 cm DSV, the B₀ homogeneity specifications ranged from 0.35 to 5 ppm (median = 0.75 ppm) VRMS for 1.5 T systems and 0.2 to 1.4 ppm (median = 0.5 ppm) VRMS for 3 T systems. The usable DSVs ranged from 16 to 49 cm (median = 35 cm) based on the image quality recommendations and the manufacturer specifications. There was general compliance between the six measured field homogeneities and manufacturer specifications although signal dephasing was observed in two systems at < 35 cm DSV. The relationships between pk-pk, VRMS, SD, and FWHM varied based on MRI system, shim volume, and quality of shim. However, VRMS and SD measurements were highly correlated.

CONCLUSIONS

The delineation of the diseased lesion from organs at risk is the main priority for RT. Therefore, field homogeneity performance for RT must minimize image blurring and image artifacts (null bands and signal dephasing) while optimizing spatial integrity and fat saturation. Based on the specifications and recommendations for field homogeneity, some MRI systems are not well suited to meet the strict demands of RT particularly for the large imaging volumes used in body MRI. VRMS and SD measurements of B₀ field homogeneity tend to be more stable and sensitive to field inhomogeneities in RT applications than pk-pk and FWHM.

Response Evaluation of Choroidal Melanoma After Brachytherapy Using Diffusion-Weighted Magnetic Resonance Imaging (DW-MRI): Preliminary Findings

Purpose: To evaluate the role of diffusion-weighted magnetic resonance imaging (DW-MRI) in the assessment of therapeutic response in patients with choroidal melanoma treated with brachytherapy.

Materials and Methods: We performed a prospective, unicentric study which included patients with choroidal melanoma and indication for brachytherapy. Three DW-MRI examinations were proposed for each patient, one before and two after treatment. The apparent diffusion coefficient (ADC) value was calculated on DW-MRI and compared with local tumor control assessed by ophthalmologic follow-up.

Results: From 07/2018 to 06/2019, 19 patients were recruited, 13 of whom underwent follow-up examinations. Patients' ages ranged from 24 to 78 years and 52.9% were male. At the ocular ultrasound, the mean tumor thickness and diameter were 6.3 and 11.5 mm, respectively. Two patients (15.4%) showed signs of tumor progression during follow-up (7 and 9 months after treatment). There was no statistically significant difference in tumor size between MR before and after treatment, however, there was a significant reduction in mean ADC in patients with progression (p = 0.02).

Conclusion: DW-MRI is a promising method for monitoring patients with choroidal melanoma; reduction in the mean ADC values between pre-treatment MRI and the first post-treatment MRI may be related to the lack of response to brachytherapy and increased risk of disease progression.

Quantitative imaging for radiotherapy purposes

Quantitative imaging biomarkers show great potential for use in radiotherapy. Quantitative images based on microscopic tissue properties and tissue function can be used to improve contouring of the radiotherapy targets. Furthermore, quantitative imaging biomarkers might be used to predict treatment response for several treatment regimens and hence be used as a tool for treatment stratification, either to determine which treatment modality is most promising or to determine patient-specific radiation dose. Finally, patient-specific radiation doses can be further tailored to a tissue/voxel specific radiation dose when quantitative imaging is used for dose painting. In this review, published standards, guidelines and recommendations on quantitative imaging assessment using CT, PET and MRI are discussed. Furthermore, critical issues regarding the use of quantitative imaging for radiation oncology purposes and resultant pending research topics are identified.

Predicting response to radiotherapy in tumors with PET/CT: when and how?

Radiotherapy is one of the main methods for tumor treatment, with the improved radiotherapy delivery technique to combat cancer, there is a growing interest for finding effective and feasible ways to predict tumor radiosensitivity. Based on a series of changes in metabolism, microvessel density, hypoxic microenvironment, and cytokines of tumors after radiotherapy, a variety of radiosensitivity detection methods have been studied. Among the detection methods, positron emission tomography-computed tomography (PET/CT) is a feasible tool for response evaluation following definitive radiotherapy for cancers with a high negative predictive value. The prognostic or predictive value of PET/CT is currently being studied widely. However, there are many unresolved issues, such as the optimal probe of PET/CT for radiosensitivity prediction, the selection of the most useful PET/CT parameters and their optimal cut-offs such as total lesion glycolysis (TLG), metabolic tumor volume (MTV) and standardized uptake value (SUV), and the optimal timing of PET/CT pre-treatment, during or following RT. Different radiosensitivity of tumors, modes of radiotherapy action and fraction scheduling may complicate the appropriate choice. In this study, we will discuss the diverse methods for evaluating radiosensitivity, and will also focus on the selection of the optimal probe, timing, cut-offs and parameters of PET/CT for evaluating the radiotherapy response.

Magnetic Resonance Imaging Assessment After Therapy in Prostate Cancer

Prostate cancer is the fifth leading cause of death worldwide. A variety of treatment options is available for localized prostate cancer and may range from active surveillance to focal therapy or whole gland treatment, that is, surgery or radiotherapy. Serum prostate-specific antigen levels are an important tool to monitor treatment success after whole gland treatment, unfortunately prostate-specific antigen is unreliable after focal therapy. Multiparametric magnetic resonance imaging of the prostate is rapidly gaining field in the management of prostate cancer and may play a crucial role in the evaluation of recurrent prostate cancer. This article will focus on postprocedural magnetic resonance imaging after different forms of local therapy in patients with prostate cancer.

Forecasting tumor and vasculature response dynamics to radiation therapy via image based mathematical modeling

BACKGROUND

Intra-and inter-tumoral heterogeneity in growth dynamics and vascularity influence tumor response to radiation therapy. Quantitative imaging techniques capture these dynamics non-invasively, and these data can initialize and constrain predictive models of response on an individual basis.

METHODS

We have developed a family of 10 biologically-based mathematical models describing the spatiotemporal dynamics of tumor volume fraction, blood volume fraction, and response to radiation therapy. To evaluate this family of models, rats (n = 13) with C6 gliomas were imaged with magnetic resonance imaging (MRI) three times before, and four times following a single fraction of 20 Gy or 40 Gy whole brain irradiation. The first five 3D time series data of tumor volume fraction, estimated from diffusion-weighted (DW-) MRI, and blood volume fraction, estimated from dynamic contrast-enhanced (DCE-) MRI, were used to calibrate tumor-specific model parameters. The most parsimonious and well calibrated of the 10 models, selected using the Akaike information criterion, was then utilized to predict future growth and response at the final two imaging time points. Model predictions were compared at the global level (percent error in tumor volume, and Dice coefficient) as well as at the local or voxel level (concordance correlation coefficient).

RESULT

The selected model resulted in < 12% error in tumor volume predictions, strong spatial agreement between predicted and observed tumor volumes (Dice coefficient > 0.74), and high level of agreement at the voxel level between the predicted and observed tumor volume fraction and blood volume fraction (concordance correlation coefficient > 0.77 and > 0.65, respectively).

CONCLUSIONS

This study demonstrates that serial quantitative MRI data collected before and following radiation therapy can be used to accurately predict tumor and vasculature response with a biologically-based mathematical model that is calibrated on an individual basis. To the best of our knowledge, this is the first effort to characterize the tumor and vasculature response to radiation therapy temporally and spatially using imaging-driven mathematical models.

Initial assessment of 3D magnetic resonance fingerprinting (MRF) towards quantitative brain imaging for radiation therapy

PURPOSE

Magnetic resonance fingerprinting (MRF) provides quantitative T1/T2 maps, enabling applications in clinical radiotherapy such as large-scale, multi-center clinical trials for longitudinal assessment of therapy response. We evaluated the feasibility of a quantitative three-dimensional-MRF (3D-MRF) towards its radiotherapy applications of primary brain tumors.

METHODS

A fast whole-brain 3D-MRF sequence initially developed for diagnostic radiology was optimized using flexible body coils, which is the typical MR imaging setup for radiotherapy treatment planning and for MR imaging (MRI)-guided treatment delivery. Optimization criteria included the accuracy and the precision of T1/T2 quantifications of polyvinylpyrrolidone (PVP) solutions, compared to those from the 3D-MRF using a 32-channel head coil. The accuracy of T1/T2 quantifications from the optimized MRF was first examined in healthy volunteers with two different coil setups. The intra- and inter-scanner variations of image intensity from the optimized sequence were quantified by longitudinal scans of the PVP solutions on two 3T scanners. Using a 3D-printed MRI geometry phantom, susceptibility-induced distortion with the optimized 3D-MRF was quantified as the Dice coefficient of phantom contours, compared to those from CT images. By introducing intentional head motion during 10% of the scan, the robustness of the optimized 3D-MRF towards motion was evaluated through visual inspection of motion artifacts and through quantitative analysis of image sharpness in brain MRF maps.

RESULTS

The optimized sequence acquired whole-brain T1, T2 and proton density maps and with a resolution of 1.2 × 1.2 × 3 mm³ in 10 min, similar to the total acquisition time of 3D T1- and T2-weighted images of the same resolution. In vivo T1 and T2 values of the white and gray matter were consistent with literature. The intra- and inter-scanner variability of the intensity-normalized MRF T1 was 1.0% ± 0.7% and 2.3% ± 1.0% respectively, in contrast to 5.3% ± 3.8% and 3.2% ± 1.6% from the normalized T1-weighted MRI. Repeatability and reproducibility of MRF T1 were independent of intensity normalization. Both phantom and human data demonstrated that the optimized 3D-MRF is more robust to subject motion and artifacts from subject-specific susceptibility difference. Compared to CT contours, the Dice coefficient of phantom contours from 3D-MRF was 0.93, improved from 0.87 from the T1-weighted MRI.

CONCLUSION

Compared to conventional MRI, the optimized 3D-MRF demonstrated improved repeatability across time points and reproducibility across scanners for better tissue quantification, as well as improved robustness to subject-specific susceptibility and motion artifacts under a typical MR imaging setup for radiotherapy. More importantly, quantitative MRF T1/T2 measurements lead to promising potentials towards longitudinal quantitative assessment of treatment response for better adaptive therapy and for large-scale, multi-center clinical trials.

Modern Radiation Therapy Planning and Delivery

Modern radiation therapy treatment planning and delivery is a complex process that relies on advanced imaging and computing technology as well as expertise from the medical team. The process begins with simulation imaging, in which three-dimensional computed tomography images (or magnetic resonance images in some cases) are used to characterize the patient anatomy. From there, the radiation oncologist delineates the relevant target/tumor volumes and normal tissue and communicates the goals for treatment planning. The planning process attempts to generate a radiation therapy treatment plan that will deliver a therapeutic dose of radiation to the tumor while sparing nearby normal tissue.

Basic concepts and applications of functional magnetic resonance imaging for radiotherapy of prostate cancer

Recently, the interest to integrate magnetic resonance imaging (MRI) in radiotherapy for prostate cancer has increased considerably. MRI can contribute in all steps of the radiotherapy workflow from diagnosis, staging, and target definition to treatment follow-up. Of particular interest is the ability of MRI to provide a wide range of functional measures. The complexity of MRI as an imaging modality combined with the growing interest of the application to prostate cancer radiotherapy, emphasize the need for dedicated education within the radiation oncology community. In this context, an overview of the most common as well as a few upcoming functional MR imaging techniques is presented: the basic methodology and measurement is described, the link between the functional measures and the underlying biology is established, and finally relevant applications of functional MRI useful for prostate cancer radiotherapy are given.

Dosimetric Impact of MRI Distortions: A Study on Head and Neck Cancers

PURPOSE

To evaluate the effect of magnetic resonance (MR) imaging (MRI) geometric distortions on head and neck radiation therapy treatment planning (RTP) for an MRI-only RTP. We also assessed the potential benefits of patient-specific shimming to reduce the magnitude of MR distortions for a 3-T scanner.

METHODS AND MATERIALS

Using an in-house Matlab algorithm, shimming within entire imaging volumes and user-defined regions of interest were simulated. We deformed 21 patient computed tomography (CT) images with MR distortion fields (gradient nonlinearity and patient-induced susceptibility effects) to create distorted CT (dCT) images using bandwidths of 122 and 488 Hz/mm at 3 T. Field parameters from volumetric modulated arc therapy plans initially optimized on dCT data sets were transferred to CT data to compute a new plan. Both plans were compared to determine the impact of distortions on dose distributions.

RESULTS

Shimming across entire patient volumes decreased the percentage of voxels with distortions of more than 2 mm from 15.4% to 2.0%. Using the user-defined region of interest (ROI) shimming strategy, (here the Planning target volume (PTV) was the chosen ROI volume) led to increased geometric for volumes outside the PTV, as such voxels within the spinal cord with geometric shifts above 2 mm increased from 11.5% to 32.3%. The worst phantom-measured residual system distortions after 3-dimensional gradient nonlinearity correction within a radial distance of 200 mm from the isocenter was 2.17 mm. For all patients, voxels with distortion shifts of more than 2 mm resulting from patient-induced susceptibility effects were 15.4% and 0.0% using bandwidths of 122 Hz/mm and 488 Hz/mm at 3 T. Dose differences between dCT and CT treatment plans in D₅₀ at the planning target volume were 0.4% ± 0.6% and 0.3% ± 0.5% at 122 and 488 Hz/mm, respectively.

CONCLUSIONS

The overall effect of MRI geometric distortions on data used for RTP was minimal. Shimming over entire imaging volumes decreased distortions, but user-defined subvolume shimming introduced significant errors in nearby organs and should probably be avoided.

Early assessment of acute kidney injury using targeted field of view diffusion-weighted imaging: An in vivo study

Acute kidney injury (AKI) is a common complication in various clinical settings. In recent years, AKI diagnostics have been investigated intensively showing the emerging need for early characterization of this disease. To verify whether targeted field-of-view diffusion-weighted imaging (tFOV-DWI) is feasible to significantly improve the performance of traditional full field-of-view diffusion-weighted imaging (fFOV-DWI) in the early assessment of AKI. 14 rabbits with unilateral AKI were induced by injection of microspheres under the guidance of digital subtraction angiography (DSA). All rabbits underwent tFOV-DWI and fFOV-DWI immediately after the surgery. Artifacts, distortion and lesion identification were graded by two experienced radiologists, and the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were measured. Apparent diffusion coefficient (ADC) maps were then derived. Blood samples were collected pre- and post-surgery and serum creatinine weres measured. Renal specimen and biopsy were performed as the reference standard. Student t-test was used to ascertain statistical significance between the above parameters for tFOV-DWI and fFOV-DWI. The interobserver agreement and ADC measurements agreement were assessed. A higher percentage of renal lesions (17 out of 19) were detected in tFOV-DWI compared with fFOV-DWI (14 out of 19). Significant differences were observed in ADC value for both techniques between the lesion regions and normal tissues (p < 0.001). Histological findings were inversely correlated with ADC values of tFOV-DWI (r = -0.97, P < 0.001 for cortex; r = -0.98, P < 0.001 for medulla) and fFOV-DWI sequences (r = -0.95, P < 0.001 for cortex; r = -0.98, P < 0.001 for medulla). Those tFOV-DW images rated by the radiologists exhibit superior performance in terms of all assessed measures (P < 0.05), and interobserver agreement was excellent (ICC, 0.78 to 0.92). Besides, the ADC values derived from tFOV-DWI had a satisfactory agreement with those estimated by fFOV-DWI. The animal study demonstrates that the tFOV-DWI strategy provided visually better image quality and lesion depiction than conventional fFOV-DWI for early assessment of AKI.

Potentials and challenges of diffusion-weighted magnetic resonance imaging in radiotherapy

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Discussion of DW imaging protocols and imaging setup.

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Discussion of mono- and bi-exponential models for quantitative parameter extraction.

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Review of recent publications investigating potential benefits of using DWI in RT, including detailed synoptic table.

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Detailed discussion of geometric and quantitative accuracy of DW imaging and DW-derived parameters.

Purpose

To review the potential and challenges of integrating diffusion weighted magnetic resonance imaging (DWI) into radiotherapy (RT).

Content

Details related to image acquisition of DWI for RT purposes are discussed, along with the challenges with respect to geometric accuracy and the robustness of quantitative parameter extraction. An overview of diffusion- and perfusion-related parameters derived from mono- and bi-exponential models is provided, and their role as potential RT biomarkers is discussed. Recent studies demonstrating potential of DWI in different tumor sites such as the head and neck, rectum, cervix, prostate, and brain, are reviewed in detail.

Conclusion

DWI has shown promise for RT outcome prediction, response assessment, as well as for tumor delineation and characterization in several cancer types. Geometric and quantification robustness is challenging and has to be addressed adequately. Evaluation in larger clinical trials with well designed imaging protocol and advanced analysis models is needed to develop the optimal strategy for integrating DWI in RT.

Diffusion-weighted MRI and ADC versus FET-PET and GdT1w-MRI for gross tumor volume (GTV) delineation in re-irradiation of recurrent glioblastoma

BACKGROUND AND PURPOSE

GTV definition for re-irradiation treatment planning in recurrent glioblastoma (rGBM) is usually based on contrast-enhanced MRI (GdT1w-MRI) and, for an increased specificity, on amino acid PET. Diffusion-weighted (DWI) MRI and ADC maps can reveal regions of high cellularity as surrogate for active tumor. The objective of this study was to compare the localization and quality of diffusion restriction foci (GTV-ADClow) with FET-PET (GTV-PET) and GdT1w-MRI (GTV-GdT1w-MRI).

MATERIAL AND METHODS

We prospectively evaluated 41 patients, who received a fractionated stereotactic re-irradiation for rGBM. GTV-PET was generated automatically (tumor-to-background ratio 1.7-1.8) and manually customized. GTV-ADClow was manually defined based on DWI data (3D diffusion gradients, b = 0, 1000 s/mm²) and parametric ADC maps. The localization of recurrence was correlated with initial GdT1w-MRI and PET data.

RESULTS

In 30/41 patients, DWI-MRI showed areas with restricted diffusion (mean ADC-value 0.74 ± 0.22 mm²/s). 66% of GTVs-ADClow were located outside the GdT1w-MRI volume and 76% outside increased FET uptake regions. Furthermore, GTVs-ADClow were only partially included in the high dose volume and received in mean 82% of the reference dose. An adjusted volume including GdT1w-MRI, PET-positive and restricted diffusion areas would imply a GTV increase of 48%. GTV-PET and GdT1w-MRI correlated better with the localization of re-recurrence in comparison to GTV-ADClow.

CONCLUSION

Unexpectedly, GTV-ADClow overlapped only partially with FET-PET and GdT1w-MRI in rGBM. Moreover, GTV-ADClow correlated poorly with later rGBM-recurrences. Seeing as a restricted diffusion is known to correlate with hypercellularity, this imaging discrepancy could only be further explained in histopathological studies.

Preclinical MRI: Studies of the irradiated brain

Radiation therapy (RT) plays a central role in the treatment of primary brain tumors. However, despite recent advances in RT treatment, local recurrences following therapy remain common. Radiation necrosis (RN) is a severe, late complication of radiation therapy in the brain. RN is a serious clinical problem often associated with devastating neurologic complications. Therapeutic strategies, including neuroprotectants, have been described, but have not been widely translated in routine clinical use. We have developed a mouse model that recapitulates all of the major pathologic features of late-onset RN for the purposes of characterizing the basic pathogenesis of RN, identifying non-invasive (imaging) biomarkers of RN that might allow for the radiologic discernment of tumor and RN, systematic testing of tumor and RN therapeutics, and exploring the complex interplay between RN pathogenesis and tumor recurrence. Herein, we describe the fundamental clinical challenges associated with RN and the progress made towards addressing these challenges by combining our novel mouse model of late-onset RN and magnetic resonance imaging (MRI). MRI techniques discussed include conventional T1- and T2-weighted imaging, diffusion-weighted imaging, magnetization transfer, and measures of tissue oxygenation. Studies of RN mitigation and neuroprotection are described, including the use of anti-VEGF antibodies, and inhibitors of GSK-3β, HIF-1α, and CXCR4. We conclude with some future perspectives on the irradiated brain and the study and treatment of recurrent tumor growing in an irradiated tumor microenvironment.

Evaluating the repeatability and set-up sensitivity of a large field of view distortion phantom and software for magnetic resonance-only radiotherapy

BACKGROUND AND PURPOSE

Magnetic Resonance (MR)-only radiotherapy requires geometrically accurate MR images over the full scanner Field of View (FoV). This study aimed to investigate the repeatability of distortion measurements made using a commercial large FoV phantom and analysis software and the sensitivity of these measurements to small set-up errors.

MATERIALS AND METHODS

Geometric distortion was measured using a commercial phantom and software with 2D and 3D acquisition sequences on three different MR scanners. Two sets of repeatability measurements were made: three scans acquired without moving the phantom between scans (single set-up) and five scans acquired with the phantom re-set up in between each scan (repeated set-up). The set-up sensitivity was assessed by scanning the phantom with an intentional 1 mm lateral offset and independently an intentional 1° rotation.

RESULTS

The mean standard deviation of distortion for all phantom markers for the repeated set-up scans was < 0.4 mm for all scanners and sequences. For the 1 mm lateral offset scan 90 % of the markers agreed within two standard deviations of the mean of the repeated set-up scan (median of all scanners and sequences, range 78%-93%). For the 1° rotation scan, 80% of markers agreed within two standard deviations of the mean (range 69%-93%).

CONCLUSIONS

Geometric distortion measurements using a commercial phantom and associated software appear repeatable, although with some sensitivity to set-up errors. This suggests the phantom and software are appropriate for commissioning a MR-only radiotherapy workflow.

Biological imaging for individualized therapy in radiation oncology: part I physical and technical aspects

Recently, there has been an increase in the imaging modalities available for radiotherapy planning and radiotherapy prognostic outcome: dual energy computed tomography (CT), dynamic contrast enhanced CT, dynamic contrast enhanced magnetic resonance imaging (MRI), diffusion-weighted MRI, positron emission tomography-CT, dynamic contrast enhanced ultrasound, MR spectroscopy and positron emission tomography-MR. These techniques enable more precise gross tumor volume definition than CT alone and moreover allow subvolumes within the gross tumor volume to be defined which may be given a boost dose or an individual voxelized dose prescription may be derived. With increased plan complexity care must be taken to immobilize the patient in an accurate and reproducible manner. Moreover the physical and technical limitations of the entire treatment planning chain need to be well characterized and understood, interdisciplinary collaboration ameliorated (physicians and physicists within nuclear medicine, radiology and radiotherapy) and image protocols standardized.

MRI-only treatment planning: benefits and challenges

Over the past decade, the application of magnetic resonance imaging (MRI) has increased, and there is growing evidence to suggest that improvements in the accuracy of target delineation in MRI-guided radiation therapy may improve clinical outcomes in a variety of cancer types. However, some considerations should be recognized including patient motion during image acquisition and geometric accuracy of images. Moreover, MR-compatible immobilization devices need to be used when acquiring images in the treatment position while minimizing patient motion during the scan time. Finally, synthetic CT images (i.e. electron density maps) and digitally reconstructed radiograph images should be generated from MRI images for dose calculation and image guidance prior to treatment. A short review of the concepts and techniques that have been developed for implementation of MRI-only workflows in radiation therapy is provided in this document.

An adaptive Fuzzy C-means method utilizing neighboring information for breast tumor segmentation in ultrasound images

PURPOSE

Ultrasound (US) imaging has been widely used in breast tumor diagnosis and treatment intervention. Automatic delineation of the tumor is a crucial first step, especially for the computer-aided diagnosis (CAD) and US-guided breast procedure. However, the intrinsic properties of US images such as low contrast and blurry boundaries pose challenges to the automatic segmentation of the breast tumor. Therefore, the purpose of this study is to propose a segmentation algorithm that can contour the breast tumor in US images.

METHODS

To utilize the neighbor information of each pixel, a Hausdorff distance based fuzzy c-means (FCM) method was adopted. The size of the neighbor region was adaptively updated by comparing the mutual information between them. The objective function of the clustering process was updated by a combination of Euclid distance and the adaptively calculated Hausdorff distance. Segmentation results were evaluated by comparing with three experts' manual segmentations. The results were also compared with a kernel-induced distance based FCM with spatial constraints, the method without adaptive region selection, and conventional FCM.

RESULTS

Results from segmenting 30 patient images showed the adaptive method had a value of sensitivity, specificity, Jaccard similarity, and Dice coefficient of 93.60 ± 5.33%, 97.83 ± 2.17%, 86.38 ± 5.80%, and 92.58 ± 3.68%, respectively. The region-based metrics of average symmetric surface distance (ASSD), root mean square symmetric distance (RMSD), and maximum symmetric surface distance (MSSD) were 0.03 ± 0.04 mm, 0.04 ± 0.03 mm, and 1.18 ± 1.01 mm, respectively. All the metrics except sensitivity were better than that of the non-adaptive algorithm and the conventional FCM. Only three region-based metrics were better than that of the kernel-induced distance based FCM with spatial constraints.

CONCLUSION

Inclusion of the pixel neighbor information adaptively in segmenting US images improved the segmentation performance. The results demonstrate the potential application of the method in breast tumor CAD and other US-guided procedures.

Multiparametric Magnetic Resonance Imaging of Recurrent Prostate Cancer

There is growing consensus that multiparametric magnetic resonance imaging (mpMRI) is an effective modality in the detection of locally recurrent prostate cancer after prostatectomy and radiation therapy. The emergence of magnetic resonance (MR)-guided focal therapies, such as cryoablation, high-intensity focused ultrasound, and laser ablation, have made the use of mpMRI even more important, as the normal anatomy is inevitably altered and the detection of recurrence is made more difficult. The aim of this article is to review the utility of mpMRI in detecting recurrent prostate cancer in patients following radical prostatectomy, radiation therapy, and focal therapy and to discuss expected post-treatment mpMRI findings, the varied appearance of recurrent tumors, and their mimics.