Repeated diffusion MRI reveals earliest time point for stratification of radiotherapy response in brain metastases

Intravoxel incoherent motion magnetic resonance imaging to assess early tumor response to radiation therapy: Review and future directions

Early prediction of radiation response by imaging is a dynamic field of research and it can be obtained using a variety of noninvasive magnetic resonance imaging methods. Recently, intravoxel incoherent motion (IVIM) has gained interest in cancer imaging. IVIM carries both diffusion and perfusion information, making it a promising tool to assess tumor response. Here, we briefly introduced the basics of IVIM, reviewed existing studies of IVIM in various type of tumors during radiotherapy in order to show whether IVIM is a useful technique for an early assessment of radiation response. 31/40 studies reported an increase of IVIM parameters during radiotherapy compared to baseline. In 27 studies, this increase was higher in patients with good response to radiotherapy. Future directions including implementation of IVIM on MR-Linac and its limitation are discussed. Obtaining new radiologic biomarkers of radiotherapy response could open the way for a more personalized, biology-guided radiation therapy.

Validation of echo planar imaging based diffusion-weighted magnetic resonance imaging on a 0.35 T MR-Linac

Background and Purpose

The feasibility of acquiring diffusion-weighted imaging (DWI) images on an MR-Linac for quantitative response assessment during radiotherapy was explored. DWI data obtained with a Spin Echo Echo Planar Imaging sequence adapted for a 0.35 T MR-Linac were examined and compared with DWI data from a conventional 3 T scanner.

Materials and Methods

Apparent diffusion coefficient (ADC) measurements and a distortion correction technique were investigated using DWI-calibrated phantoms and in the brains of seven volunteers. All DWI utilized two phase-encoding directions for distortion correction and off-resonance field estimation. ADC maps in the brain were analyzed for automatically segmented normal tissues.

Results

Phantom ADC measurements on the MR-Linac were within a 3 % margin of those recorded by the 3 T scanner. The maximum distortion observed in the phantom was 2.0 mm prior to correction and 1.1 mm post-correction on the MR-Linac, compared to 6.0 mm before correction and 3.6 mm after correction at 3 T. In vivo, the average ADC values for gray and white matter exhibited variations of 14 % and 4 %, respectively, for different selections of b-values on the MR-Linac. Distortions in brain images before correction, estimated through the off-resonance field, reached 2.7 mm on the MR-Linac and 12 mm at 3 T.

Conclusion

Accurate ADC measurements are achievable on a 0.35 T MR-Linac, both in phantom and in vivo. The selection of b-values significantly influences ADC values in vivo. DWI on the MR-Linac demonstrated lower distortion levels, with a maximum distortion reduced to 1.1 mm after correction.

Reproducibility of diffusion-weighted magnetic resonance imaging in head and neck cancer assessed on a 1.5 T MR-Linac and comparison to parallel measurements on a 3 T diagnostic scanner

BACKGROUND AND PURPOSE

Before quantitative imaging biomarkers (QIBs) acquired with magnetic resonance imaging (MRI) can be used for interventional trials in radiotherapy (RT), technical validation of these QIBs is necessary. The aim of this study was to assess the reproducibility of apparent diffusion coefficient (ADC) values, derived from diffusion-weighted (DW) MRI, in head and neck cancer using a 1.5 T MR-Linac (MRL) by comparison to a 3 T diagnostic scanner (DS).

MATERIAL AND METHODS

DW-MRIs were acquired on MRL and DS for 15 head and neck cancer patients before RT and in week 2 and rigidly registered to the planning computed tomography. Mean ADC values were calculated for submandibular (SG) and parotid (PG) glands as well as target volumes (TV, gross tumor volume and lymph nodes), which were delineated based on computed tomography. Mean absolute ADC differences as well as within-subject coefficient of variation (wCV) and intraclass correlation coefficients (ICCs) were calculated for all volumes of interest.

RESULTS

A total of 23 datasets were analyzed. Mean ADC difference (DS-MRL) for SG, PG and TV resulted in 142, 254 and 93·10-6 mm2/s. wCVs/ICCs, comparing MRL and DS, were determined as 13.7 %/0.26, 24.4 %/0.23 and 16.1 %/0.73 for SG, PG and TV, respectively.

CONCLUSION

ADC values, measured on the 1.5 T MRL, showed reasonable reproducibility with an ADC underestimation in contrast to the DS. This ADC shift must be validated in further experiments and considered for future translation of QIB candidates from DS to MRL for response adaptive RT.

Quantitative MRI on MR-Linacs: Towards Biological Image-Guided Adaptive Radiotherapy

Recognizing the potential of quantitative imaging biomarkers (QIBs) in radiotherapy, many studies have investigated the prognostic value of quantitative MRI (qMRI). With the introduction of MRI-guided radiotherapy systems, the practical challenges of repeated imaging have been substantially reduced. Since patients are treated inside an MRI scanner, acquisition of qMRI can be done during each fraction with limited or no prolongation of the fraction duration. In this review paper, we identify the steps that need been taken to move from MR as an imaging technique to a useful biomarker for MRI-guided radiotherapy (MRgRT).

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.

Soy lecithin: A beneficial substance for adjusting the ADC in aqueous solutions to the values of biological tissues

PURPOSE

To test soy lecithin as a substance added to water for the construction of MRI phantoms with tissue-like diffusion coefficients. The performance of soy lecithin was assessed for the useable range of adjustable ADC values, the degree of non-Gaussian diffusion, simultaneous effects on relaxation times, and spectral signal properties.

METHODS

Aqueous soy lecithin solutions of different concentrations (0%, 0.5%, 1%, 2%, 3% …, 10%) and soy lecithin-agar gels were prepared and examined on a 3 Tesla clinical scanner at 18.5° ± 0.5°C. Echoplanar sequences (b values: 0-1000/3000 s/mm² ) were applied for ADC measurements. Quantitative relaxometry and MRS were performed for assessment of T₁ , T₂ , and detectable spectral components.

RESULTS

The presence of soy lecithin significantly restricts the diffusion of water molecules and mimics the nearly Gaussian nature of diffusion observed in tissue (for b values <1000 s/mm² ). ADC values ranged from 2.02 × 10^-3  mm² /s to 0.48 × 10^-3  mm² /s and cover the entire physiological range reported on biological tissue. Measured T₁ /T₂ values of pure lecithin solutions varied from 2685/2013 to 668/133 ms with increasing concentration. No characteristic signals of soy lecithin were observed in the MR spectrum. The addition of agar to the soy lecithin solutions allowed T₂ values to be well adjusted to typical values found in parenchymal tissue without affecting the soy lecithin-controlled ADC value.

CONCLUSION

Soy lecithin is a promising substance for the construction of diffusion phantoms with tissue-like ADC values. It provides several advantages over previously proposed substances, in particular a wide range of adjustable ADC values, the lack of additional ¹ H-signals, and the possibility to adjust ADC and T₂ values (by adding agar) almost independently of each other.

Can Apparent Diffusion Coefficient (ADC) maps replace Diffusion Tensor Imaging (DTI) maps to predict the volumetric response of meningiomas to Gamma Knife Radiosurgery?

PURPOSE

Noninvasive methods are desired to predict the treatment response to Stereotactic Radiosurgery (SRS) to improve individual tumor management. In a previous study, we demonstrated that Diffusion Tensor Imaging (DTI)-derived parameter maps significantly correlate to SRS response. This study aimed to analyze and compare the predictive value of intratumoral ADC and DTI parameters in patients with meningiomas undergoing radiosurgery.

METHODS

MR images of 70 patients treated with Gamma Knife SRS for WHO grade I meningiomas were retrospectively reviewed. MR acquisition included pre- and post-treatment DWI and DTI sequences, and subtractions were calculated to assess for radiation-induced changes in the parameter values.

RESULTS

After a mean follow-up period (FUP) of 52.7 months, 69 of 70 meningiomas were controlled, with a mean volume reduction of 34.9%. Whereas fractional anisotropy (FA) values of the initial exam showed the highest correlation to tumor volume change at the last FU (CC = - 0.607), followed by the differences between first and second FU values of FA (CC = - 0.404) and the first longitudinal diffusivity (LD) value (CC = - 0.375), the correlation coefficients of all ADC values were comparably low. Nevertheless, all these correlations, except for ADC measured at the first follow-up, reached significance.

CONCLUSION

For the first time, the prognostic value of ADC maps measured in meningiomas before and at first follow-up after Gamma Knife SRS, was compared to simultaneously acquired DTI parameter maps. Quantities assessed from ADC maps present significant correlations to the volumetric meningioma response but are less effective than correlations with DTI parameters.

Decomposition-based framework for tumor classification and prediction of treatment response from longitudinal MRI

Objective.In the field of radiation oncology, the benefit of MRI goes beyond that of providing high soft-tissue contrast images for staging and treatment planning. With the recent clinical introduction of hybrid MRI linear accelerators it has become feasible to map physiological parameters describing diffusion, perfusion, and relaxation during the entire course of radiotherapy, for example. However, advanced data analysis tools are required for extracting qualified prognostic and predictive imaging biomarkers from longitudinal MRI data. In this study, we propose a new prediction framework tailored to exploit temporal dynamics of tissue features from repeated measurements. We demonstrate the framework using a newly developed decomposition method for tumor characterization.Approach.Two previously published MRI datasets with multiple measurements during and after radiotherapy, were used for development and testing:T₂-weighted multi-echo images obtained for two mouse models of pancreatic cancer, and diffusion-weighted images for patients with brain metastases. Initially, the data was decomposed using the novel monotonous slope non-negative matrix factorization (msNMF) tailored for MR data. The following processing consisted of a tumor heterogeneity assessment using descriptive statistical measures, robust linear modelling to capture temporal changes of these, and finally logistic regression analysis for stratification of tumors and volumetric outcome.Main Results.The framework was able to classify the two pancreatic tumor types with an area under curve (AUC) of 0.999,P< 0.001 and predict the tumor volume change with a correlation coefficient of 0.513,P= 0.034. A classification of the human brain metastases into responders and non-responders resulted in an AUC of 0.74,P= 0.065.Significance.A general data processing framework for analyses of longitudinal MRI data has been developed and applications were demonstrated by classification of tumor type and prediction of radiotherapy response. Further, as part of the assessment, the merits of msNMF for tumor tissue decomposition were demonstrated.

The critical components for effective adaptive radiotherapy in patients with unresectable non-small-cell lung cancer: who, when and how

Adaptive radiotherapy (ART) is a new radiotherapy technology based on image-guided radiation therapy technology, used to avoid radiation overexposure to residual tumors and the surrounding normal tissues. Tumors undergoing the same radiation doses and modes can occur unequal shrinkage due to the variation of response times to radiation doses in different patients. To perform ART effectively, eligible patients with a high probability of benefits from ART need to be identified. Confirming the precise timetable for ART in every patient is another urgent problem to be resolved. Moreover, the outcomes of ART are different depending on the various image guidance used. This review discusses 'who, when and how' as the three key factors involved in the most effective implementation for the management of ART.

Clinical utility of a 1.5 T magnetic resonance imaging-guided linear accelerator during conventionally fractionated and hypofractionated prostate cancer radiotherapy

Purpose

To report our initial experience with 1.5 T magnetic resonance imaging (MRI) linear accelerator (LINAC) in prostate cancer radiotherapy in terms of its use in a radiation oncology clinic.

Methods

The medical records of 14 prostate cancer patients treated with MRI-guided radiotherapy were retrospectively evaluated. The fraction time, adapt-to-position (ATP):adapt-to-shape (ATS) usage rate, machine-associated treatment interruption rate, median gamma pass rate, the percentage of planning target volume receiving at least 95% of the prescription dose coverage value of each ATS fraction, the effect of the learning curve on the fraction time and radiation-related acute gastrointestinal and genitourinary toxicities were evaluated.

Results

Fourteen patients have completed their treatment receiving a total of 375 fractions. Six patients (42%) were treated with the moderately hypofractionated regimen, five patients (36%) with conventionally fractionated, and three patients (22%) with the ultra-hypofractionated radiotherapy regimens. The ATP : ATS usage ratio was 3:372. The median fraction time was 46 min (range, 24-81 min). For the 3%/3 mm criterion, median gamma pass rate was 99.4% (range, 94.6–100%). Machine-related treatment interruptions were observed in 11 (2.9%) of 375 fractions, but this interruption rate decreased from 4.1% to 0.8%, after an upgrade. Three patients (22%) had gastrointestinal and five patients (36%) had genitourinary toxicity. No ≥grade 3 toxicity was observed.

Conclusion

1.5 T MRI-LINAC device could be used as a conventional LINAC device, when the conditions of the radiotherapy center are appropriate. MRI-guided prostate radiotherapy is safe and feasible, and high-quality studies with a larger number of patients and long-term results are needed to better evaluate this new technology.

The radiomic-clinical model using the SHAP method for assessing the treatment response of whole-brain radiotherapy: a multicentric study

OBJECTIVE

To develop and validate a pretreatment magnetic resonance imaging (MRI)-based radiomic-clinical model to assess the treatment response of whole-brain radiotherapy (WBRT) by using SHapley Additive exPlanations (SHAP), which is derived from game theory, and can explain the output of different machine learning models.

METHODS

We retrospectively enrolled 228 patients with brain metastases from two medical centers (184 in the training cohort and 44 in the validation cohort). Treatment responses of patients were categorized as a non-responding group vs. a responding group according to the Response Assessment in Neuro-Oncology Brain Metastases (RANO-BM) criteria. For each tumor, 960 features were extracted from the MRI sequence. The least absolute shrinkage and selection operator (LASSO) was used for feature selection. A support vector machine (SVM) model incorporating clinical factors and radiomic features wase used to construct the radiomic-clinical model. SHAP method explained the SVM model by prioritizing the importance of features, in terms of assessment contribution.

RESULTS

Three radiomic features and three clinical factors were identified to build the model. Radiomic-clinical model yielded AUCs of 0.928 (95%CI 0.901-0.949) and 0.851 (95%CI 0.816-0.886) for assessing the treatment response in the training cohort and validation cohort, respectively. SHAP summary plot illustrated the feature's value affected the feature's impact attributed to model, and SHAP force plot showed the integration of features' impact attributed to individual response.

CONCLUSION

The radiomic-clinical model with the SHAP method can be useful for assessing the treatment response of WBRT and may assist clinicians in directing personalized WBRT strategies in an understandable manner.

KEY POINTS

• Radiomic-clinical model can be useful for assessing the treatment response of WBRT. • SHAP could explain and visualize radiomic-clinical machine learning model in a clinician-friendly way.

Accuracy and precision of apparent diffusion coefficient measurements on a 1.5 T MR-Linac in central nervous system tumour patients

BACKGROUND AND PURPOSE

MRI linear accelerators (MR-Linacs) may allow treatment adaptation to be guided by quantitative MRI including diffusion-weighted imaging (DWI). The aim of this study was to evaluate the accuracy and precision of apparent diffusion coefficient (ADC) measurements from DWI on a 1.5 T MR-Linac in patients with central nervous system (CNS) tumours through comparison with a diagnostic scanner.

MATERIALS AND METHODS

CNS patients were treated using a 1.5 T Elekta Unity MR-Linac. DWI was acquired during MR-Linac treatment and on a Philips Ingenia 1.5 T. The agreement between the two scanners on median ADC over the gross tumour/clinical target volumes (GTV/CTV) and in brain regions (white/grey matter, cerebrospinal fluid (CSF)) was computed. Repeated scans were used to estimate ADC repeatability. Daily changes in ADC over the GTV of high-grade gliomas were characterized from MR-Linac scans.

RESULTS

DWI from 59 patients was analyzed. MR-Linac ADC measurements showed a small bias relative to Ingenia measurements in white matter, grey matter, GTV, and CTV (bias: -0.05 ± 0.03, -0.08 ± 0.05, -0.1 ± 0.1, -0.08 ± 0.07 μm²/ms). ADC differed substantially in CSF (bias: -0.5 ± 0.3 μm²/ms). The repeatability of MR-Linac ADC over white/grey matter was similar to previous reports (coefficients of variation for median ADC: 1.4%/1.8%). MR-Linac ADC changes in the GTV were detectable.

CONCLUSIONS

It is possible to obtain ADC measurements in the brain on a 1.5 T MR-Linac that are comparable to those of diagnostic-quality scanners. This technical validation study adds to the foundation for future studies that will correlate brain tumour ADC with clinical outcomes.

Daily Intravoxel Incoherent Motion (IVIM) In Prostate Cancer Patients During MR-Guided Radiotherapy-A Multicenter Study

PURPOSE

Daily quantitative MR imaging during radiotherapy of cancer patients has become feasible with MRI systems integrated with linear accelerators (MR-linacs). Quantitative images could be used for treatment response monitoring. With intravoxel incoherent motion (IVIM) MRI, it is possible to acquire perfusion information without the use of contrast agents. In this multicenter study, daily IVIM measurements were performed in prostate cancer patients to identify changes that potentially reflect response to treatment.

MATERIALS AND METHODS

Forty-three patients were included, treated with 20 fractions of 3 Gy on a 1.5 T MR-linac. IVIM measurements were performed on each treatment day. The diffusion coefficient (D), perfusion fraction (f), and pseudo-diffusion coefficient (D*) were calculated based on the median signal intensities in the non-cancerous prostate and the tumor. Repeatability coefficients (RCs) were determined based on the first two treatment fractions. Separate linear mixed-effects models were constructed for the three IVIM parameters.

RESULTS

In total, 726 fractions were analyzed. Pre-treatment average values, measured on the first fraction before irradiation, were 1.46 × 10-3 mm2/s, 0.086, and 28.7 × 10-3 mm2/s in the non-cancerous prostate and 1.19 × 10-3 mm2/s, 0.088, and 28.9 × 10-3 mm2/s in the tumor, for D, f, and D*, respectively. The repeatability coefficients for D, f, and D* in the non-cancerous prostate were 0.09 × 10-3 mm2/s, 0.05, and 15.3 × 10-3 mm2/s. In the tumor, these values were 0.44 × 10-3 mm2/s, 0.16, and 76.4 × 10-3 mm2/s. The mixed effects analysis showed an increase in D of the tumors over the course of treatment, while remaining stable in the non-cancerous prostate. The f and D* increased in both the non-cancerous prostate and tumor.

CONCLUSIONS

It is feasible to perform daily IVIM measurements on an MR-linac system. Although the repeatability coefficients were high, changes in IVIM perfusion parameters were measured on a group level, indicating that IVIM has potential for measuring treatment response.

Technical Challenges of Real-Time Adaptive MR-Guided Radiotherapy

In the past few years, radiotherapy (RT) has experienced a major technological innovation with the development of hybrid machines combining magnetic resonance (MR) imaging and linear accelerators. This new technology for MR-guided cancer treatment has the potential to revolutionize the field of adaptive RT due to the opportunity to provide high-resolution, real-time MR imaging before and during treatment application. However, from a technical point of view, several challenges remain which need to be tackled to ensure safe and robust real-time adaptive MR-guided RT delivery. In this manuscript, several technical challenges to MR-guided RT are discussed. Starting with magnetic field strength tradeoffs, the potential and limitations for purely MR-based RT workflows are discussed. Furthermore, the current status of real-time 3D MR imaging and its potential for real-time RT are summarized. Finally, the potential of quantitative MR imaging for future biological RT adaptation is highlighted.

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.

ADC measurements on the Unity MR-linac - A recommendation on behalf of the Elekta Unity MR-linac consortium

BACKGROUND AND PURPOSE

Diffusion-weighted imaging (DWI) for treatment response monitoring is feasible on hybrid magnetic resonance linear accelerator (MR-linac) systems. The MRI scanner of the Elekta Unity system has an adjusted design compared to diagnostic scanners. We investigated its impact on measuring the DWI-derived apparent diffusion coefficient (ADC) regarding three aspects: the choice of b-values, the spatial variation of the ADC, and scanning during radiation treatment. The aim of this study is to give recommendations for accurate ADC measurements on Unity systems.

MATERIALS AND METHODS

Signal-to-noise ratio (SNR) measurements with increasing b-values were done to determine the highest bvalue that can be measured reliably. The spatial variation of the ADC was assessed on six Unity systems with a cylindrical phantom of 40 cm diameter. The influence of gantry rotation and irradiation was investigated by acquiring DWI images before and during treatment of 11 prostate cancer patients.

RESULTS

On the Unity system, a maximum b-value of 500 s/mm2 should be used for ADC quantification, as a trade-off between SNR and diffusion weighting. Accurate ADC values were obtained within 7 cm from the iso-center, while outside this region ADC values deviated more than 5%. The ADC was not influenced by the rotating linac or irradiation during treatment.

CONCLUSION

We provide Unity system specific recommendations for measuring the ADC. This will increase the consistency of ADC values acquired in different centers on the Unity system, enabling large cohort studies for biomarker discovery and treatment response monitoring.

The Use of Treatment Response Assessment Maps in Discriminating Between Radiation Effect and Persistent Tumoral Lesion in Metastatic Brain Tumors Treated with Gamma Knife Radiosurgery

BACKGROUND

Traditional imaging modalities are not useful in the follow-up of irradiated metastatic brain tumors, because radiation can change imaging characteristics. We aimed to assess the ability of treatment response assessment maps (TRAMs) calculated from delayed-contrast magnetic resonance imaging (MRI) in differentiation between radiation effect and persistent tumoral tissue.

METHODS

TRAMs were calculated by subtracting three-dimensional T1 MRIs acquired 5 minutes after contrast injection from the images acquired 60-105 minutes later. Red areas were regarded as radiation effect and blue areas as persistent tumoral lesion. Thirty-seven patients with 130 metastatic brain tumors who were treated with Gamma Knife radiosurgery and who underwent TRAMs perfusion-weighted MRI were enrolled in this retrospective study.

RESULTS

The median age was 58 years and the most common primary diagnosis was lung cancer (n = 21). The median follow-up period of patients was 12 months. The overall local control rate was 100% at 1 year and 98.9% at 2 years. The median progression-free survival was 12 months. The mean overall survival was 27.3 months. The radiologic and clinical follow-up showed a clinicoradiologic diagnosis of a persistent tumoral lesion in 3 tumors (2.3%) and radiation effect in 127 tumors (97.7%). There was a fair agreement between clinicoradiologic diagnosis and TRAMs analysis (κ = 0.380). The sensitivity and positive predictive value of TRAMs in diagnosing radiation effect were 96.06% and 99.2%, respectively. TRAMs showed comparable results to perfusion-weighted MRI, with a diagnostic odds ratio of 27.4 versus 20.7, respectively.

CONCLUSIONS

The presented results show the ability of TRAMs in differentiating radiation effect and persistent tumoral lesions.

Quantitative magnetic resonance imaging on hybrid magnetic resonance linear accelerators: Perspective on technical and clinical validation

Many preclinical and clinical observations support that functional magnetic resonance imaging (MRI), such as diffusion weighted (DW) and dynamic contrast enhanced (DCE) MRI, might have a predictive value for radiotherapy. The aim of this review was to assess the current status of quantitative MRI on hybrid MR-Linacs. In a literature research, four publications were identified, investigating technical feasibility, accuracy, repeatability and reproducibility of DW and DCE-MRI in phantoms and first patients. Accuracy and short term repeatability was < 5% for DW-MRI in current MR-Linac systems. Consequently, quantitative imaging providing accurate and reproducible functional information seems possible in MR-Linacs.

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.

Tyrosine Kinase Inhibitor Therapy for Brain Metastases in Non-Small-Cell Lung Cancer: A Primer for Radiologists

Treatment options for patients who develop brain metastases secondary to non-small-cell lung cancer have rapidly expanded in recent years. As a key adjunct to surgical and radiation therapy options, systemic therapies are now a critical component of the oncologic management of metastatic CNS disease in many patients with non-small-cell lung cancer. The aim of this review article was to provide a guide for radiologists, outlining the role of systemic therapies in metastatic non-small-cell lung cancer, with a focus on tyrosine kinase inhibitors. The critical role of the blood-brain barrier in the development of systemic therapies will be described. The final sections of this review will provide an overview of current imaging-based guidelines for therapy response. The utility of the Response Assessment in Neuro-Oncology criteria will be discussed, with a focus on how to use the response criteria in the assessment of patients treated with systemic and traditional therapies.

Diffusion MRI outlined viable tumour volume beats GTV in intra-treatment stratification of outcome

BACKGROUND AND PURPOSE

In radiotherapy, treatment response is generally evaluated many weeks after end of the treatment course. If the treatment outcome could be predicted during radiotherapy better tumour control could be achieved through timely adaptation of the treatment strategy. In this study intra-treatment change based on the diffusion MRI outlined viable tumour volume (VTV) was assessed and compared to the standard GTV to study their outcome prediction capacity.

MATERIALS AND METHODS

Thirty-eight brain metastases from twenty-one cancer patients were analysed in this prospective trial. Diffusion and structural MRI was acquired on a 1 T machine before, during, and at follow-up 2-3 months after radiotherapy. The VTV was defined as a region with high cellularity using high b-value diffusion MRI scans. Further, the diffusivity of the VTV was derived as the apparent diffusion coefficient (ADC). Treatment outcome was determined using RECIST defined bounds in the T1W MRI follow-up scan. Longitudinal statistical analysis was performed using a linear mixed effect model.

RESULTS

The GTV declined in both responding and non-responding (significantly) tumours with inseparable rates during radiotherapy. The VTV volume fraction reduced significantly in the responding tumours only. The ADC of the VTV increased significantly in responding metastases whereas it decreased in non-responding metastases. Furthermore, no association between baseline tumour size or primary disease and outcome was observed.

CONCLUSION

GTV size change during radiotherapy is not a reliable predictor of outcome in brain metastases. On the other hand, change in the volume fraction of VTV and diffusivity of VTV shows ability to stratify treatment outcome.

First clinical experiences with a high field 1.5 T MR linac

Purpose: A 1.5 T MR Linac (MRL) has recently become available. MRL treatment workflows (WF) include online plan adaptation based on daily MR images (MRI). This study reports initial clinical experiences after five months of use in terms of patient compliance, cases, WF timings, and dosimetric accuracy. Method and materials: Two different WF were used dependent on the clinical situation of the day; Adapt To Position WF (ATP) where the reference plan position is adjusted rigidly to match the position of the targets and the OARs, and Adapt To Shape WF (ATS), where a new plan is created to match the anatomy of the day, using deformable image registration. Both WFs included three 3D MRI scans for plan adaptation, verification before beam on, and validation during IMRT delivery. Patient compliance and WF timings were recorded. Accuracy in dose delivery was assessed using a cylindrical diode phantom. Results: Nineteen patients have completed their treatment receiving a total of 176 fractions. Cases vary from prostate treatments (60Gy/20F) to SBRT treatments of lymph nodes (45 Gy/3F) and castration by ovarian irradiation (15 Gy/3F). The median session time (patient in to patient out) for 127 ATPs was 26 (21-78) min, four fractions lasted more than 45 min due to additional plan adaptation. For the 49 ATSs a median time of 12 (1-24) min was used for contouring resulting in a total median session time of 42 (29-91) min. Three SBRT fractions lasted more than an hour. The time on the MRL couch was well tolerated by the patients. The median gamma pass rate (2 mm,2% global max) for the adapted plans was 99.2 (93.4-100)%, showing good agreement between planned and delivered dose. Conclusion: MRL treatments, including daily MRIs, plan adaptation, and accurate dose delivery, are possible within a clinically acceptable timeframe and well tolerated by the patients.

The Molecular Effects of Ionizing Radiations on Brain Cells: Radiation Necrosis vs. Tumor Recurrence

The central nervous system (CNS) is generally resistant to the effects of radiation, but higher doses, such as those related to radiation therapy, can cause both acute and long-term brain damage. The most important results is a decline in cognitive function that follows, in most cases, cerebral radionecrosis. The essence of radio-induced brain damage is multifactorial, being linked to total administered dose, dose per fraction, tumor volume, duration of irradiation and dependent on complex interactions between multiple brain cell types. Cognitive impairment has been described following brain radiotherapy, but the mechanisms leading to this adverse event remain mostly unknown. In the event of a brain tumor, on follow-up radiological imaging often cannot clearly distinguish between recurrence and necrosis, while, especially in patients that underwent radiation therapy (RT) post-surgery, positron emission tomography (PET) functional imaging, is able to differentiate tumors from reactive phenomena. More recently, efforts have been done to combine both morphological and functional data in a single exam and acquisition thanks to the co-registration of PET/MRI. The future of PET imaging to differentiate between radionecrosis and tumor recurrence could be represented by a third-generation PET tracer already used to reveal the spatial extent of brain inflammation. The aim of the following review is to analyze the effect of ionizing radiations on CNS with specific regard to effect of radiotherapy, focusing the attention on the mechanism underling the radionecrosis and the brain damage, and show the role of nuclear medicine techniques to distinguish necrosis from recurrence and to early detect of cognitive decline after treatment.

What Neuroradiologists Need to Know About Radiation Treatment for Neural Tumors

Radiation oncologists and radiologists have a unique and mutually dependent relationship. Radiation oncologists rely on diagnostic imaging to locate the tumor and define the treatment target volume, evaluation of response to therapy, and follow-up. Accurate interpretation of post-treatment imaging requires diagnostic radiologists to have a basic understanding of radiation treatment planning and delivery. There are various radiation treatment modalities such as 3D conformal radiation therapy, intensity modulated radiation therapy and stereotactic radiosurgery as well as different radiation modalities such as photons and protons that can be used for treatment. All of these have subtle differences in how the treatment is planned and how the imaging findings might be affected. This paper provides an overview of the basic principles of radiation oncology, different radiation treatment modalities, how radiation therapy is planned and delivered, how knowledge of this process can help interpretation of images, and how the radiologist can contribute to this process.

Feasibility and accuracy of quantitative imaging on a 1.5 T MR-linear accelerator

PURPOSE

Systems for magnetic resonance (MR-) guided radiotherapy enable daily MR imaging of cancer patients during treatment, which is of interest for treatment response monitoring and biomarker discovery using quantitative MRI (qMRI). Here, the performance of a 1.5 T MR-linac regarding qMRI was assessed on phantoms. Additionally, we show the feasibility of qMRI in a prostate cancer patient on this system for the first time.

MATERIALS AND METHODS

Four 1.5 T MR-linac systems from four institutes were included in this study. T₁ and T₂ relaxation times, and apparent diffusion coefficient (ADC) maps, as well as dynamic contrast enhanced (DCE) images were acquired. Bland-Altman statistics were used, and accuracy, repeatability, and reproducibility were determined.

RESULTS

Median accuracy for T₁ ranged over the four systems from 2.7 to 14.3%, for T₂ from 10.4 to 14.1%, and for ADC from 1.9 to 2.7%. For DCE images, the accuracy ranged from 12.8 to 35.8% for a gadolinium concentration of 0.5 mM and deteriorated for higher concentrations. Median short-term repeatability for T₁ ranged from 0.6 to 5.1%, for T₂ from 0.4 to 1.2%, and for ADC from 1.3 to 2.2%. DCE acquisitions showed a coefficient of variation of 0.1-0.6% in the signal intensity. Long-term repeatability was 1.8% for T₁, 1.4% for T₂, 1.7% for ADC, and 17.9% for DCE. Reproducibility was 11.2% for T₁, 2.9% for T₂, 2.2% for ADC, and 18.4% for DCE.

CONCLUSION

These results indicate that qMRI on the Unity MR-linac is feasible, accurate, and repeatable which is promising for treatment response monitoring and treatment plan adaptation based on daily qMRI.

Emerging Functional Imaging Biomarkers of Tumour Responses to Radiotherapy

Tumour responses to radiotherapy are currently primarily assessed by changes in size. Imaging permits non-invasive, whole-body assessment of tumour burden and guides treatment options for most tumours. However, in most tumours, changes in size are slow to manifest and can sometimes be difficult to interpret or misleading, potentially leading to prolonged durations of ineffective treatment and delays in changing therapy. Functional imaging techniques that monitor biological processes have the potential to detect tumour responses to treatment earlier and refine treatment options based on tumour biology rather than solely on size and staging. By considering the biological effects of radiotherapy, this review focusses on emerging functional imaging techniques with the potential to augment morphological imaging and serve as biomarkers of early response to radiotherapy.

DW-MRI for esophageal squamous cell carcinoma, correlations between ADC values with histologic differentiation and VEGF expression: A retrospective study

The aim of the present study was to assess the correlations between diffusion-weighted magnetic resonance imaging (DW-MRI) features with the histologic differentiation and the expression of vascular endothelial growth factor (VEGF) in esophageal squamous cell carcinoma (ESCC). A total of 52 patients with ESCC included in the present study received radiotherapy, and all patients underwent contrast enhanced MRI and DW-MRI prior to and following radiotherapy. The diffusion sensitivity coefficient (b value) was set as 800 s/mm². Apparent diffusion coefficient (ADC) values were automatically computed. VEGF expression was evaluated by immunohistochemical staining. The results demonstrated that the pathological grading of ESCC was positively correlated with ADC values (r=0.635, P=0.0007), and the VEGF expression was inversely correlated with ADC values (r=−0.321, P=0.008). However, no correlation was identified between the pathological grading and the VEGF expression (r=0.178, P=0.284). All patients were categorized as complete response (CR) or partial response (PR) and the ADC values were increased significantly following radiotherapy. The mean ADC values in the CR group were higher than the PR group prior to radiotherapy (t=5.156, P=0.0004). Therefore, we concluded that the DWI with ADC value measurement may represent the grade of tumor histologic differentiation and the degree of VEGF expression, and may also serve as a useful marker to predict radiotherapy and anti-VEGF response in ESCC. ADC value may be a substitution for assessing tumor angiogenesis and novel prognostic factor and contribute to the treatment of ESCC.

Model-Interpolated Gating for Magnetic Resonance Image-Guided Radiation Therapy

PURPOSE

To develop and validate a technique for radiation therapy gating using slow (≤1 frame per second) magnetic resonance imaging (MRI) and a motion model. Proposed uses of the technique include radiation therapy gating using T2-weighted images and conducting additional imaging studies during gated treatments.

METHODS AND MATERIALS

The technique uses a physiologically guided breathing motion model to interpolate deformed target position between 2-dimensional (2D) MRI images acquired every 1 to 3 seconds. The model is parameterized by a 1-dimensional respiratory bellows surrogate and is continuously updated with the most recently acquired 2D images. A phantom and 8 volunteers were imaged with a 0.35T MRI-guided radiation therapy system. A balanced steady-state free precession sequence with a 2D frame rate of 3 frames per second was used to evaluate the technique. The accuracy and beam-on positive predictive value (PPV) of the model-based gating decisions were evaluated using the gating decisions derived from imaging as a ground truth. A T2-weighted gating offline proof-of-concept study using a half-Fourier, single-shot, turbo-spin echo sequence is reported.

RESULTS

Model-interpolated gating accuracy, beam-on PPV, and median absolute distances between model and image-tracked target centroids were, on average, 98.3%, 98.4%, and 0.33 mm, respectively, in the balanced steady-state free precession phantom studies and 93.7%, 92.1%, and 0.86 mm, respectively, in the volunteer studies. T2 model-interpolated gating in 6 volunteers yielded an average accuracy and PPV of 94.3% and 92.5%, respectively, and the mean absolute median distance between modeled and imaged target centroids was 0.86 mm.

CONCLUSIONS

This work demonstrates the concept of model-interpolated gating for MRI-guided radiation therapy. The technique was found to be potentially sufficiently accurate for clinical use. Further development is needed to accommodate out-of-plane motion and the use of an internal MR-based respiratory surrogate.

Therapy of breast cancer brain metastases: challenges, emerging treatments and perspectives

Brain metastases are the most common central nervous system tumors in adults, and incidence of brain metastases is increasing due to both improved diagnostic techniques (e.g. magnetic resonance imaging) and increased cancer patient survival through advanced systemic treatments. Outcomes of patients remain disappointing and treatment options are limited, usually involving multimodality approaches. Brain metastases represent an unmet medical need in solid tumor care, especially in breast cancer, where brain metastases are frequent and result in impaired quality of life and death. Challenges in the management of brain metastases have been highlighted in this review. Innovative research and treatment strategies, including prevention approaches and emerging systemic treatment options for brain metastases of breast cancer, are further discussed.