The potential role of magnetic resonance spectroscopy in image-guided radiotherapy

Myeloid cell-derived creatine in the hypoxic niche promotes glioblastoma growth

Glioblastoma (GBM) is a malignancy dominated by the infiltration of tumor-associated myeloid cells (TAMCs). Examination of TAMC metabolic phenotypes in mouse models and patients with GBM identified the de novo creatine metabolic pathway as a hallmark of TAMCs. Multi-omics analyses revealed that TAMCs surround the hypoxic peri-necrotic regions of GBM and express the creatine metabolic enzyme glycine amidinotransferase (GATM). Conversely, GBM cells located within these same regions are uniquely specific in expressing the creatine transporter (SLC6A8). We hypothesized that TAMCs provide creatine to tumors, promoting GBM progression. Isotopic tracing demonstrated that TAMC-secreted creatine is taken up by tumor cells. Creatine supplementation protected tumors from hypoxia-induced stress, which was abrogated with genetic ablation or pharmacologic inhibition of SLC6A8. Lastly, inhibition of creatine transport using the clinically relevant compound, RGX-202-01, blunted tumor growth and enhanced radiation therapy in vivo. This work highlights that myeloid-to-tumor transfer of creatine promotes tumor growth in the hypoxic niche.

Magnetic resonance spectroscopy and its application in colorectal cancer diagnosis and screening: A narrative review

There are several slightly invasive methods to detect colorectal carcinoma (CRC) including colonoscopy and sigmoidoscopy; but there is no noninvasive, accurate screening test. It is recommended to initiate screening at the age of 50 for non-familial CRC. Laboratory tests are routinely suggested if internal observation and imaging are recommended for further evaluation. Spectroscopic-based imaging, such as magnetic resonance spectroscopy (MRS) is an interesting and promising tool with the potential to be an alternative to some minimally invasive procedures, such as biopsy. Accordingly, MRS might be a suitable substitution for invasive methods, such as colonoscopy. This article aimed to review the studies that have evaluated the MRS technique as a screening tool in CRC.

Molecular Imaging in Photon Radiotherapy

Nowadays, more than ever before, the treatment of cancer patients requires an interdisciplinary approach more than ever. Radiation therapy (RT) has become an indispensable pillar of cancer treatment early on, offering a local, curative treatment option and symptom control in palliative cases.

A method for cranial target delineation in radiotherapy treatment planning aided by single-voxel magnetic resonance spectroscopy: evaluation using a custom-designed gel-based phantom and simulations

OBJECTIVE

Magnetic resonance spectroscopy (MRS) has been useful in radiotherapy treatment planning (RTP) especially in tumor delineation. Routinely, 2D/3D MRSI data are used for this application. However, not all centers have access to 2D/3D MRSI. The objective of this study was to introduce a method of using single-voxel spectroscopy (SVS) data in target delineation and assess its reliability.

METHODS

A gel-based phantom containing Creatine (Cr), N-acetyl-l-aspartic-acid (NAA), and Choline (Cho) was designed and built. The metabolite ratios simulate the normal and tumoral part of the brain. The jMRUI software (v. 6.0) was used to simulate a 1.5 T GE MRI scanner. The metabolite spectra provided by different time of echos (TE)s of the Point-RESolved Spectroscopy pulse-sequence (PRESS), different data-points, and post-processings were quantized by jMRUI. PseudoMRSI maps of Cho/Cr, NAA/Cr, and Cho + Cr/NAA were created. A conformity index (CI) was used to determine which metabolite-ratio isolines are more appropriate for tumor delineation.

RESULTS

The simulation accuracy was verified. There were no differences > 4% between the measured and simulated spectra in peak regions. The pseudoMRSI map of Cho + Cr/NAA smoothly followed the complicated geometry of the tumor inside the gel-based phantom. The results showed that the single-voxel spectra produced by the PRESS pulse sequence with the TE of 144 ms, 512 data-points, and minimum post-processings of water suppression, eddy current correction, and baseline correction can be used for target delineation.

CONCLUSION

This study suggests that SVS data can be used to aid target delineation by using a mathematical approach. This can enable a wider use of MR-derived information in radiotherapy.

ADVANCES IN KNOWLEDGE

To the best of our knowledge, until now, 2D or 3D MRSI data provided from 3T MRI scanners have been used for MRS-based radiotherapy treatment planning. However, there are a lot of centers that are equipped to 1.5 T MRI scanners and some of them just equipped to SVS. This study introduces a mathematical approach to help these centers to take the benefits of MRS-based treatment planning.

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.

The Use of Quantitative Imaging in Radiation Oncology: A Quantitative Imaging Network (QIN) Perspective

Modern radiation therapy is delivered with great precision, in part by relying on high-resolution multidimensional anatomic imaging to define targets in space and time. The development of quantitative imaging (QI) modalities capable of monitoring biologic parameters could provide deeper insight into tumor biology and facilitate more personalized clinical decision-making. The Quantitative Imaging Network (QIN) was established by the National Cancer Institute to advance and validate these QI modalities in the context of oncology clinical trials. In particular, the QIN has significant interest in the application of QI to widen the therapeutic window of radiation therapy. QI modalities have great promise in radiation oncology and will help address significant clinical needs, including finer prognostication, more specific target delineation, reduction of normal tissue toxicity, identification of radioresistant disease, and clearer interpretation of treatment response. Patient-specific QI is being incorporated into radiation treatment design in ways such as dose escalation and adaptive replanning, with the intent of improving outcomes while lessening treatment morbidities. This review discusses the current vision of the QIN, current areas of investigation, and how the QIN hopes to enhance the integration of QI into the practice of radiation oncology.

Survey on deep learning for radiotherapy

More than 50% of cancer patients are treated with radiotherapy, either exclusively or in combination with other methods. The planning and delivery of radiotherapy treatment is a complex process, but can now be greatly facilitated by artificial intelligence technology. Deep learning is the fastest-growing field in artificial intelligence and has been successfully used in recent years in many domains, including medicine. In this article, we first explain the concept of deep learning, addressing it in the broader context of machine learning. The most common network architectures are presented, with a more specific focus on convolutional neural networks. We then present a review of the published works on deep learning methods that can be applied to radiotherapy, which are classified into seven categories related to the patient workflow, and can provide some insights of potential future applications. We have attempted to make this paper accessible to both radiotherapy and deep learning communities, and hope that it will inspire new collaborations between these two communities to develop dedicated radiotherapy applications.

From imaging to biology of glioblastoma: new clinical oncology perspectives to the problem of local recurrence

GBM is one of the most common and aggressive brain tumors. Surgery and adjuvant chemoradiation have succeeded in providing a survival benefit. Although most patients will eventually experience local recurrence, the means to fight recurrence are limited and prognosis remains poor. In a disease where local control remains the major challenge, few trials have addressed the efficacy of local treatments, either surgery or radiation therapy. The present article reviews recent advances in the biology, imaging and biomarker science of GBM as well as the current treatment status of GBM, providing new perspectives to the problem of local recurrence.

The Role of PET/MR Imaging in Precision Medicine

Fluorodeoxyglucose PET and PET/computed tomography have gained acceptance in the evaluation of disease. Nontargeted tracers have been used in the diagnosis of certain malignancies but may not be sensitive or specific enough to become standard of care. Newer targeted PET tracers have been developed that target disease-specific biomarkers, and allow accurate and sensitive detection of disease. Combined with the capabilities of MR imaging to evaluate soft tissue, precision imaging with PET/MR imaging can change the diagnosis. This article discusses specific areas in which precision imaging with nontargeted and targeted diagnostic agents can change the diagnosis and treatment.

Characterization of spatial distortion in a 0.35 T MRI-guided radiotherapy system

Spatial distortion results in image deformation that can degrade accurate targeting and dose calculations in MRI-guided adaptive radiotherapy. The authors present a comprehensive assessment of a 0.35 T MRI-guided radiotherapy system's spatial distortion using two commercially-available phantoms with regularly spaced markers. Images of the spatial integrity phantoms were acquired using five clinical protocols on the MRI-guided radiotherapy machine with the radiotherapy gantry positioned at various angles. Software was developed to identify and localize all phantom markers using a template matching approach. Rotational and translational corrections were implemented to account for imperfect phantom alignment. Measurements were made to assess uncertainties arising from susceptibility artifacts, image noise, and phantom construction accuracy. For a clinical 3D imaging protocol with a 1.5 mm reconstructed slice thickness, 100% of spheres within a 50 mm radius of isocenter had a 3D deviation of 1 mm or less. Of the spheres within 100 mm of isocenter, 99.9% had a 3D deviation less than 1 mm. 94.8% and 100% of the spheres within 175 mm were found to be within 1 mm and 2 mm of the expected positions in 3D respectively. Maximum 3D distortions within 50 mm, 100 mm and 175 mm of isocenter were 0.76 mm, 1.15 mm and 1.88 mm respectively. Distortions present in images acquired using the real-time imaging sequence were less than 1 mm for 98.1% and 95.0% of the cylinders within 50 mm and 100 mm of isocenter. The corresponding maximum distortion in these regions was 1.10 mm and 1.67 mm. These results may be used to inform appropriate planning target volume (PTV) margins for 0.35 T MRI-guided radiotherapy. Observed levels of spatial distortion should be explicitly considered when using PTV margins of 3 mm or less or in the case of targets displaced from isocenter by more than 50 mm.

The future of image-guided radiotherapy will be MR guided

Advances in image-guided radiotherapy (RT) have allowed for dose escalation and more precise radiation treatment delivery. Each decade brings new imaging technologies to help improve RT patient setup. Currently, the most frequently used method of three-dimensional pre-treatment image verification is performed with cone beam CT. However, more recent developments have provided RT with the ability to have on-board MRI coupled to the teleradiotherapy unit. This latest tool for treating cancer is known as MR-guided RT. Several varieties of these units have been designed and installed in centres across the globe. Their prevalence, history, advantages and disadvantages are discussed in this review article. In preparation for the next generation of image-guided RT, this review also covers where MR-guided RT might be heading in the near future.

Choline-based imaging of prostate cancer with combined [18F] fluorocholine PET and 1H MR spectroscopy by means of integrated PET/MRI

PURPOSE

To evaluate integrated PET/MRI/¹H MR spectroscopy in patients with prostate cancer.

SUBJECTS AND METHODS

Data analysis comprised calculations of correlations of standardized uptake values (SUVs) and ratios of (choline+creatine)/citrate as well as of single metabolite values and a logistic regression analysis of PET data and MR spectroscopy data in 22 patients.

RESULTS

SUVmean and integral values of choline correlated significantly in tumors. Logistic regression analysis demonstrated diagnostic superiority of PET over spectroscopy.

CONCLUSION

Simultaneous acquisition of PET and MR spectroscopy with integrated PET/MRI is feasible. Choline compounds and choline metabolism show a positive significant correlation.

Imaging Genomics of Glioblastoma: Biology, Biomarkers, and Breakthroughs

Glioblastoma is regarded as the most aggressive and most common primary malignant brain tumor in adults. Despite advancements in chemotherapy and radiotherapy, prognosis and overall survival of glioblastoma patients remain dismal. Recently, progresses in genetic profiling have increased our understanding of the underlying heterogenous molecular nature of this aggressive tumor. Several prognostic and predictive molecular biomarkers have been identified that have been linked to patient's survival and response to treatment, respectively. Imaging genomics represents a novel entity in clinical sciences that bidirectionally links imaging features with underlying molecular profile and thus can serve as a surrogate for noninvasive genomic correlation, prediction, and identification.

Review of potential improvements using MRI in the radiotherapy workflow

The goal of modern radiotherapy is to deliver a lethal amount of dose to tissue volumes that contain a significant amount of tumour cells while sparing surrounding unaffected or healthy tissue. Online image guided radiotherapy with stereotactic ultrasound, fiducial-based planar X-ray imaging or helical/conebeam CT has dramatically improved the precision of radiotherapy, with moving targets still posing some methodical problems regarding positioning. Therefore, requirements for precise target delineation and identification of functional body structures to be spared by high doses become more evident. The identification of areas of relatively radioresistant cells or areas of high tumor cell density is currently under development. This review outlines the state of the art of MRI integration into treatment planning and its importance in follow up and the quantification of biological effects. Finally the current state of the art of online imaging for patient positioning will be outlined and indications will be given what the potential of integrated radiotherapy/online MRI systems is.

Automatic voxel positioning for MRS at 7 T

OBJECT

The purpose of this study was to test, for the first time, whether spectroscopy voxels could be positioned automatically with high accuracy and reproducibility in ultrahigh-field longitudinal magnetic resonance spectroscopy (MRS) studies.

MATERIALS AND METHODS

MRS voxels were automatically positioned in two cingulate subregions of 12 healthy subjects using a vendor-provided automatic voxel positioning (AutoAlign) technique, and were manually placed in the same regions of 10 healthy subjects by an experienced technician in three 7 T MRS scan sessions. Different coils were used for manual (24-channel coil) and automatic (32-channel coil) voxel placement, and the effects of signal-to-noise-ratio differences on the spectra were considered.

RESULTS

Over three scan sessions and two regions scanned for each subject, a mean voxel geometric overlap ratio of 0.91 for automatic positioning reflected accurate voxel alignment, while the geometric overlap ratio was only 0.70 for voxels placed manually. Comparable voxel positions among the three scan sessions (p > 0.05) indicated high reproducibility of automatic voxel alignment. In comparison, significant voxel displacement among scan sessions (p < 0.05) was found using manual voxel positioning.

CONCLUSIONS

In view of the highly accurate and reproducible voxel alignment with automatic voxel positioning, we propose the application of automatic rather than manual voxel positioning in future ultrahigh-field longitudinal MRS studies.