MRI for identification of progression in brain tumors: from morphology to function

New opportunities for RGD-engineered metal nanoparticles in cancer

The advent of nanotechnology has opened new possibilities for bioimaging. Metal nanoparticles (such as gold, silver, iron, copper, etc.) hold tremendous potential and offer enormous opportunities for imaging and diagnostics due to their broad optical characteristics, ease of manufacturing technique, and simple surface modification. The arginine-glycine-aspartate (RGD) peptide is a three-amino acid sequence that seems to have a considerably greater ability to adhere to integrin adhesion molecules that exclusively express on tumour cells. RGD peptides act as the efficient tailoring ligand with a variety of benefits including non-toxicity, greater precision, rapid clearance, etc. This review focuses on the possibility of non-invasive cancer imaging using metal nanoparticles with RGD assistance.

A Rapid Late Enhancement MRI Protocol Improves Differentiation between Brain Tumor Recurrence and Treatment-Related Contrast Enhancement of Brain Parenchyma

PURPOSE

Differentiation between tumor recurrence and treatment-related contrast enhancement in MRI can be difficult. Late enhancement MRI up to 75 min after contrast agent application has been shown to improve differentiation between tumor recurrence and treatment-related changes. We investigated the diagnostic performance of late enhancement using a rapid MRI protocol optimized for clinical workflow.

METHODS

Twenty-three patients with 28 lesions suspected for glioma recurrence underwent MRI including T1-MPRAGE-series acquired 2 and 20 min after contrast agent administration. Early contrast series were subtracted from late contrast series using motion correction. Contrast enhancing lesions were retrospectively and independently evaluated by two readers blinded to the patients' later clinical course and histology with or without the use of late enhancement series. Sensitivity, specificity, NPV, and PPV were calculated for both readers by comparing results of MRI with histological samples.

RESULTS

Using standard MR sequences, sensitivity, specificity, PPV, and NPV were 0.84, 0, 0.875, and 0 (reader 1) and 0.92, 0, 0.885, and 0 (reader 2), respectively. Early late enhancement increased sensitivity, specificity, PPV, and NPV to 1 for each value and for both readers. Inter-reader reliability increased from 0.632 (standard MRI sequences) to 1.0 (with early late enhancement).

CONCLUSION

The described rapid late enhancement MRI protocol improves MRI-based discrimination between tumor tissue and treatment-related changes of the brain parenchyma.

Rare-earth based materials: an effective toolbox for brain imaging, therapy, monitoring and neuromodulation

Brain diseases, including tumors and neurodegenerative disorders, are among the most serious health problems. Non-invasively high-resolution imaging methods are required to gain anatomical structures and information of the brain. In addition, efficient diagnosis technology is also needed to treat brain disease. Rare-earth based materials possess unique optical properties, superior magnetism, and high X-ray absorption abilities, enabling high-resolution imaging of the brain through magnetic resonance imaging, computed tomography imaging, and fluorescence imaging technologies. In addition, rare-earth based materials can be used to detect, treat, and regulate of brain diseases through fine modulation of their structures and functions. Importantly, rare-earth based materials coupled with biomolecules such as antibodies, peptides, and drugs can overcome the blood-brain barrier and be used for targeted treatment. Herein, this review highlights the rational design and application of rare-earth based materials in brain imaging, therapy, monitoring, and neuromodulation. Furthermore, the development prospect of rare-earth based materials is briefly introduced.

Grading Trigone Meningiomas Using Conventional Magnetic Resonance Imaging With Susceptibility-Weighted Imaging and Perfusion-Weighted Imaging

OBJECTIVE

To compare conventional magnetic resonance imaging (MRI), susceptibility-weighted imaging (SWI), and perfusion-weighted imaging (PWI) characteristics in different grades of trigone meningiomas.

METHODS

Thirty patients with trigone meningiomas were enrolled in this retrospective study. Conventional MRI was performed in all patients; SWI (17 cases), dynamic contrast-enhanced PWI (10 cases), and dynamic susceptibility contrast PWI (6 cases) were performed. Demographics, conventional MRI features, SWI- and PWI-derived parameters were compared between different grades of trigone meningiomas.

RESULTS

On conventional MRI, the irregularity of tumor shape (ρ = 0.497, P = 0.005) and the extent of peritumoral edema (ρ = 0.187, P = 0.022) might help distinguish low-grade and high-grade trigone meningiomas. On multiparametric functional MRI, rTTPmax (1.17 ± 0.06 vs 1.30 ± 0.05, P = 0.048), Kep, Ve, and iAUC demonstrated their potentiality to predict World Health Organization grades I, II, and III trigone meningiomas.

CONCLUSIONS

Conventional MRI combined with dynamic susceptibility contrast and dynamic contrast-enhanced can help predict the World Health Organization grade of trigone meningiomas.

Clinical Applications of Magnetic Resonance Spectroscopy in Brain Tumors: From Diagnosis to Treatment

Magnetic resonance spectroscopy (MRS) is a valuable tool for imaging brain tumors, primarily as an adjunct to conventional imaging and clinical presentation. MRS is useful in initial diagnosis of brain tumors, helping differentiate tumors from possible mimics such as metastatic disease, lymphoma, demyelination, and infection, as well as in the subsequent follow-up of patients after resection and chemoradiation. Unfortunately, the spectroscopic appearance of many pathologies can overlap, and ultimately follow-up or biopsy may be required to make a definitive diagnosis. Future developments may continue to increase the value of MRS for initial diagnosis, treatment planning, and early detection of recurrence.

Magnetic resonance spectroscopic imaging in gliomas: clinical diagnosis and radiotherapy planning

The reprogramming of cellular metabolism is a hallmark of cancer diagnosis and prognosis. Proton magnetic resonance spectroscopic imaging (MRSI) is a non-invasive diagnostic technique for investigating brain metabolism to establish cancer diagnosis and IDH gene mutation diagnosis as well as facilitate pre-operative planning and treatment response monitoring. By allowing tissue metabolism to be quantified, MRSI provides added value to conventional MRI. MRSI can generate metabolite maps from a single volume or multiple volume elements within the whole brain. Metabolites such as NAA, Cho and Cr, as well as their ratios Cho:NAA ratio and Cho:Cr ratio, have been used to provide tumor diagnosis and aid in radiation therapy planning as well as treatment assessment. In addition to these common metabolites, 2-hydroxygluterate (2HG) has also been quantified using MRSI following the recent discovery of IDH mutations in gliomas. This has opened up targeted drug development to inhibit the mutant IDH pathway. This review provides guidance on MRSI in brain gliomas, including its acquisition, analysis methods, and evolving clinical applications.

A potential field segmentation based method for tumor segmentation on multi-parametric MRI of glioma cancer patients

Background

Accurate segmentation of brain tumors is vital for the gross tumor volume (GTV) definition in radiotherapy. Functional MR images like apparent diffusion constant (ADC) and fractional anisotropy (FA) images can provide more comprehensive information for sensitive detection of the GTV. We synthesize anatomical and functional MRI for accurate and semi-automatic segmentation of GTVs and improvement of clinical efficiency.

Methods

Four MR image sets including T1-weighted contrast-enhanced (T1C), T2-weighted (T2), apparent diffusion constant (ADC) and fractional anisotropy (FA) images of 5 glioma patients were acquired and registered. A new potential field segmentation (PFS) method was proposed based on the concept of potential field in physics. For T1C, T2 and ADC images, global potential field segmentation (global-PFS) was used on user defined region of interest (ROI) for rough segmentation and then morphologically processed for accurate delineation of the GTV. For FA images, white matter (WM) was removed using local potential field segmentation (local-PFS), and then tumor extent was delineated with region growing and morphological methods. The individual segmentations of multi-parametric images were ensembled into a fused segmentation, considered as final GTV. GTVs were compared with manually delineated ground truth and evaluated with segmentation quality measure (Q), Dice’s similarity coefficient (DSC) and Sensitivity and Specificity.

Results

Experimental study with the five patients’ data and new method showed that, the mean values of Q, DSC, Sensitivity and Specificity were 0.80 (±0.07), 0.88 (±0.04), 0.92 (±0.01) and 0.88 (±0.05) respectively. The global-PFS used on ROIs of T1C, T2 and ADC images can avoid interferences from skull and other non-tumor areas. Similarity to local-PFS on FA images, it can also reduce the time complexity as compared with the global-PFS on whole image sets.

Conclusions

Efficient and semi-automatic segmentation of the GTV can be achieved with the new method. Combination of anatomical and functional MR images has the potential to provide new methods and ideas for target definition in radiotherapy.

Current concepts in radiologic assessment of pediatric brain tumors during treatment, part 1

Pediatric brain tumors differ from those in adults by location, phenotype and genotype. In addition, they show dissimilar imaging characteristics before and after treatment. While adult brain tumor treatment effects are primarily assessed on MRI by measuring the contrast-enhancing components in addition to abnormalities on T2-weighted and fluid-attenuated inversion recovery images, these methods cannot be simply extrapolated to pediatric central nervous system tumors. A number of researchers have attempted to solve the problem of tumor assessment during treatment in pediatric neuro-oncology; specifically, the Response Assessment in Pediatric Neuro-Oncology (RAPNO) working group was recently established to deal with the distinct challenges in evaluating treatment-related changes on imaging, but no established criteria are available. In this article we review the current methods to evaluate brain tumor therapy and the numerous challenges that remain. In part 1, we examine the role of T2-weighted imaging and fluid-attenuated inversion recovery sequences, contrast enhancement, volumetrics and diffusion imaging techniques. We pay particular attention to several specific pediatric brain tumors, such as optic pathway glioma, diffuse midline glioma and medulloblastoma. Finally, we review the best means to assess leptomeningeal seeding.

Surgical Considerations in the Optimal Management of Patients with Malignant Brain Tumors

OPINION STATEMENT

Advances in technology are revolutionizing medicine and the limits of what we can offer to our patients. In neurosurgery, technology continues to reduce morbidity, increase surgical accuracy, facilitate tissue acquisition, and promote novel techniques for prolonging survival in patients with neuro-oncologic disease. Surgery has been the backbone of glioma diagnosis and treatment by providing adequate, high quality material for precise histologic diagnosis, and genomic characterization in the setting of significant intratumoral heterogeneity, thus allowing personalized treatment selection in the clinic. The ability to obtain and accurately measure the maximal extent of resection in glioma surgery also remains a central role of the neurosurgeon in managing this cancer. To meet these goals, today's operating room has transformed from the traditional operating table and anesthesia machine to include neuronavigation instrumentation, intraoperative computed tomography, and magnetic resonance imaging scanners, advanced surgical microscopes fitted with fluorescent light filters, and electrocorticography machines. While surgeons, oncologists, and radiation oncologists all play unique critical roles in the care of patients with malignant gliomas, familiarity with developing techniques in complimentary subspecialties can enhance coordination of patient care, research productivity, professional interactions, and patient confidence and comfort with the physician team. Herein, we provide a summary of the advances in the field of neurosurgical oncology which allow more precise and optimal surgical resection for patients with malignant gliomas.

A fuzzy feature fusion method for auto-segmentation of gliomas with multi-modality diffusion and perfusion magnetic resonance images in radiotherapy

The diffusion and perfusion magnetic resonance (MR) images can provide functional information about tumour and enable more sensitive detection of the tumour extent. We aimed to develop a fuzzy feature fusion method for auto-segmentation of gliomas in radiotherapy planning using multi-parametric functional MR images including apparent diffusion coefficient (ADC), fractional anisotropy (FA) and relative cerebral blood volume (rCBV). For each functional modality, one histogram-based fuzzy model was created to transform image volume into a fuzzy feature space. Based on the fuzzy fusion result of the three fuzzy feature spaces, regions with high possibility belonging to tumour were generated automatically. The auto-segmentations of tumour in structural MR images were added in final auto-segmented gross tumour volume (GTV). For evaluation, one radiation oncologist delineated GTVs for nine patients with all modalities. Comparisons between manually delineated and auto-segmented GTVs showed that, the mean volume difference was 8.69% (±5.62%); the mean Dice’s similarity coefficient (DSC) was 0.88 (±0.02); the mean sensitivity and specificity of auto-segmentation was 0.87 (±0.04) and 0.98 (±0.01) respectively. High accuracy and efficiency can be achieved with the new method, which shows potential of utilizing functional multi-parametric MR images for target definition in precision radiation treatment planning for patients with gliomas.

Adult Brain Tumors: Clinical Applications of Magnetic Resonance Spectroscopy

Proton magnetic resonance spectroscopy (H-MRS) may be helpful in suggesting tumor histology and tumor grade and may better define tumor extension and the ideal site for biopsy compared with conventional magnetic resonance (MR) imaging. A multifunctional approach with diffusion-weighted imaging, perfusion-weighted imaging, and permeability maps, along with H-MRS, may enhance the accuracy of the diagnosis and characterization of brain tumors and estimation of therapeutic response. Integration of advanced imaging techniques with conventional MR imaging and the clinical history help to improve the accuracy, sensitivity, and specificity in differentiating tumors and nonneoplastic lesions.

MRI in Glioma Immunotherapy: Evidence, Pitfalls, and Perspectives

Pseudophenomena, that is, imaging alterations due to therapy rather than tumor evolution, have an important impact on the management of glioma patients and the results of clinical trials. RANO (response assessment in neurooncology) criteria, including conventional MRI (cMRI), addressed the issues of pseudoprogression after radiotherapy and concomitant chemotherapy and pseudoresponse during antiangiogenic therapy of glioblastomas (GBM) and other gliomas. The development of cancer immunotherapy forced the identification of further relevant response criteria, summarized by the iRANO working group in 2015. In spite of this, the unequivocal definition of glioma progression by cMRI remains difficult particularly in the setting of immunotherapy approaches provided by checkpoint inhibitors and dendritic cells. Advanced MRI (aMRI) may in principle address this unmet clinical need. Here, we discuss the potential contribution of different aMRI techniques and their indications and pitfalls in relation to biological and imaging features of glioma and immune system interactions.

RGD/CTX-conjugated multifunctional Eu–Gd2O3NRs for targeting detection and inhibition of early tumor

The multifunctional Eu–Gd₂O₃nanorods (NRs) with targeting/limitation of early glioblastoma and enhancements ofin vivoMR and luminescence imaging were fabricated through a hydrothermal-calcination, PEGylation and thiolation conjugation of arginine–glycine–aspartic (RGD) and chlorotoxin (CTX).

Advanced MRI may complement histological diagnosis of lower grade gliomas and help in predicting survival

MRI grading of grade II and III gliomas may have an important impact on treatment decisions. Occasionally,both conventional MRI (cMRI) and histology fail to clearly establish the tumour grade. Three cMRI features(no necrosis; no relevant oedema; absent or faint contrast enhancement) previously validated in 196 patients with supratentorial gliomas directed our selection of 68 suspected low-grade gliomas (LGG) that were also investigated by advanced MRI (aMRI), including perfusion weighted imaging (PWI), diffusion weighted imaging(DWI) and spectroscopy. All the gliomas had histopathological diagnoses. Sensitivity and specificity of cMRI preoperative diagnosis were 78.5 and 38.5 %, respectively, and 85.7 and 53.8 % when a MRI was included, respectively. ROC analysis showed that cut-off values of 1.29 for maximum rCBV, 1.69 for minimum rADC, 2.1 for rCho/Cr ratio could differentiate between LGG and HGG with a sensitivity of 61.5, 53.8, and 53.8 % and a specificity of 54.7, 43 and 64.3 %, respectively. A significantly longer OS was observed in patients with a maximum rCBV<1.46 and minimum rADC>1.69 (80 vs 55 months, p = 0.01; 80 vs 51 months, p = 0.002, respectively). This result was also confirmed when cases were stratified according to pathology (LGG vs HGG). The ability of a MRI to differentiate between LGG and HGG and to predict survival improved as the number of a MRI techniques considered increased. In a selected population of suspected LGG,classification by cMRI underestimated the actual fraction of HGG. aMRI slightly increased the diagnostic accuracy compared to histopathology. However, DWI and PWI were prognostic markers independent of histological grade.

Diffusion and perfusion weighted magnetic resonance imaging for tumor volume definition in radiotherapy of brain tumors

Accurate target volume delineation is crucial for the radiotherapy of tumors. Diffusion and perfusion magnetic resonance imaging (MRI) can provide functional information about brain tumors, and they are able to detect tumor volume and physiological changes beyond the lesions shown on conventional MRI. This review examines recent studies that utilized diffusion and perfusion MRI for tumor volume definition in radiotherapy of brain tumors, and it presents the opportunities and challenges in the integration of multimodal functional MRI into clinical practice. The results indicate that specialized and robust post-processing algorithms and tools are needed for the precise alignment of targets on the images, and comprehensive validations with more clinical data are important for the improvement of the correlation between histopathologic results and MRI parameter images.

Impact of histopathological transformation and overall survival in patients with progressive anaplastic glioma

Progression of anaplastic glioma (World Health Organization [WHO] grade III) is typically determined radiographically, and transformation to glioblastoma (GB) (WHO grade IV) is often presumed at that time. However, the frequency of actual histopathologic transformation of anaplastic glioma and the subsequent clinical impact is unclear. To determine these associations, we retrospectively reviewed all anaplastic glioma patients who underwent surgery at our center at first radiographic progression, and we examined the effects of histological diagnosis, clinical history, and molecular factors on transformation rate and survival. We identified 85 anaplastic glioma (39 astrocytoma, 24 oligodendroglioma, 22 oligoastrocytoma), of which 38.8% transformed to GB. Transformation was associated with shorter overall survival (OS) from the time of diagnosis (3.4 vs. 10.9years, p=0.0005) and second surgery (1.0 vs. 3.5years, p<0.0001). Original histologic subtype did not significantly impact the risk of transformation or OS. No other factors, including surgery, adjuvant therapy or molecular markers, significantly affected the risk of transformation. However, mutations in isocitrate dehydrogenase 1 (IDH1) was associated with longer time to progression (median 4.6 vs. 1.4years, p=0.008) and OS (median 10.0 vs. 4.2years, p=0.046). At radiographic progression, tissue diagnosis may be warranted as histologic grade may provide valuable prognostic information and affect therapeutic clinical trial selection criteria for this patient population.

Dendrimer technologies for brain tumor

Despite low prevalence, brain tumors are one of the most lethal forms of cancer. Unfortunately the blood-brain barrier (BBB), a highly regulated, well coordinated and efficient barrier, checks the permeation of most of the drugs across it. Hence, crossing this barrier is one of the most significant challenges in the development of efficient central nervous system therapeutics. Surface-engineered dendrimers improve biocompatibility, drug-release kinetics and aptitude to target the BBB and/or tumors and facilitate transportation of anticancer bioactives across the BBB. This review sheds light on different aspects of brain tumors and dendrimers based on different approaches for treatment including recent research, opportunities and challenges encountered in development of novel and efficient dendrimer-based therapeutics for the treatment of brain tumors.

Communication of medical images to diverse audiences using multimodal imaging

A study has been completed examining design issues concerning the interpretation of and dissemination of multimodal medical imaging data sets to diverse audiences. To create a model data set mouse fibrosarcoma tissue was visualised via magnetic resonance imaging (MRI), Matrix-Assisted Laser Desorption/Ionisation-Mass Spectrometry (MALDI-MSI) and histology. MRI images were acquired using the 0.25T Esaote GScan; MALDI images were acquired using a Q-Star Pulsar I mass spectrometer. Histological staining of the same tissue sections used for MALDI-MSI was then carried out. Areas assigned to hemosiderin deposits due to haemorrhaging could be visualised via MRI. In the MALDI-MSI data obtained the distribution sphingomyelin species could be used to identify regions of viable tumour. Mathematical ‘up sampling’ using hierarchical clustering-based segmentation provided a sophisticated image enhancement tool for both MRI and MALDI-MS and assisted in the correlation of images.

Comparison between magnetic resonance spectroscopy and diffusion weighted imaging in the evaluation of gliomas response after treatment

PURPOSE

To compare magnetic resonance spectroscopy (MRS) and diffusion weighted imaging (DWI) in the assessment of progression and regression of brain tumors in order to assess whether there is correlation between MRS and DWI in the monitoring of patients with primary tumors after therapy.

METHODS

Magnetic resonance imaging (MRI) has been performed in 80 patients, 48 affected by high grade gliomas (HGG) and 32 affected by low grade gliomas (LGG). The variation of apparent diffusion coefficient (ADC) value and metabolite ratios before and after treatment has been used to test DWI sequences and MRS as predictor to response to therapy. Comparison between post contrast-enhancement sequences, MRS and DWI has been done in terms of accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). Moreover statistical correlation of ADC deviations with MRS metabolites variations before and after therapy have been studied.

RESULTS

In the case of HGG, MRS shows better sensitivity, specificity, PPV, NPV and accuracy compared to DWI, especially when considering the Choline/N-acetylaspartate (Cho/NAA) ratio. Regarding the LGG, the technique that better evaluates the response to treatment appears to be the DWI. A moderate correlation between ADC deviations and Cho, Lipide (Lip) and Lactate (Lac) has been found in LGG; while NAA revealed to be weakly correlated to ADC variation. Considering HGG, a weak correlation has been found between ADC deviations and MRS metabolites.

CONCLUSION

Combination of DWI and MRS can help to characterize different changes related to treatment and to evaluate brain tumor response to treatment.

Upconversion nanoparticles conjugated with Gd(3+) -DOTA and RGD for targeted dual-modality imaging of brain tumor xenografts

Glioblastoma multiforme (GBM) is the most common and malignant form of primary brain tumors in human. Small molecular magnetic resonance imaging (MRI) contrast agents are used for GBM diagnosis. However, conventional contrast agents have several limitations, such as low T1 relaxivity, short circulation half lives and absence of tumor targeting. Herein, we develop an upconversion nanoprobe labeled with Gd(3+) -DOTA and RGD (UCNP-Gd-RGD) for dual-modality imaging of glioblastoma. The preparation of UCNP-Gd-RGD starts with amine-functional upconversion nanoparticle core, followed by PEGylation, Gd(3+) DOTA conjugation and RGD labeling. The obtained UCNP-Gd-RGD has improved colloidal stability and reduced cytotoxicity compared with the UCNP core counterpart. Meanwhile, UCNP-Gd-RGD shows strong upconversion luminescence in deep-red region and three times enhancement of T1 relaxivity over Gd(3+) DOTA. Due to the recognition between UCNP-Gd-RGD and integrin αv β3 receptors, the nanoprobe specifically binds to U87MG cells, as evidenced by confocal microscopy and quantified by ICP-MS. Furthermore, UCNP-Gd-RGD demonstrates a preferential retention in subcutaneous U87MG tumor xenograft as shown in both in vivo upconversion fluorescence/MR imaging studies and ex vivo analysis. UCNP-Gd-RGD, conjugated with numerous RGD peptide and T1 contrast enhancing molecules, is promising for MR imaging of glioblastoma and delineating the tumor boundary before surgery. In addition, NIR-to-red upconversion characteristic of UCNP-Gd-RGD facilitates its potential intra-operative use for fluorescence-guided tumor resection.

Seven-tesla magnetic resonance imaging accurately quantifies intratumoral uptake of therapeutic nanoparticles in the McA rat model of hepatocellular carcinoma: preclinical study in a rodent model

OBJECTIVES

After inducing McA tumors in Sprague-Dawley rats (McA-SD), the following hypotheses were tested: first, that hypervascular McA tumors grown in Sprague-Dawley rats provide a suitable platform to investigate drug delivery; and second, that high-field MRI can be used to measure intratumoral uptake of DOX-SPIOs.

MATERIALS AND METHODS

McA cells were implanted into the livers of 18 Sprague-Dawley rats. In successfully inoculated animals, 220-μL DOX-SPIOs were delivered to tumors via the intravenous or intra-arterial route. Pretreatment and posttreatment T2*-weighted images were obtained using 7-T MRI, and change in R2* value (ΔR2*) was obtained from mean signal intensities of tumors in these images. Tumor iron concentration ([Fe]), an indicator of DOX-SPIO uptake, was measured using mass spectroscopy. The primary outcome variable was the Pearson correlation between ΔR2* and [Fe].

RESULTS

Tumors grew successfully in 13 of the 18 animals (72%). Mean (SD) maximum tumor diameter was 0.83 (0.25) cm. The results of phantom studies revealed a strong positive correlation between ΔR2* and [Fe], with r = 0.98 (P < 0.01). The results of in vivo drug uptake studies demonstrated a positive correlation between ΔR2* and [Fe], with r = 0.72 (P = 0.0004).

CONCLUSIONS

The McA tumors grown in the Sprague-Dawley rats demonstrated uptake of nanoparticle-based therapeutic agents. Magnetic resonance imaging quantification of intratumoral uptake strongly correlated with iron concentrations in pathological specimens, suggesting that MRI may be used to quantify uptake of iron-oxide nanotherapeutics.

Data-driven MRSI spectral localization via low-rank component analysis

Magnetic resonance spectroscopic imaging (MRSI) is a powerful tool capable of providing spatially localized maps of metabolite concentrations. Its utility, however, is often depreciated by spectral leakage artifacts resulting from low spatial resolution measurements through an effort to reduce acquisition times. Though model-based techniques can help circumvent these drawbacks, they require strong prior knowledge, and can introduce additional artifacts when the underlying models are inaccurate. We introduce a novel scheme in which a generative model is estimated from the raw MRSI data via a regularized variational framework that minimizes the model approximation error within a measurement-prescribed subspace. As additional a priori information, our approach relies only upon a measured field inhomogeneity map at high spatial resolution. We demonstrate the feasibility of our approach on both synthetic and experimental data.

Image-guided local delivery strategies enhance therapeutic nanoparticle uptake in solid tumors

Nanoparticles (NP) have emerged as a novel class of therapeutic agents that overcome many of the limitations of current cancer chemotherapeutics. However, a major challenge to many current NP platforms is unfavorable biodistribution, and limited tumor uptake, upon systemic delivery. Delivery, therefore, remains a critical barrier to widespread clinical adoption of NP therapeutics. To overcome these limitations, we have adapted the techniques of image-guided local drug delivery to develop nanoablation and nanoembolization. Nanoablation is a tumor ablative strategy that employs image-guided placement of electrodes into tumor tissue to electroporate tumor cells, resulting in a rapid influx of NPs that is not dependent on cellular uptake machinery or stage of the cell cycle. Nanoembolization involves the image-guided delivery of NPs and embolic agents directly into the blood supply of tumors. We describe the design and testing of our innovative local delivery strategies using doxorubicin-functionalized superparamagnetic iron oxide nanoparticles (DOX-SPIOs) in cell culture, and the N1S1 hepatoma and VX2 tumor models, imaged by high resolution 7T MRI. We demonstrate that local delivery techniques result in significantly increased intratumoral DOX-SPIO uptake, with limited off-target delivery in tumor-bearing animal models. The techniques described are versatile enough to be extended to any NP platform, targeting any solid organ malignancy that can be accessed via imaging guidance.

MicroRNAs in brain metastases: big things come in small packages

Metastatic brain tumors provide a formidable obstacle in the survival of affected cancer patients, an obstacle that current treatment is essentially ineffective against. Our understanding of the metastatic cascade has demonstrated the role of incorrectly regulated protein expression and proved it to be a crucial component of this process. Recently, molecular studies have emphasized the role of microRNAs, small non-coding RNAs that alter protein expression, in the regulation of both normal and abnormal biological processes, including cancer and its metastasis to the brain. Furthermore, studies have demonstrated the ability to distinguish normal from cancerous cells, primary from secondary brain tumors, and correctly categorize metastatic brain tumor tissue of origin based solely on microRNA profiles. Interestingly, manipulation of microRNAs has proven effective in cancer treatment. With the promise of reduced toxicity, increased efficacy, and individually directed therapy, using microRNA in the treatment of metastatic brain tumors may prove very useful. In this review, we focus on the multiple potential microRNA targets for the treatment of metastatic brain lesions as well as current and future directions for its use in gene therapy.

Spatial characteristics of newly diagnosed grade 3 glioma assessed by magnetic resonance metabolic and diffusion tensor imaging

The spatial heterogeneity in magnetic resonance (MR) metabolic and diffusion parameters and their relationship were studied for patients with treatment-naive grade 3 gliomas. MR data were evaluated from 51 patients with newly diagnosed grade 3 gliomas. Anatomic, diffusion, and metabolic imaging data were considered. Variations in metabolite levels, apparent diffusion coefficient (ADC), and fractional anisotropy (FA) were evaluated in regions of gadolinium enhancement and T2 hyperintensity as well as regions with abnormal metabolic signatures. Contrast enhancement was present in only 21 of the 51 patients. When present, the enhancing component of the lesion had higher choline-to-N-acetylaspartate index (CNI), higher choline, lower N-acetylaspartate, similar creatine, similar ADC and FA, and higher lactate/lipid than the nonenhancing lesion. Regions with CNI ≥ 4 had higher choline, lower N-acetylaspartate, higher lactate/lipid, higher ADC, and lower FA than normal-appearing white matter and regions with intermediate CNI values. For lesions that exhibited gadolinium enhancement, the metabolite levels and diffusion parameters in the region of enhancement were consistent with it corresponding to the most abnormal portion of the tumor. For nonenhancing lesions, areas with CNI ≥ 4 were the most abnormal in metabolic and diffusion parameters. This suggests that the region with the highest CNI might provide a good target for biopsies for nonenhancing lesions to obtain a representative histologic diagnosis of its degree of malignancy. Metabolic and diffusion parameter levels may be of interest not only for directing tissue sampling but also for defining the targets for focal therapy and assessing response to therapy.

Two-order targeted brain tumor imaging by using an optical/paramagnetic nanoprobe across the blood brain barrier

Surgical resection is a mainstay of brain tumor treatments. However, the completed excision of malignant brain tumor is challenged by its infiltrative nature. Contrast enhanced magnetic resonance imaging is widely used for defining brain tumor in clinic. However its ability in tumor visualization is hindered by the transient circulation lifetime, nontargeting specificity, and poor blood brain barrier (BBB) permeability of the commercially available MR contrast agents. In this work, we developed a two-order targeted nanoprobe in which MR/optical imaging reporters, tumor vasculature targeted cyclic [RGDyK] peptides, and BBB-permeable Angiopep-2 peptides are labeled on the PAMAM-G5 dendrimer. This nanoprobe is supposed to first target the α(V)β(3) integrin on tumor vasculatures. Increased local concentration of nanoprobe facilitates the association between BBB-permeable peptides and the low-density lipoprotein receptor-related protein (LRP) receptors on the vascular endothelial cells, which further accelerates BBB transverse of the nanoprobe via LRP receptor-mediated endocytosis. The nanoprobes that have penetrated the BBB secondly target the brain tumor because both α(V)β(3) integrin and LRP receptor are highly expressed on the tumor cells. In vivo imaging studies demonstrated that this nanoprobe not only efficiently crossed intact BBB in normal mice, but also precisely delineated the boundary of the orthotropic U87MG human glioblastoma xenograft with high target to background signal ratio. Overall, this two-order targeted nanoprobe holds the promise to noninvasively visualize brain tumors with uncompromised BBB and provides the possibility for real-time optical-image-guided brain tumor resection during surgery.

Treatment monitoring in gliomas: comparison of dynamic susceptibility-weighted contrast-enhanced and spectroscopic MRI techniques for identifying treatment failure

OBJECTIVE

To evaluate whether dynamic susceptibility-weighted contrast-enhanced (DSC), dynamic contrast-enhanced (DCE), and proton spectroscopic imaging ((1)H-MRSI) can identify progression and predict treatment failure during follow-up before tumor size changes, contrast agent uptake, or when new lesions become obvious. The aim was also to find out which of the aforementioned techniques had the best diagnostic performance compared with each other and standard magnetic resonance imaging (MRI).

MATERIALS AND METHODS

Thirty-seven patients with gliomas (21 women, 16 men; mean age at inclusion, 48 ± 14 years [standard deviation]) were assessed prospectively by (1)H-MRSI (point-resolved spectroscopy), DCE, and DSC perfusion MRI, each after a single dose of gadobenate dimeglumine during follow-up. Histology was available in all cases (resection, N = 18; biopsy, N = 19). All patients with low-grade gliomas (n = 20) did not receive any radio- or chemotherapy after partial resection (n = 7) or biopsy (n = 13), whereas 17 patients with high-grade gliomas had received adjuvant radiotherapy immediately after surgery. Tumor progression (progressive disease, PD) was defined as increase in longest glioma diameter by at least 20% (Response Evaluation Criteria in Solid Tumors), appearance of new lesions, or new contrast-enhancement. DSC, DCE, and MRSI image analyses comprised a detailed semiquantitative region of interest (ROI) analysis of the different parameters. Wilcoxon signed-rank test, Wilcoxon rank sum test, and Cox regression were used for statistical analysis.

RESULTS

The median follow-up time was 607 days. Twenty patients showed PD (54%), 8 of 20 with low-grade (40%) and 12 of 17 with high-grade gliomas (71%). In PD, significant positive differences between log2-transformed ROI ratios at the last measurement in comparison to the first measurement (baseline) could be detected for tumor blood flow (P < 0.006) and volume (P < 0.001) derived from DSC and for maximum choline within tumor tissue (P = 0.0029) and Cho/Cr (P = 0.032) but not choline/N-acetyl-aspartate (P = 0.37) derived from MRSI. In contrast, these parameters were not significantly higher at last measurement in stable disease. Also, the differences between last value and baseline were significantly different between PD and stable disease for tumor blood flow (P < 0.004) and volume (P < 0.002) as well as for maximum choline within tumor tissue (P = 0.0011). The best prognostic parameter for PD at Cox analysis was time-dependent difference to baseline of log2 of relative regional cerebral blood flow normalized on gray matter (hazard ratio, 2.67; 95% confidence interval, 1.25-6.08; P = 0.01), while a prognostic value of MRS parameters could not be demonstrated.

CONCLUSION

DSC perfusion imaging can identify progression and can predict treatment failure during follow-up of gliomas with the best diagnostic performance.

Imaging of brain tumors: MR spectroscopy and metabolic imaging

The utility of magnetic resonance spectroscopy (MRS) in diagnosis and evaluation of treatment response to human brain tumors has been widely documented. The role of MRS in tumor classification, tumors versus nonneoplastic lesions, prediction of survival, treatment planning, monitoring of therapy, and post-therapy evaluation is discussed. This article delineates the need for standardization and further study in order for MRS to become widely used as a routine clinical tool.

Magnetic resonance imaging of multifunctional pluronic stabilized iron-oxide nanoparticles in tumor-bearing mice

We are investigating the magnetic resonance imaging characteristics of magnetic nanoparticles (MNPs) that consist of an iron-oxide magnetic core coated with oleic acid (OA), then stabilized with a pluronic or tetronic block copolymer. Since pluronics and tetronics vary structurally, and also in the ratio of hydrophobic (poly[propylene oxide]) and hydrophilic (poly[ethylene oxide]) segments in the polymer chain and in molecular weight, it was hypothesized that their anchoring to the OA coating around the magnetic core could significantly influence the physical properties of MNPs, their interactions with biological environment following intravenous administration, and ability to localize to tumors. The amount of block copolymer associated with MNPs was seen to depend upon their molecular structures and influence the characteristics of MNPs. Pluronic F127-modified MNPs demonstrated sustained and enhanced contrast in the whole tumor, whereas that of Feridex IV was transient and confined to the tumor periphery. In conclusion, our pluronic F127-coated MNPs, which can also be loaded with anticancer agents for drug delivery, can be developed as an effective cancer theranostic agent, i.e. an agent with combined drug delivery and imaging properties.

A Markov decision process approach to temporal modulation of dose fractions in radiation therapy planning

The current state of the art in cancer treatment by radiation optimizes beam intensity spatially such that tumors receive high dose radiation whereas damage to nearby healthy tissues is minimized. It is common practice to deliver the radiation over several weeks, where the daily dose is a small constant fraction of the total planned. Such a 'fractionation schedule' is based on traditional models of radiobiological response where normal tissue cells possess the ability to repair sublethal damage done by radiation. This capability is significantly less prominent in tumors. Recent advances in quantitative functional imaging and biological markers are providing new opportunities to measure patient response to radiation over the treatment course. This opens the door for designing fractionation schedules that take into account the patient's cumulative response to radiation up to a particular treatment day in determining the fraction on that day. We propose a novel approach that, for the first time, mathematically explores the benefits of such fractionation schemes. This is achieved by building a stylistic Markov decision process (MDP) model, which incorporates some key features of the problem through intuitive choices of state and action spaces, as well as transition probability and reward functions. The structure of optimal policies for this MDP model is explored through several simple numerical examples.