Harish Poptani

Diffusion-Weighted Magnetic Resonance Imaging for Predicting and Detecting Early Response to Chemoradiation Therapy of Squamous Cell Carcinomas of the Head and Neck

Purpose: The aim of this study was to investigate the utility of apparent diffusion coefficient (ADC) for prediction and early detection of treatment response in head and neck squamous cell carcinomas (HNSCC). Experimental Design: Diffusion-weighted magnetic resonance imaging studies were performed on 40 patients with newly diagnosed HNSCC before, during, and after the end of chemoradiation therapy. Analysis was done on data from 33 patients after exclusion of 7 patients that had incomplete data. Results: Pretreatment ADC value of complete responders (1.04 ± 0.19 × 10−3 mm2/s) was significantly lower (P < 0.05) than that from partial responders (1.35 ± 0.30 × 10−3 mm2/s). A significant increase in ADC was observed in complete responders within 1 week of treatment (P < 0.01), which remained high until the end of the treatment. The complete responders also showed significantly higher increase in ADC than the partial responders by the first week of chemoradiation (P < 0.01). When pretreatment ADC value was used for predicting treatment response, the area under the receiver operating characteristic curve was 0.80 with a sensitivity of 65% and a specificity of 86%. However, change in ADC within the first week of chemoradiation therapy resulted in an area under the receiver operating characteristic curve of 0.88 with 86% sensitivity and 83% specificity for prediction of treatment response. Conclusions: These results suggest that ADC can be used as a marker for prediction and early detection of response to concurrent chemoradiation therapy in HNSCC.

1H MRS detects polyunsaturated fatty acid accumulation during gene therapy of glioma: Implications for the in vivo detection of apoptosis

1 H MRS detects polyunsaturated fatty acid accumulation during gene therapy of glioma: Implications for the in vivo detection of apoptosis

Clinical Proton MR Spectroscopy in Central Nervous System Disorders

A large body of published work shows that proton (hydrogen 1 [(1)H]) magnetic resonance (MR) spectroscopy has evolved from a research tool into a clinical neuroimaging modality. Herein, the authors present a summary of brain disorders in which MR spectroscopy has an impact on patient management, together with a critical consideration of common data acquisition and processing procedures. The article documents the impact of (1)H MR spectroscopy in the clinical evaluation of disorders of the central nervous system. The clinical usefulness of (1)H MR spectroscopy has been established for brain neoplasms, neonatal and pediatric disorders (hypoxia-ischemia, inherited metabolic diseases, and traumatic brain injury), demyelinating disorders, and infectious brain lesions. The growing list of disorders for which (1)H MR spectroscopy may contribute to patient management extends to neurodegenerative diseases, epilepsy, and stroke. To facilitate expanded clinical acceptance and standardization of MR spectroscopy methodology, guidelines are provided for data acquisition and analysis, quality assessment, and interpretation. Finally, the authors offer recommendations to expedite the use of robust MR spectroscopy methodology in the clinical setting, including incorporation of technical advances on clinical units.

Prediction of response to chemoradiation therapy in squamous cell carcinomas of the head and neck using dynamic contrast-enhanced MR imaging.

BACKGROUND AND PURPOSE: Tumor microenvironment, including blood flow and permeability, may provide crucial information regarding response to chemoradiation therapy. Thus, the objective of this study was to investigate the efficacy of pretreatment DCE-MR imaging for prediction of response to chemoradiation therapy in HNSCC. MATERIALS AND METHODS: DCE-MR imaging studies were performed on 33 patients with newly diagnosed HNSCC before neoadjuvant chemoradiation therapy by using a 1.5T (n = 24) or a 3T (n = 9) magnet. The data were analyzed by using SSM for estimation of Ktrans, ve, and τi. Response to treatment was determined on completion of chemoradiation as CR, with no evidence of disease (clinically or pathologically), or PR, with pathologically proved residual tumor. RESULTS: The average pretreatment Ktrans value of the CR group (0.64 ± 0.11 minutes−1, n = 24) was significantly higher (P = .001) than that of the PR (0.21 ± 0.05 minutes−1, n = 9) group. No significant difference was found in other pharmacokinetic model parameters: ve and τi, between the 2 groups. Although the PR group had larger metastatic nodal volume than the CR group, it was not significantly different (P = .276). CONCLUSIONS: These results indicate that pretreatment DCE-MR imaging can be potentially used for prediction of response to chemoradiation therapy of HNSCC.

Differentiation between glioblastomas and solitary brain metastases using diffusion tensor imaging

The purpose of this study is to determine whether diffusion tensor imaging (DTI) metrics including tensor shape measures such as linear and planar anisotropy coefficients (CL and CP) can help differentiate glioblastomas from solitary brain metastases. Sixty-three patients with histopathologic diagnosis of glioblastomas (22 men, 16 women, mean age 58.4 years) and brain metastases (13 men, 12 women, mean age 56.3 years) were included in this study. Contrast-enhanced T1-weighted, fluid-attenuated inversion recovery (FLAIR) images, fractional anisotropy (FA), apparent diffusion coefficient (ADC), CL and CP maps were co-registered and each lesion was semi-automatically subdivided into four regions: central, enhancing, immediate peritumoral and distant peritumoral. DTI metrics as well as the normalized signal intensity from the contrast-enhanced T1-weighted images were measured from each region. Univariate and multivariate logistic regression analyses were employed to determine the best model for classification. The results demonstrated that FA, CL and CP from glioblastomas were significantly higher than those of brain metastases from all segmented regions (p<0.05), and the differences from the enhancing regions were most significant (p<0.001). FA and CL from the enhancing region had the highest prediction accuracy when used alone with an area under the curve of 0.90. The best logistic regression model included three parameters (ADC, FA and CP) from the enhancing part, resulting in 92% sensitivity, 100% specificity and area under the curve of 0.98. We conclude that DTI metrics, used individually or combined, have a potential as a non-invasive measure to differentiate glioblastomas from metastases.

Differentiation between Glioblastomas, Solitary Brain Metastases, and Primary Cerebral Lymphomas Using Diffusion Tensor and Dynamic Susceptibility Contrast-Enhanced MR Imaging

More on the eternal question: what can we use to differentiate preoperatively glioblastomas, metastases, and lymphomas? Here, the authors investigated whether diffusion tensor imaging and gadolinium perfusion studies could be used for this purpose. They evaluated 26 GBMs, 25 brain metastases, and 16 primary cerebral lymphomas with these techniques. Basically, GBMs showed lower fractional anisotropy and higher perfusion patterns. The best predictive data obtained were the apparent diffusion coefficients from enhancing tumor regions and the perfusion (cerebral blood volume) from the peritumoral regions. Although this is probably something that we all use on a daily basis, it is nice to see it reported in such an organized and careful fashion. BACKGROUND AND PURPOSE: Glioblastomas, brain metastases, and PCLs may have similar enhancement patterns on MR imaging, making the differential diagnosis difficult or even impossible. The purpose of this study was to determine whether a combination of DTI and DSC can assist in the differentiation of glioblastomas, solitary brain metastases, and PCLs. MATERIALS AND METHODS: Twenty-six glioblastomas, 25 brain metastases, and 16 PCLs were retrospectively identified. DTI metrics, including FA, ADC, CL, CP, CS, and rCBV were measured from the enhancing, immediate peritumoral and distant peritumoral regions. A 2-level decision tree was designed, and a multivariate logistic regression analysis was used at each level to determine the best model for classification. RESULTS: From the enhancing region, significantly elevated FA, CL, and CP and decreased CS values were observed in glioblastomas compared with brain metastases and PCLs (P < .001), whereas ADC, rCBV, and rCBVmax values of glioblastomas were significantly higher than those of PCLs (P < .01). The best model to distinguish glioblastomas from nonglioblastomas consisted of ADC, CS (or FA) from the enhancing region, and rCBV from the immediate peritumoral region, resulting in AUC = 0.938. The best predictor to differentiate PCLs from brain metastases comprised ADC from the enhancing region and CP from the immediate peritumoral region with AUC = 0.909. CONCLUSIONS: The combination of DTI metrics and rCBV measurement can help in the differentiation of glioblastomas from brain metastases and PCLs.

MR-Visible Lipids and the Tumor Microenvironment

MR‐visible lipids or mobile lipids are defined as lipids that are observable using proton MRS in cells and tissues. These MR‐visible lipids are composed of triglycerides and cholesterol esters that accumulate in neutral lipid droplets, where their MR visibility is conferred as a result of the increased molecular motion available in this unique physical environment. This review discusses the factors that lead to the biogenesis of MR‐visible lipids in cancer cells and in other cell types, such as immune cells and fibroblasts. We focus on the accumulations of mobile lipids that are inducible in cultured cells by a number of stresses, including culture conditions, and in response to activating stimuli or apoptotic cell death induced by anticancer drugs. This is compared with animal tumor models, where increases in mobile lipids are observed in response to chemo‐ and radiotherapy, and to human tumors, where mobile lipids are observed predominantly in high‐grade brain tumors and in regions of necrosis. Conducive conditions for mobile lipid formation in the tumor microenvironment are discussed, including low pH, oxygen availability and the presence of inflammatory cells. It is concluded that MR‐visible lipids appear in cancer cells and human tumors as a stress response. Mobile lipids stored as neutral lipid droplets may play a role in the detoxification of the cell or act as an alternative energy source, especially in cancer cells, which often grow in ischemic/hypoxic environments. The role of MR‐visible lipids in cancer diagnosis and the assessment of the treatment response in both animal models of cancer and human brain tumors is also discussed. Although technical limitations exist in the accurate detection of intratumoral mobile lipids, early increases in mobile lipids after therapeutic interventions may be useful as a potential biomarker for the assessment of treatment response in cancer. Copyright

Cystic intracranial mass lesions: Possible role of in vivo MR spectroscopy in its differential diagnosis

Thirty-four patients showing cystic intracranial mass lesions on MR imaging were evaluated by in vivo proton MR spectroscopy (MRS) with the aim of detecting lesion-specific spectral patterns that may assist imaging in better tissue characterization. In vivo spectroscopy was performed using stimulated echo acquisition mode with echo times 20 and 270 m in all, and spin echo with echo time 135 m in 11 patients. All primary neoplasms (intra-as well as extra-axial) showed choline (3.22 ppm) resonance along with lipid and/or lactate (1.3 ppm). It was not possible to grade cystic gliomas based on N-acetyl asparate-to-choline ratio. High-grade gliomas (n = 8) showed lipid/lactate and low-grade gliomas (n = 6) showed only lactate. Seven patients with brain abscess showed resonances only from acetate (1.92 ppm), lactate (1.3 ppm) and alanine (1.5 ppm). Two cases of metastatic adenocarcinoma showed only lipid/lactate. In 7 patients with epidermoid cyst, lactate along with an unassigned resonance at 1.8 ppm was observed and could be easily differentiated from arachnoid cysts (n = 2), which showed only minimal lactate. A case of cystic meningioma could be differentiated from cystic schwannoma by the presence of alanine in the former. It is concluded that MR imaging, when combined with in vivo MRS, may help to better characterize intracranial cystic mass lesions.

Role of In Vivo Proton Magnetic Resonance Spectroscopy in the Diagnosis and Management of Brain Abscesses

OBJECTIVE In vivo proton magnetic resonance spectroscopy was performed for 24 patients with pyogenic brain abscesses, to examine the consistency of the spectral patterns and to observe the changes in metabolites with treatment. METHODS Localized proton spectra were obtained from 4- to 8-ml volumes in the abscesses, using stimulated echo acquisition mode and spin echo sequences. Twenty-two patients were treated with combined surgical and medical therapy, and two patients were treated conservatively. High-resolution magnetic resonance spectroscopy was performed for 15 samples of abscesses obtained from these patients, to confirm the assignments of resonances seen in vivo. Postaspiration studies were performed for 12 patients treated with combined medical and surgical therapy and 2 patients treated medically. RESULTS Lactate and amino acids were seen in spectra for all patients, irrespective of the time of spectroscopy after the onset of combined medical and surgical therapy. Acetate and pyruvate disappeared after 1 week of combined treatment. CONCLUSION It was concluded that spectral patterns for brain abscesses are consistent and specific and can assist in the noninvasive diagnosis of abscesses. Responses to combined treatment could be monitored by showing the changes in metabolite patterns in serial spectroscopic studies.

In vivo and ex vivo MRI detection of localized and disseminated neural stem cell grafts in the mouse brain

The application of stem cells as delivery vehicles opens up the opportunity for targeting therapeutic proteins to the damaged or degenerating central nervous system. Neural stem cell (NSC) lines have been shown to engraft, differentiate and correct certain central nervous system diseases. The present study was performed to test the ability of magnetic resonance imaging (MRI) in detecting transplanted NSCs under conditions of limited migration in the normal adult mouse brain versus widespread migration when the cells are transplanted neonatally. The C17.2 NSC line was labeled in vitro with superparamagnetic iron oxide (SPIO) particles and the labeled cells were implanted intracranially. Serial in vivo gradient echo MR imaging was performed using a 4.7 T horizontal bore magnet. High resolution ex vivo images of the isolated brains were performed at 9.4 T, and the presence of iron was correlated with Prussian blue staining in histological sections. Adult animals injected with SPIO-labeled stem cells exhibited hypointense regions near the injection site that were observed up to 32 days after injection. In neonatally transplanted animals, MR signal intensity from transplanted NSCs was not apparent in in vivo imaging but ex vivo MR images revealed small hypointense regions throughout the brain including the olfactory bulbs, cortex and the cerebellum, reflecting the wide distribution of the engrafted cells. These regions were correlated with Prussian blue staining, which confirmed the presence of SPIO particles inside the engrafted cells. We have shown that MRI is capable of differentiating localized and widespread engraftment of C17.2 stem cells in the central nervous system.