Weighted Contrast Enhancement Research Articles

Measurement of treatment dependent glioblastoma cell density in T1- weighted contrast enhancement at autopsy.

e14035 Background: With an average overall survival of 12-18 months, glioblastoma has a particularly grim diagnosis. Standard treatment of glioblastoma, following detection on MRI, is surgical resection followed by radiation therapy and chemotherapy and is monitored through MR imaging. Glioblastoma has a unique heterogenous nature that complicates visualization of subtly enhancing tumor. This study used autopsy tissue samples taken from glioblastoma patients with varying treatment, to examine the effects of treatment on cell density within regions of contrast enhancement, using T1-weighted subtraction maps (T1S) from the last MR images to death. Methods: Eight patients diagnosed with glioblastoma at autopsy were recruited for this study. Two patients had no treatment and six received a combination of chemo-radiation and other treatments, including but not limited to bevacizumab (Bev) and TTFields therapy. At autopsy, whole brain samples were sliced axially aligned to the patient’s final MRI to death. Time between last MRI and death ranged from 4-27 days (mean 16 days). Overall survival (OS) ranged from 4-538 days (mean 307 days). Large tissue samples were taken from regions of suspected tumor or treatment effect, for a total of 18 tissue samples. Tissue samples were processed, H&E stained, and digitized at 40X resolution (Huron Slide Scanner). Cell density (cells/mm2) was calculated using digital histology. T1S were created for each patient by subtracting intensity normalized T1 weighted images from T1 post contrast images (T1C). Digital histology was aligned and resampled into MRI space using manual control point registration. Mixed effect models were used to compare differences in cell density across contrast enhancement (T1SE vs. NE) as well as across treatment groups (treatment vs. no treatment). Results: Cellularity was compared across regions of T1S enhancement (T1SE) and non-enhancement (NE) within manually selected regions of interest. Cell density compared between regions of T1SE and NE was not different (p=0.219). Total cell density was increased in patients who had received treatment compared to no treatment in both regions of T1SE and NE (p=0.014). Conclusions: Overall, cell density was increased in patients who had received treatment after diagnosis of glioblastoma. Additional research is needed to examine the extent of treatment’s effect on cellularity of glioblastoma. This work begins to characterize the use of T1S in evaluating glioblastoma tumor burden in patients with varying treatment histories.[Table: see text]

Assessment of Residual Tumor After Resection of Glioma: A Magnetic Resonance Spectroscopic Study

Background: Detection of actual residual tumor extent after resection of gliomas is important for further treatment implications. Conventional MRI features such as T1 weighted contrast enhancement or T2 weighted hyperintensity are not strong indicators of the tumor. Therefore, it is needed to use advanced metabolic imaging such as magnetic resonance spectroscopy (MRS). Objectives: This work reports the contrast between MRS defining metabolic alteration and imaging features of residual tumor after glioma resection. Objectives: This work reports the contrast between MRS defining metabolic alteration and imaging features of residual tumor after glioma resection. Methods: Eighteen patients with glioma after tumor resection were included in the study. Routine MRI sequences and multi-voxel MRS were obtained. Metabolic regions of interest (ROI) were defined for Cho/NAA and Cho/Cr in different thresholds. Imaging ROI for residual tumor (ROI-t) was defined on conventional MR images. Area of each ROI, the distance between ROI centers, and dice coefficient for the evaluation of similarity between imaging and metabolic ROIs were calculated. Results: Maximum similarity and minimum distance of ROI centers were determined between ROI of Cho/NAA > 1.7 and ROI-t. For Cho/Cr, the maximum similarity was determined in > 1.5. Conclusions: Findings of the present study propose that MRS could be a proper detector for residual tumor after surgical treatment of glioma.

A continuous-infusion dynamic MRI model at 3.0 Tesla for the serial quantitative evaluation of microvascular proliferation in an animal model of glioblastoma multiforme.

To develop a continuous-infusion dynamic MRI technique to characterize tumor-associated microvascular proliferation (MVP) in a rat brain model of glioblastoma multiforme. The proposed model assumes effects due to tumor-associated MVP (eg, vascular permeability, Ktrans ; intravascular plasma fraction, vp ) cannot be individually separated and solves for a single parameter (kvasc ) that quantifies the T1 -weighted contrast enhancement from dynamic images acquired during continuous contrast agent (CA) infusion. Untreated C6 tumor-bearing animals (N = 6) were serially imaged on postoperative days (PODs) 14 and 18 with a 3 Tesla clinical scanner utilizing a dynamic spatial and temporal resolution of 0.38 × 0.38 × 1.5 mm3 and 3.47 s, respectively. An association was present between PODs 14 and 18 for median tumor kvasc (Pearson's r = 0.94, P = 0.0052) and CA concentration ([CA], derived from pre- and postcontrast R1 maps; r = 0.94, P = 0.0054). On POD 18, there was a voxel-based association between kvasc and [CA] within each tumor (0.45 < r < 0.82, P < 0.001). However, voxel-based subregions demonstrated a reduced association between kvasc and [CA] (N = 5; -0.08 < r < 0.22, P > 0.05) or an inverse association (N = 1; r = -0.28, P = 0.001), indicating differences between locations of vascular permeability and subsequent CA pooling in tumors. The continuous-infusion method may provide a quantitative measure for characterizing and monitoring tumor-associated MVP. Magn Reson Med 78:1824-1838, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

BiTA/SWCE: Image Enhancement With Bilateral Tone Adjustment and Saliency Weighted Contrast Enhancement

Researchers have proposed various image enhancement methods to make images better correlate to the human visual system. This letter proposed an innovative image enhancement framework that combines bilateral tone adjustment (BiTA) and saliency-weighted contrast enhancement (SWCE) methods. Unlike most curve-based global contrast enhancement methods, BiTA enhances the mid-tone regions that normally contain important scenes, in addition to the bright and dark regions. For local contrast enhancement, SWCE integrates the concept of image saliency into a simple filter-based contrast enhancement method. Regions with higher saliency values, which indicate that the regions have a higher extent of human interest, deserve a greater degree of enhancement. In addition, this letter presents the ratio of saliency-weighted relative entropy to noise to evaluate the enhancement quality. Simulation results show that the proposed schemes achieve high contrast enhancement with little noise and great image quality.