Placing Regions Of Interest Research Articles

Automated Region of Interest Detection Method in Scintigraphic Glomerular Filtration Rate Estimation.

The glomerular filtration rate (GFR) is a crucial index to measure renal function. In daily clinical practice, the GFR can be estimated using the Gates method, which requires the clinicians to define the region of interest (ROI) for the kidney and the corresponding background in dynamic renal scintigraphy. The manual placement of ROIs to estimate the GFR is subjective and labor-intensive, however, making it an undesirable and unreliable process. This work presents a fully automated ROI detection method to achieve accurate and robust GFR estimations. After image preprocessing, the ROI for each kidney was delineated using a shape prior constrained level set (spLS) algorithm and then the corresponding background ROIs were obtained according to the defined kidney ROIs. In computer simulations, the spLS method had the best performance in kidney ROI detection compared with the previous threshold method (threshold) and the Chan-Vese level set (cvLS) method. In further clinical applications, 223 sets of 99mTc-diethylenetriaminepentaacetic acid renal scintigraphic images from patients with abnormal renal function were reviewed. Compared with the former ROI detection methods (threshold and cvLS), the GFR estimations based on the ROIs derived by the spLS method had the highest consistency and correlations (r = 0.98, p < 0.001) with the reference estimated by experienced physicians. The results indicate that the proposed automated ROI detection method has great potential in automated ROI detection for accurate and robust GFR estimation in dynamic renal scintigraphy.

Virtual Computed Tomography Colonography: Evaluation of 2D and Virtual 3D Image Quality of Sub-mSv Examinations Enabled by Third-generation Dual Source Scanner Featuring Tin Filtering

To evaluate two- and three-dimensional (2D and 3D) image quality of sub-milliSievert (mSv) computed tomography (CT) colonography utilizing a third-generation dual source CT scanner featuring a tin filter. We retrospectively evaluated 26 consecutive patients who underwent third-generation dual source CT colonography, nine with the standard-dose clinical-scan protocol (SDP) and 17 with a low-dose protocol (LDP) featuring a tin filter. Radiation dose was evaluated by volume computed tomography dose index (CTDIvol), dose length product (DLP), effective dose (E), and size-specific dose estimate. Objective image quality was evaluated utilizing signal-to-noise ratio (SNR) derived from standardized placed regions of interest on the transverse 2D images and the ratio of SNR/CTDIvol (normalized SNR). Two radiologists in consensus assessed subjective image quality of the virtual 3D images. There were no significant differences in subjective image quality (P = .661). All examinations were rated "excellent" or "good" for diagnostic confidence. The mean total for DLP/E was 143.4 ± 29.8 mGy/3.00 ± 0.40 mSv in the SDP and therefore significantly higher than in the LDP with 36.9 ± 8.7 mGy/0.75 ± 0.16 mSv (P < .001). The SNR was 8.9 ± 2.1 in the SDP and 4.9 ± 0.8 in the LDP. Third-generation dual source CT featuring a tin filter enables consistent sub-mSv colonography without substantially impairing image quality.

Two Different Methods of Region-of-Interest Placement for Differentiation of Benign and Malignant Breast Lesions by Apparent Diffusion Coefficient Value

Purpose:We aimed to investigate the influence of different methods of region-of-interest (ROI) placement on apparent diffusion coefficient (ADC) values in breast tumours and their accuracy in differentiating benign versus malignant tumors in mass and nonmass lesions.Methods and Materials:In this prospective study, 79 patients with 98 breast lesions, from 2015 until 2017, were investigated by 1.5-T breast MRI. Histopathology evaluation were done for all malignant lesions and most of the benign ones. ADC values were measured in normal breast tissue and by two ways of ROI placement in the breast lesions (mass and non-mass): 1- ROI covering the whole lesion, 2- ROI in the highest part (most restricted area) of the lesion in DWI images. The accuracy of these two approaches were compared.Results:The age range was 17-68 years with mean age 43.3 ± 9.9 years. 49% of the lesions were benign and 51% of tumors were malignant. Our results revealed that the measured ADC values in normal breast tissue were higher than breast lesions (P≤0.01). Appropriate cut off determination in non-mass was not valid by both methods, but in mass in the first way was 1.45×10-3mm2/s and in the most restricted part was 1.16×10-3 mm2/s. ADC values differed significantly between the two ways of ROI placement in mass lesions (P<.001). Most restricted part ADC showed the best diagnostic performance in mass lesions with area under curve 0.88 versus 0.82.Conclusion:ROI placement has significant impact on the meseaured ADC values of breast lesions and ROIs in most restricted parts were more accurate than whole-lesion ROIs. Cut-off values differed significantly based on the methods of measurement.

Enhancement and Intensity Inhomogeneity Correction of Diffusion-Weighted MR Images of Neonatal and Infantile Brain Using Dynamic Stochastic Resonance

Imaging of infantile/neonatal brain mandates tailored radio frequency coils (RF coils) to achieve a homogeneous field over a small region of interest (ROI). Most centers, however, perform pediatric imaging using adult RF coils only as procurement of tailored pediatric coils might prove quite expensive. This practice may not scientifically justified, whereas the image post-processing techniques reduces the deleterious effects of magnetic field inhomogeneity due to a small ROI being scanned in a large RF coil. Further, the eccentric placement of ROI within the RF coil perpetuates the field inhomogeneity within the scanned region. Hence, the structures closer to the coil appear brighter than those farther away giving rise to a ‘shading artefact’. The effect even more accentuates in weak signal sequences like diffusion-weighted imaging (DWI). The proposed method significantly removes shading artefact of real DWI and synthetic T1 and T2 weighted magnetic resonance images. Dynamic stochastic resonance (DSR) intelligently uses the coefficient of discrete cosine transform of an image for brightness normalization and image enhancement simultaneously. The quality of the output image depends on the bistability parameters associated with the dynamic equation. Particle swarm optimization (PSO) tunes these bistability parameters for the entropy minimization of different group of tissues individually. The proposed algorithm outperforms the post processing based homomorphic filtering, local entropy minimization with spline model and multiplicative intrinsic component optimization methods. The proposed PSO based DSR approach may be helpful in accurate diagnosis.

Free-water and free-water corrected fractional anisotropy in primary and premotor corticospinal tracts in chronic stroke.

Measures from diffusion MRI have been used to characterize the corticospinal tract in chronic stroke. However, diffusivity can be influenced by partial volume effects from free-water, region of interest placement, and lesion masking. We collected diffusion MRI from a cohort of chronic stroke patients and controls and used a bitensor model to calculate free-water corrected fractional anisotropy (FAT ) and free water (FW) in the primary motor corticospinal tract (M1-CST) and the dorsal premotor corticospinal tract (PMd-CST). Region of interest analyses and whole-tract slice-by-slice analyses were used to assess between-group differences in FAT and FW in each tract. Correlations between FAT and FW and grip strength were also examined. Following lesion masking and correction for multiple comparisons, relative increases in FW were found for the stroke group in large portions of the M1-CST and PMd-CST in the lesioned hemisphere. FW in cortical regions was the strongest predictor of grip strength in the stroke group. Our findings also demonstrated that FAT is sensitive to the direct effects of the lesion itself, thus after controlling for the lesion, differences in FAT in nonlesioned tissue were small and generally similar between hemispheres and groups. Our observations suggest that FW may be a robust biological measurement that can be used to assess microstructure in residual white matter after stroke. Hum Brain Mapp 38:4546-4562, 2017. © 2017 Wiley Periodicals, Inc.

Diffusion-weighted imaging of breast lesions: Region-of-interest placement and different ADC parameters influence apparent diffusion coefficient values.

To investigate the influence of region-of-interest (ROI) placement and different apparent diffusion coefficient (ADC) parameters on ADC values, diagnostic performance, reproducibility and measurement time in breast tumours. In this IRB-approved, retrospective study, 149 histopathologically proven breast tumours (109 malignant, 40 benign) in 147 women (mean age 53.2) were investigated. Three radiologists independently measured minimum, mean and maximum ADC, each using three ROI placement approaches:1 - small 2D-ROI, 2 - large 2D-ROI and 3 - 3D-ROI covering the whole lesion. One reader performed all measurements twice. Median ADC values, diagnostic performance, reproducibility, and measurement time were calculated and compared between all combinations of ROI placement approaches and ADC parameters. Median ADC values differed significantly between the ROI placement approaches (p < .001). Minimum ADC showed the best diagnostic performance (AUC .928-.956), followed by mean ADC obtained from 2D ROIs (.926-.94). Minimum and mean ADC showed high intra- (ICC .85-.94) and inter-reader reproducibility (ICC .74-.94). Median measurement time was significantly shorter for the 2D ROIs (p < .001). ROI placement significantly influences ADC values measured in breast tumours. Minimum and mean ADC acquired from 2D-ROIs are useful for the differentiation of benign and malignant breast lesions, and are highly reproducible, with rapid measurement. • Region of interest placement significantly influences apparent diffusion coefficient of breast tumours. • Minimum and mean apparent diffusion coefficient perform best and are reproducible. • 2D regions of interest perform best and provide rapid measurement times.

Diagnostic accuracy of hepatorenal index in the detection and grading of hepatic steatosis.

The objectives of our study were to assess the accuracy of hepatorenal index (HRI) in detection and grading of hepatic steatosis and to evaluate various factors that can affect the HRI measurement. Forty-five patients, who had undergone an abdominal sonographic examination within 30 days of liver biopsy, were enrolled. The HRI was calculated as the ratio of the mean brightness levels of the liver and renal parenchymas. The effect of the measurement technique on the HRI was evaluated by using various sizes, depths, and locations of the regions of interest (ROIs) in the liver. The measurements were obtained by two observers. The HRI was compared with the subjective grading of steatosis. The optimal HRI cutoff to detect steatosis was 2.01, yielding a sensitivity of 62.5% and specificity of 95.2%. Subjective grading had a sensitivity of 87.5% and specificity of 62.5%. HRIs of the hepatic steatosis group were statistically different from the no-steatosis group (p < 0.05). However, there was no statistically significant difference between mild steatosis and no-steatosis groups (p value = 0.72). There was a strong correlation between different HRIs based on variable placements of ROIs, except when the ROIs were positioned randomly. Interclass correlation coefficient for measurements performed by two observers was 0.74 (confidence interval: 0.58-0.86). The HRI is an effective tool for detecting hepatic steatosis. It provides similar accuracy for different methods of ROI placement (except for random placement) and has good interobserver agreement. It, however, is unable to effectively differentiate between absent and mild steatosis. © 2016 Wiley Periodicals, Inc. J Clin Ultrasound 44:580-586, 2016.

Ultrasound Shear Wave Elastography for Liver Disease. A Critical Appraisal of the Many Actors on the Stage.

Ultrasound Shear Wave Elastography for Liver Disease. A Critical Appraisal of the Many Actors on the Stage.

Multi-Parametric MRI and Texture Analysis to Visualize Spatial Histologic Heterogeneity and Tumor Extent in Glioblastoma.

BackgroundGenetic profiling represents the future of neuro-oncology but suffers from inadequate biopsies in heterogeneous tumors like Glioblastoma (GBM). Contrast-enhanced MRI (CE-MRI) targets enhancing core (ENH) but yields adequate tumor in only ~60% of cases. Further, CE-MRI poorly localizes infiltrative tumor within surrounding non-enhancing parenchyma, or brain-around-tumor (BAT), despite the importance of characterizing this tumor segment, which universally recurs. In this study, we use multiple texture analysis and machine learning (ML) algorithms to analyze multi-parametric MRI, and produce new images indicating tumor-rich targets in GBM.MethodsWe recruited primary GBM patients undergoing image-guided biopsies and acquired pre-operative MRI: CE-MRI, Dynamic-Susceptibility-weighted-Contrast-enhanced-MRI, and Diffusion Tensor Imaging. Following image coregistration and region of interest placement at biopsy locations, we compared MRI metrics and regional texture with histologic diagnoses of high- vs low-tumor content (≥80% vs <80% tumor nuclei) for corresponding samples. In a training set, we used three texture analysis algorithms and three ML methods to identify MRI-texture features that optimized model accuracy to distinguish tumor content. We confirmed model accuracy in a separate validation set.ResultsWe collected 82 biopsies from 18 GBMs throughout ENH and BAT. The MRI-based model achieved 85% cross-validated accuracy to diagnose high- vs low-tumor in the training set (60 biopsies, 11 patients). The model achieved 81.8% accuracy in the validation set (22 biopsies, 7 patients).ConclusionMulti-parametric MRI and texture analysis can help characterize and visualize GBM’s spatial histologic heterogeneity to identify regional tumor-rich biopsy targets.

Qualitative and quantitative diffusion-weighted imaging of the breast at 3T - A useful adjunct to contrast-enhanced MRI in characterization of breast lesions.

Objective:To distinguish between benign and malignant breast lesions on the basis of their signal intensity on diffusion-weighted imaging and their apparent diffusion coefficient (ADC) values at 3 T MRI, along with histopathological correlation.Materials and Methods:A retrospective analysis of 500 patients who underwent 3 T MRI between August 2011 and May 2013 was done. Of these, 226 patients with 232 lesions that were proved by histopathology were included in the study. ADC values were calculated at b values of 0, 1000, and 1500 s/mm2 after identification on contrast-enhanced images and appropriate ROI(Region of interest) placement. ADC value and histopathology correlation was analyzed.Results:Out of 232 lesions, 168 lesions were histologically malignant and 64 were histologically benign. With an ADC cut-off value of 1.1 ×10−3 mm2/s for malignant lesions, a sensitivity of 92.80% and specificity of 80.23% was obtained. Out of 12/232 false-negative lesions, 6 were mucinous carcinoma in which a high ADC value of 1.8-1.9 ×10−3 mm2/s was obtained. Purely DCIS (Ductal carcinoma in situ) lesions presenting as non-mass-like enhancement had a high ADC value of 1.2-1.5 ×10−3 mm2/s, thereby reducing specificity.Conclusion:Diffusion-weighted Imaging and quantitative assessment by ADC values may act as an effective parameter in increasing the diagnostic accuracy and specificity of contrast-enhanced breast MRI in characterization of breast lesions.

Adaptive iterative dose reduction 3D (AIDR 3D) vs. filtered back projection: radiation dose reduction capabilities of wide volume and helical scanning techniques on area-detector CT in a chest phantom study.

Computed tomography (CT) has important roles for lung cancer screening, and therefore radiation dose reduction by using iterative reconstruction technique and scanning methods receive widespread attention. To evaluate the effect of two reconstruction techniques (filtered back projection [FBP] and adaptive iterative dose reduction using three-dimensional processing [AIDR 3D]) and two acquisition techniques (wide-volume scan [WVS] and helical scan as 64-detector-row CT [64HS]) on the lung nodule identifications of using a chest phantom. A chest CT phantom including lung nodules was scanned using WVS and 64HS at nine different tube currents (TCs; range, 270-10 mA). All CT datasets were reconstructed with AIDR 3D and FBP. Standard deviation (SD) measurements by region of interest placement and qualitative nodule identifications were statistically compared. 64HS and WVS were evaluated separately, and FBP images acquired with 270 mA was defined as the standard reference. SDs of all datasets with AIDR 3D showed no significant differences (P > 0.05) with standard reference. When comparing nodule identifications, area under the curve on WVS with AIDR 3D with TC <30 mA, on 64HS with AIDR 3D with TC <40 mA, and on reconstructions with FBP and each scan method with TC <60 mA was significantly lower than with standard reference (P < 0.05). With the same TC and reconstruction, SDs and nodule identifications of WVS were not significantly different from 64HS (P > 0.05). In term of SD of lung parenchyma and nodule identification, AIDR 3D can achieve more radiation dose reduction than FBP and there is no significant different between WVS and 64HS.

Comparison of the Diagnostic Performances of Three Techniques of ROI Placement for ADC Measurements in Pancreatic Adenocarcinoma

To prospectively investigate and compare three techniques of region of interest (ROI) placement for apparent diffusion coefficient (ADC) measurements in patients with pancreatic ductal adenocarcinoma (PDAC). Twenty-one patients with surgical pathology-proven PDAC and 18 healthy volunteers were included. Respiratory-triggered single-shot echo-planar diffusion-weighted imaging (b values = 0, 600 s/mm(2)) was used to calculate the ADC maps across all participants. Three readers independently measured the ADCs according to three ROI methods: whole-volume, single-slice, and small solid samples of tumor. Mean ADCs for the healthy pancreas were calculated using three measurements from pancreatic head to tail, and ADCs of distal pancreas to the tumor were also measured. The interobserver variability for the three techniques was measured using the interclass correlation coefficient. The diagnostic performances were calculated and compared using the receiver operating characteristic curves (ROC). All the ADCs measured from the three ROI placements on PDAC were significantly lower than that from the normal pancreas. ADCs of solid tumor samples were significantly lower than that measured from whole volume or single slice (both P < .001). Only the ADCs measured from the solid sample ROI placements on tumor were observed significantly lower than the ADC of distal pancreatic parenchyma (P = .005). Areas under the ROC for the identification of PDAC, based on small solid samples, single-slice and whole-volume ROIs, respectively, were 0.939, 0.791, and 0.735. ADC based on the small solid samples of tumor provided the highest diagnostic performance in assessing PDAC and was more accurate than ADCs measured from single-slice or whole-volume ROI.

Radiologic-pathologic analysis of quantitative 3D tumour enhancement on contrast-enhanced MR imaging: a study of ROI placement.

To investigate the influence of region-of-interest (ROI) placement on 3D tumour enhancement [Quantitative European Association for the Study of the Liver (qEASL)] in hepatocellular carcinoma (HCC) patients treated with transcatheter arterial chemoembolization (TACE). Phase 1: 40 HCC patients had nine ROIs placed by one reader using systematic techniques (3 ipsilateral to the lesion, 3 contralateral to the lesion, and 3 dispersed throughout the liver) and qEASL variance was measured. Intra-class correlations were computed. Phase 2: 15 HCC patients with histosegmentation were selected. Six ROIs were systematically placed by AC (3 ROIs ipsilateral and 3 ROIs contralateral to the lesion). Three ROIs were placed by 2 radiologists. qEASL values were compared to histopathology by Pearson's correlation, linear regression, and median difference. Phase 1: The dispersed method (abandoned in phase 2) had low consistency and high variance. Phase 2: qEASL correlated strongly with pathology in systematic methods [Pearson's correlation coefficient = 0.886 (ipsilateral) and 0.727 (contralateral)] and in clinical methods (0.625 and 0.879). However, ipsilateral placement matched best with pathology (median difference: 5.4 %; correlation: 0.89; regression CI: [0.904, 0.1409]). qEASL is a robust method with comparable values among tested placements. Ipsilateral placement showed high consistency and better pathological correlation. Ipsilateral and contralateral ROI placement produces high consistency and low variance. Both ROI placement methods produce qEASL values that correlate well with histopathology. Ipsilateral ROI placement produces best correlation to pathology along with high consistency.

Discussion about Improvement of Stability of the Scan Timing by Placing Small ROI in Cerebral 3D-CTA

In three-dimensional computed tomography angiography (3D-CTA) in our facility, we usually scan the volume of the brain according to the bolus tracking method. Fluoroscopic slice is placed at the Willis’s ring and the timing of scan is determined subjectively by a radiological technologist after strong enhancement of the basal cerebral artery is confirmed. In these procedures, however, variation of scan timing is often problematic. Therefore, we design the surpassing method to place the small region-of-interest (ROI) at the basal cerebral arteries and to start CT scan automatically. In this protocol, the fluoroscopic slices of the distal internal carotid arteries are selected referring to the precontrast volume data, small ROIs are set in bilateral internal carotid arteries, and scan trigger of CT is started automatically at the threshold of 170 HU. The maximum 80 mL of iodine contrast agent 300 mgI/mL is injected intravenously at the rate of 4.0 mL/sec, and the volume of the arterial phase is scanned automatically. We measure ROIs at the internal carotid arteries based on the obtained volume data of arterial phase and estimate the optimal scan timings from the fluoroscopic CT images reformatted at the intervals of 0.1 sec. In 38 of 53 patients, placement of the small ROIs is succeeded and automatic or manual CT scan is performed. In the patients who succeed in placement of the small ROIs, optimal scan timing of the arterial phase is obtained, while in the patients who fail placement of the small ROIs, a large variation is observed in their scan timings. Their results suggest that more stable scanning of the arterial phase is available by means of small ROI placement and automatic scanning. The clinical significance is large because the stability and reproducibility of the examination provide a quantitative analysis and more accurate diagnosis.

Inter- and intra-rater reliability of diffusion tensor imaging parameters in the normal pediatric spinal cord.

To assess inter- and intra-rater reliability (agreement) between two region of interest (ROI) methods in pediatric spinal cord diffusion tensor imaging (DTI). Inner-Field-of-View DTI data previously acquired from ten pediatric healthy subjects (mean age = 12.10 years) was used to assess for reliability. ROIs were drawn by two neuroradiologists on each subject data twice within a 3-mo interval. ROIs were placed on axial B0 maps along the cervical spine using free-hand and fixed-size ROIs. Agreement analyses for fractional anisotropy (FA), axial diffusivity, radial diffusivity and mean diffusivity were performed using intra-class-correlation (ICC) and Cronbach's alpha statistical methods. Inter- and intra-rater agreement between the two ROI methods showed moderate (ICC = 0.5) to strong (ICC = 0.84). There were significant differences between raters in the number of pixels selected using free-hand ROIs (P < 0.05). However, no significant differences were observed in DTI parameter values. FA showed highest variability in ICC values (0.10-0.87). Cronbach's alpha showed moderate-high values for raters and ROI methods. The study showed that high reproducibility in spinal cord DTI can be achieved, and demonstrated the importance of setting detailed methodology for post-processing DTI data, specifically the placement of ROIs.

PS-117 Preterm Cerebral Microcirculation Assessed With Colour Doppler: A Pilot Study

Background and aims Pilot study to explore feasibility of a colour Doppler technique for monitoring cerebral perfusion at the level of microvessels. Methods Between March 1st, 2011, and January 30th, 2013, all admitted infants born before 29 weeks of gestation were eligible for Doppler imaging. Perfusion images were acquired in a standard coronal plane. Image quality was assessed by two authors (MR, PG). The region of interest (ROI) was manually selected. A segmentation tool was developed to separate colour data from the greyscale 2D images, leading to a percentage and number of colour pixels in the image (Doppler colour index; DCI). Intra- and interobserver agreement was analysed. Results Intra- and interobserver agreement for placement of ROIs was good (bias -0.24 resp. -0.74 percentage points). Colour Doppler was able to depict microvessels in cortex, white matter and deep grey matter. The median DCI in a region of cortex-white matter was 7.8% with a wide range (1.4%-25.6%). There was no significant difference between the left and right hemisphere (Mann-Whitney U, P-value 0.61). Clinically relevant observations were tabulated, e.g. distant effect of GMH on regional perfusion. Conclusion Sonographic small vessel visualisation may help understand pathogenetic mechanisms related to perfusion and is valuable to monitor effects of treatment. ![Abstract PS-117 Figure 1][1] Abstract PS-117 Figure 1 [1]: pending:yes

Reconstruction of semiautomated cardiac regions of interest using iodine-123 metaiodobenzylguanidine myocardial scintigraphy.

Analysis using cardiac iodine-123 metaiodobenzylguanidine (MIBG) scintigraphy with regions of interest (ROIs) is useful for assessing myocardial sympathetic activity. However, manual placement of the cardiac ROI is sometimes difficult because myocardial MIBG uptake is reduced in patients with heart failure. A new method was developed to reconstruct the semiautomated cardiac ROI in a sympathetic denervated heart. Using dynamic planar data, a summed image was generated and the matrix size was changed. Then, the radial count profiles originating from the center of the left ventricle were generated to extract the myocardial count profiles. An asymmetric Gaussian distribution was fitted to each profile and the epicardial border was defined by the threshold method. This program was tested in 50 patients, and its reproducibility was validated when compared with the manual tracing method. The semiautomated method yielded a better quality image compared with the standard image with higher counts. Cardiac ROIs were generated successfully in each patient within normal limits. The intraobserver and interobserver agreements were excellent (P<0.0001 each). This approach showed a significantly higher consistency in measuring the heart-to-mediastinum ratio as compared with the manual tracing method (P<0.05). The semiautomated method is useful in generating cardiac ROIs with high reproducibility in myocardial MIBG imaging.

Automated analysis of dynamic Ca2+ signals in image sequences.

Intracellular Ca(2+) signals are commonly studied with fluorescent Ca(2+) indicator dyes and microscopy techniques. However, quantitative analysis of Ca(2+) imaging data is time consuming and subject to bias. Automated signal analysis algorithms based on region of interest (ROI) detection have been implemented for one-dimensional line scan measurements, but there is no current algorithm which integrates optimized identification and analysis of ROIs in two-dimensional image sequences. Here an algorithm for rapid acquisition and analysis of ROIs in image sequences is described. It utilizes ellipses fit to noise filtered signals in order to determine optimal ROI placement, and computes Ca(2+) signal parameters of amplitude, duration and spatial spread. This algorithm was implemented as a freely available plugin for ImageJ (NIH) software. Together with analysis scripts written for the open source statistical processing software R, this approach provides a high-capacity pipeline for performing quick statistical analysis of experimental output. The authors suggest that use of this analysis protocol will lead to a more complete and unbiased characterization of physiologic Ca(2+) signaling.

Automated Analysis of Dynamic Ca&lt;sup&gt;2+&lt;/sup&gt; Signals in Image Sequences

Intracellular Ca2+ signals are commonly studied with fluorescent Ca2+ indicator dyes and microscopy techniques. However, quantitative analysis of Ca2+ imaging data is time consuming and subject to bias. Automated signal analysis algorithms based on region of interest (ROI) detection have been implemented for one-dimensional line scan measurements, but there is no current algorithm which integrates optimized identification and analysis of ROIs in two-dimensional image sequences. Here an algorithm for rapid acquisition and analysis of ROIs in image sequences is described. It utilizes ellipses fit to noise filtered signals in order to determine optimal ROI placement, and computes Ca2+ signal parameters of amplitude, duration and spatial spread. This algorithm was implemented as a freely available plugin for ImageJ (NIH) software. Together with analysis scripts written for the open source statistical processing software R, this approach provides a high-capacity pipeline for performing quick statistical analysis of experimental output. The authors suggest that use of this analysis protocol will lead to a more complete and unbiased characterization of physiologic Ca2+ signaling.

Parametric Response Maps of Perfusion MRI May Identify Recurrent Glioblastomas Responsive to Bevacizumab and Irinotecan

BackgroundPerfusion weighted imaging (PWI) can be used to measure key aspects of tumor vascularity in vivo and recent studies suggest that perfusion imaging may be useful in the early assessment of response to angiogenesis inhibitors. Aim of this work is to compare Parametric Response Maps (PRMs) with the Region Of Interest (ROI) approach in the analysis of tumor changes induced by bevacizumab and irinotecan in recurrent glioblastomas (rGBM), and to evaluate if changes in tumor blood volume measured by perfusion MRI may predict clinical outcome.Methods42 rGBM patients with KPS ≥50 were treated until progression, as defined by MRI with RANO criteria. Relative cerebral blood volume (rCBV) variation after 8 weeks of treatment was calculated through semi-automatic ROI placement in the same anatomic region as in baseline. Alternatively, rCBV variations with respect to baseline were calculated into the evolving tumor region using a voxel-by-voxel difference. PRMs were created showing where rCBV significantly increased, decreased or remained unchanged.ResultsAn increased blood volume in PRM (PRMCBV+) higher than 18% (first quartile) after 8 weeks of treatment was associated with increased progression free survival (PFS; 24 versus 13 weeks, p = 0.045) and overall survival (OS; 38 versus 25 weeks, p = 0.016). After 8 weeks of treatment ROI analysis showed that mean rCBV remained elevated in non responsive patients (4.8±0.9 versus 5.1±1.2, p = 0.38), whereas decreased in responsive patients (4.2±1.3 versus 3.8±1.6 p = 0.04), and re-increased progressively when patients approached tumor progression.ConclusionsOur data suggest that PRMs can provide an early marker of response to antiangiogenic treatment and warrant further confirmation in a larger cohort of GBM patients.