Summarizing the 4D image stack of ultrafast dynamic contrast enhancement MRI of breast cancer in 3D using color intensity projections.

BACKGROUND: Each ultrafast dynamic contrast-enhanced (DCE) MRI sequence for breast cancer generates thousands of images in a 4D stack that need to be reviewed by a radiologist. PURPOSE: To assess whether color intensity projections (CIP) effectively summarizes-using only the time of arrival (ToA) and amount of signal enhancement (AoE) of the contrast agent-the thousands of ultrafast images. STUDY TYPE: Retrospective cohort clinical trial. SUBJECTS: The study included 89 patients who had been scanned with an MRI beast protocol, of which 26 had breast cancer and 63 did not. FIELD STRENGTH/SEQUENCE: The 115-second ultrafast DCE sequence at 3T acquired 19 consecutive frames every 4.26 seconds with 152 slices per frame, yielding a 4D stack with 2888 2D images for each of water and fat. ASSESSMENT: For each slice of the water 4D stack a single CIP image was generated that encoded the ToA in the hue (red, orange, yellow, green, cyan, blue) and AoE in the brightness. Each of three experienced radiologists assigned a Breast Imaging and Reporting Data System (BI-RADS) score for each patient, first using only the CIP images, and subsequently using both CIP and the full 4D stack. STATISTICAL TESTS: The one-sided Fisher's exact test was used to determine statistical significance of both the sensitivity and specificity between the CIP alone and the CIP plus 4D stack. RESULTS: All malignancies were detected using only CIP by at least one of the radiologists. The CIP and CIP+4D sensitivities for reader 1 were 96% and 96% (P = 0.57), specificities were 59% and 65% (P = 0.29). For reader 2, the values were 96% and 100% (P = 0.51) with 62% and 71% (P = 0.17). For reader 3 the values were 92% and 96% (P = 0.50) with 51% and 62% (P = 0.07). DATA CONCLUSION: With a 95% sensitivity, CIP provides an effective summary of ultrafast DCE images of breast cancer. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:1391-1399.

Performance of five research-domain automated WM lesion segmentation methods in a multi-center MS study.

BACKGROUND AND PURPOSE: In vivoidentification of white matter lesions plays a key-role in evaluation of patients with multiple sclerosis (MS). Automated lesion segmentation methods have been developed to substitute manual outlining, but evidence of their performance in multi-center investigations is lacking. In this work, five research-domain automated segmentation methods were evaluated using a multi-center MS dataset. METHODS: 70 MS patients (median EDSS of 2.0 [range 0.0-6.5]) were included from a six-center dataset of the MAGNIMS Study Group (www.magnims.eu) which included 2D FLAIR and 3D T1 images with manual lesion segmentation as a reference. Automated lesion segmentations were produced using five algorithms: Cascade; Lesion Segmentation Toolbox (LST) with both the Lesion growth algorithm (LGA) and the Lesion prediction algorithm (LPA); Lesion-Topology preserving Anatomical Segmentation (Lesion-TOADS); and k-Nearest Neighbor with Tissue Type Priors (kNN-TTP). Main software parameters were optimized using a training set (N = 18), and formal testing was performed on the remaining patients (N = 52). To evaluate volumetric agreement with the reference segmentations, intraclass correlation coefficient (ICC) as well as mean difference in lesion volumes between the automated and reference segmentations were calculated. The Similarity Index (SI), False Positive (FP) volumes and False Negative (FN) volumes were used to examine spatial agreement. All analyses were repeated using a leave-one-center-out design to exclude the center of interest from the training phase to evaluate the performance of the method on 'unseen' center. RESULTS: Compared to the reference mean lesion volume (4.85 ± 7.29 mL), the methods displayed a mean difference of 1.60 ± 4.83 (Cascade), 2.31 ± 7.66 (LGA), 0.44 ± 4.68 (LPA), 1.76 ± 4.17 (Lesion-TOADS) and -1.39 ± 4.10 mL (kNN-TTP). The ICCs were 0.755, 0.713, 0.851, 0.806 and 0.723, respectively. Spatial agreement with reference segmentations was higher for LPA (SI = 0.37 ± 0.23), Lesion-TOADS (SI = 0.35 ± 0.18) and kNN-TTP (SI = 0.44 ± 0.14) than for Cascade (SI = 0.26 ± 0.17) or LGA (SI = 0.31 ± 0.23). All methods showed highly similar results when used on data from a center not used in software parameter optimization. CONCLUSION: The performance of the methods in this multi-center MS dataset was moderate, but appeared to be robust even with new datasets from centers not included in training the automated methods.

Use of megavoltage cine-images for studying intra-thoracic motion during radiotherapy for locally advanced lung cancer.

BACKGROUND AND PURPOSE: Use of planning 4-dimensional CT (4DCT) scans often permits use of smaller target volumes for thoracic tumors but this assumes a reproducible pattern of motion during radiotherapy. We compared cranio-caudal (CC) motion on MV cine-images acquired during treatment with that seen on planning 4DCT. METHODS AND MATERIALS: A pre-programmable respiratory motion phantom and a software tool for motion assessment were used to validate the use of MV cine-images for motion detection. MV cine-images acquired in 20 patients with node-positive lung cancer were analyzed using the same software. Intra-fraction CC motion on 6 MV cine-images from each patient was compared with CC motion on their planning 4DCT. RESULTS: Software-based motion measurement on MV cine-images from the phantom corresponded to actual motion. Mean CC motion of primary tumor, carina and hilus on 4DCT was 7.3mm (range 2-13.8mm), 6.8mm (1.8-21.2) and 11.0mm (4.2-15.1), respectively. Corresponding intra-fraction motion on MV cine was 4.1mm (0.6-13.6mm); 2.7mm (0-10mm) and 6.0mm (1.8-14.4mm), respectively. The tumor, hilus and carina could be tracked in 95%, 88% and 38% of the MV cine-images, respectively. CONCLUSIONS: Intra-fraction motion can be reliably measured using MV-cine images from a phantom. Motion discrepancies identified on MV cine-images can identify patients in whom planning 4DCT scans are not representative.

Disturbed functional connectivity in brain tumour patients: evaluation by graph analysis of synchronization matrices.

OBJECTIVE: Cerebral functions are based on the functional interactions between multiple distinct specialized regions of the brain. Functional interactions require anatomical connections as well as the synchronization of brain oscillations. The present work aims at evaluating the impact of brain tumours on spatial patterns of functional connectivity of the brain measured at rest by MEG. METHODS: We analyzed the statistical dependency (by computing the synchronization likelihood (SL, a measure of generalized synchronization)) between MEG signals at rest, in 17 patients with a brain tumour and in 15 healthy controls. Following an approach that derives from graph theory, we also analyzed the architectural properties of the networks by computing two parameters from the SL matrix, the cluster coefficient C and the characteristic path length L. RESULTS: Alterations in synchronization levels were found in the patients and were not focal but involved intra-hemispheric connectivity. Effects were different considering the frequencies sub-bands, predominating in a decrease in high frequencies bands for long-distance connections and an increase in slower bands for local connectivity. In addition, graph analysis reveals changes in the normal "small-world" network architecture in addition to changes in synchronization levels with some differences according to the studied frequency sub-bands. CONCLUSIONS: Brain tumours alter the functional connectivity and the "network" architecture of the brain. These alterations are not focal and effects are different considering the frequencies sub-bands. SIGNIFICANCE: These neurophysiological changes may contribute to the cognitive alterations observed in patients with brain tumours.

Color intensity projections: a rapid approach for evaluating four-dimensional CT scans in treatment planning.

PURPOSE: Four-dimensional computerized tomography scans (4DCT) enable intrafractional motion to be determined. Because more than 1500 images can be generated with each 4DCT study, tools for efficient data visualization and evaluation are needed. We describe the use of color intensity projections (CIP) for visualizing mobility. METHODS: Four-dimensional computerized tomography images of each patient slice were combined into a CIP composite image. Pixels largely unchanged over the component images appear unchanged in the CIP image. However, pixels whose intensity changes over the phases of the 4DCT appear in the CIP image as colored pixels, and the hue encodes the percentage of time the tissue was in each location. CIPs of 18 patients were used to study tumor and surrogate markers, namely the diaphragm and an abdominal marker block. RESULTS: Color intensity projections permitted mobility of high-contrast features to be quickly visualized and measured. In three selected expiratory phases ("gating phases") that were reviewed in the sagittal plane, gating would have reduced mean tumor mobility from 6.3 +/- 2.0 mm to 1.4 +/- 0.5 mm. Residual tumor mobility in gating phases better correlated with residual mobility of the marker block than that of the diaphragm. CONCLUSION: CIPs permit immediate visualization of mobility in 4DCT images and simplify the selection of appropriate surrogates for gated radiotherapy.

How do brain tumors alter functional connectivity? A magnetoencephalography study.

OBJECTIVE: This study was undertaken to test the hypothesis that brain tumors interfere with normal brain function by disrupting functional connectivity of brain networks. METHODS: Functional connectivity was assessed by computing the synchronization likelihood in a broad band (0.5-60Hz) or in the gamma band (30-60Hz) between all pairwise combinations of magnetoencephalography signals. Magnetoencephalography recordings were made at rest in 17 brain tumor patients and 15 healthy control subjects. For a given threshold of synchronization likelihood values, graphs of the suprathreshold connections between each magnetoencephalography channel and the others channels were built. RESULTS: In some regions, a variable number of channels without connectivity (missing connective points) at this threshold was found. The number of missing connective points was higher in patients with brain tumors than in control subjects (p < 0.0001, broad and gamma band) and was higher for left-sided than right-sided tumors (p = 0.008, broad band; p < 0.0001, gamma band). Individual results analysis indicates that the majority of brain tumor patients display several regions with missing connective point alterations in the affected and in the contralateral hemisphere. INTERPRETATION: Our findings suggest that brain tumors induce a loss of functional connectivity that affects multiple brain regions, and that left side brain tumors have the more severe consequences in this respect.