Diffusion-weighted MRI of the spinal cord in cervical spondylotic myelopathy after instrumented fusion.

Introduction: This study investigated tissue diffusion properties within the spinal cord of individuals treated for cervical spondylotic myelopathy (CSM) using post-decompression stabilization hardware. While previous research has indicated the potential of diffusion-weighted MRI (DW-MRI) markers of CSM, the metallic implants often used to stabilize the decompressed spine hamper conventional DW-MRI. Methods: Utilizing recent developments in DW-MRI metal-artifact suppression technologies, imaging data was acquired from 38 CSM study participants who had undergone instrumented fusion, as well as asymptomatic (non-instrumented) control participants. Apparent diffusion coefficients were determined in axial slice sections and split into four categories: a) instrumented levels, b) non-instrumented CSM levels, c) adjacent-segment (to instrumentation) CSM levels, and d) non-instrumented control levels. Multi-linear regression models accounting for age, sex, and body mass index were used to investigate ADC measures within each category. Furthermore, the cord diffusivity within CSM subjects was correlated with symptom scores and the duration since fusion procedures. Results: ADC measures of the spinal cord in CSM subjects were globally reduced relative to control subjects (p = 0.005). In addition, instrumented levels within the CSM subjects showed reduced diffusivity relative to controls (p = 0.003), while ADC within non-instrumented CSM levels did not statistically deviate from control levels (p = 0.107). Discussion: Multi-spectral DW-MRI technology can be effectively employed to evaluate cord diffusivity near fusion hardware in subjects who have undergone surgery for CSM. Leveraging this advanced technology, this study had identified significant reductions in cord diffusivity, relative to control subjects, in CSM patients treated with conventional metallic fusion instrumentation.

Functional Connectivity Magnetic Resonance Imaging Sequences in Patients With Postsurgical Persistent Spinal Pain Syndrome Type 2 With Implanted Spinal Cord Stimulation Systems: A Safety, Feasibility, and Validity Study.

BACKGROUND: Chronic pain has been associated with alterations in brain connectivity, both within networks (regional) and between networks (cross-network connectivity). Functional connectivity (FC) data on chronic back pain are limited and based on heterogeneous pain populations. Patients with postsurgical persistent spinal pain syndrome (PSPS) type 2 are good candidates for spinal cord stimulation (SCS) therapy. We hypothesize that 1) FC magnetic resonance imaging (fcMRI) scans can be safely obtained in patients with PSPS type 2 with implanted therapeutic SCS devices and that 2) their cross-network connectivity patterns are altered and involve emotion and reward/aversion functions. MATERIALS AND METHODS: Resting-state (RS) fcMRI (rsfcMRI) scans were obtained from nine patients with PSPS type 2 implanted with therapeutic SCS systems and 13 age-matched controls. Seven RS networks were analyzed, including the striatum. RESULTS: Cross-network FC sequences were safely obtained on a 3T MRI scanner in all nine patients with PSPS type 2 with implanted SCS systems. FC patterns involving emotion/reward brain circuitry were altered as compared with controls. Patients with a history of constant neuropathic pain, experiencing longer therapeutic effects of SCS, had fewer alterations in their connectivity patterns. CONCLUSIONS: To our knowledge, this is the first report of altered cross-network FC involving emotion/reward brain circuitry in a homogeneous population of patients with chronic pain with fully implanted SCS systems, on a 3T MRI scanner. All rsfcMRI studies were safe and well tolerated by all nine patients, with no detectable effects on the implanted devices.

Predicting Neoadjuvant Treatment Response in Rectal Cancer Using Machine Learning: Evaluation of MRI-Based Radiomic and Clinical Models.

BACKGROUND: Radiomics is an approach to medical imaging that quantifies the features normally translated into visual display. While both radiomic and clinical markers have shown promise in predicting response to neoadjuvant chemoradiation therapy (nCRT) for rectal cancer, the interrelationship is not yet clear. METHODS: A retrospective, single-institution study of patients treated with nCRT for locally advanced rectal cancer was performed. Clinical and radiomic features were extracted from electronic medical record and pre-treatment magnetic resonance imaging, respectively. Machine learning models were created and assessed for complete response and positive treatment effect using the area under the receiver operating curves. RESULTS: Of 131 rectal cancer patients evaluated, 68 (51.9%) were identified to have a positive treatment effect and 35 (26.7%) had a complete response. On univariate analysis, clinical T-stage (OR 0.46, p = 0.02), lymphovascular/perineural invasion (OR 0.11, p = 0.03), and statin use (OR 2.45, p = 0.049) were associated with a complete response. Clinical T-stage (OR 0.37, p = 0.01), lymphovascular/perineural invasion (OR 0.16, p = 0.001), and abnormal carcinoembryonic antigen level (OR 0.28, p = 0.002) were significantly associated with a positive treatment effect. The clinical model was the strongest individual predictor of both positive treatment effect (AUC = 0.64) and complete response (AUC = 0.69). The predictive ability of a positive treatment effect increased by adding tumor and mesorectal radiomic features to the clinical model (AUC = 0.73). CONCLUSIONS: The use of a combined model with both clinical and radiomic features resulted in the strongest predictive capability. With the eventual goal of tailoring treatment to the individual, both clinical and radiologic markers offer insight into identifying patients likely to respond favorably to nCRT.

Accurate segmentation of prostate cancer histomorphometric features using a weakly supervised convolutional neural network.

Purpose: Prostate cancer primarily arises from the glandular epithelium. Histomophometric techniques have been used to assess the glandular epithelium in automated detection and classification pipelines; however, they are often rigid in their implementation, and their performance suffers on large datasets where variation in staining, imaging, and preparation is difficult to control. The purpose of this study is to quantify performance of a pixelwise segmentation algorithm that was trained using different combinations of weak and strong stroma, epithelium, and lumen labels in a prostate histology dataset. Approach: We have combined weakly labeled datasets generated using simple morphometric techniques and high-quality labeled datasets from human observers in prostate biopsy cores to train a convolutional neural network for use in whole mount prostate labeling pipelines. With trained networks, we characterize pixelwise segmentation of stromal, epithelium, and lumen (SEL) regions on both biopsy core and whole-mount H&E-stained tissue. Results: We provide evidence that by simply training a deep learning algorithm on weakly labeled data generated from rigid morphometric methods, we can improve the robustness of classification over the morphometric methods used to train the classifier. Conclusions: We show that not only does our approach of combining weak and strong labels for training the CNN improve qualitative SEL labeling within tissue but also the deep learning generated labels are superior for cancer classification in a higher-order algorithm over the morphometrically derived labels it was trained on.

Radiomic Features of Multiparametric MRI Present Stable Associations With Analogous Histological Features in Patients With Brain Cancer.

Magnetic resonance (MR)-derived radiomic features have shown substantial predictive utility in modeling different prognostic factors of glioblastoma and other brain cancers. However, the biological relationship underpinning these predictive models has been largely unstudied, and the generalizability of these models had been called into question. Here, we examine the localized relationship between MR-derived radiomic features and histology-derived "histomic" features using a data set of 16 patients with brain cancer. Tile-based radiomic features were collected on T1, post-contrast T1, FLAIR, and diffusion-weighted imaging (DWI)-derived apparent diffusion coefficient (ADC) images acquired before patient death, with analogous histomic features collected for autopsy samples coregistered to the magnetic resonance imaging. Features were collected for each original image, as well as a 3D wavelet decomposition of each image, resulting in 837 features per MR and histology image. Correlative analyses were used to assess the degree of association between radiomic-histomic pairs for each magnetic resonance imaging. The influence of several confounds was also assessed using linear mixed-effect models for the normalized radiomic-histomic distance, testing for main effects of different acquisition field strengths. Results as a whole were largely heterogeneous, but several features showed substantial associations with their histomic analogs, particularly those derived from the FLAIR and postcontrast T1W images. These features with the strongest association typically presented as stable across field strengths as well. These data suggest that a subset of radiomic features can consistently capture texture information on underlying tissue histology.

Functional connectivity and structural analysis of trial spinal cord stimulation responders in failed back surgery syndrome.

BACKGROUND: Chronic pain has been associated with alterations in brain structure and function that appear dependent on pain phenotype. Functional connectivity (FC) data on chronic back pain (CBP) is limited and based on heterogeneous pain populations. We hypothesize that failed back surgery syndrome (FBSS) patients being considered for spinal cord stimulation (SCS) therapy have altered resting state (RS) FC cross-network patterns that 1) specifically involve emotion and reward/aversion functions and 2) are related to pain scores. METHODS: RS functional MRI (fMRI) scans were obtained for 10 FBSS patients who are being considered for but who have not yet undergone implantation of a permanent SCS device and 12 healthy age-matched controls. Seven RS networks were analyzed including the striatum (STM). The Wilcoxon signed-rank test evaluated differences in cross-network FC strength (FCS). Differences in periaqueductal grey (PAG) FC were assessed with seed-based analysis. RESULTS: Cross-network FCS was decreased (p<0.05) between the STM and all other networks in these FBSS patients. There was a negative linear relationship (R2 = 0.76, p<0.0022) between STMFCS index and pain scores. The PAG showed decreased FC with network elements and amygdala but increased FC with the sensorimotor cortex and cingulate gyrus. CONCLUSIONS: Decreased FC between STM and other RS networks in FBSS has not been previously reported. This STMFCS index may represent a more objective measure of chronic pain specific to FBSS which may help guide patient selection for SCS and subsequent management.

Multispectral diffusion-weighted MRI of the instrumented cervical spinal cord: a preliminary study of 5 cases.

PURPOSE: Diffusion-weighted imaging has undergone substantial investigation as a potential tool for advanced assessment of spinal cord health. Unfortunately, commonly encountered surgically implanted spinal hardware has historically disrupted these studies. This preliminary investigation applies the recently developed multispectral diffusion-weighted PROPELLER technique to quantitative assessment of the spinal cord immediately adjacent to metallic spinal fusion instrumentation. METHODS: Morphological and diffusion-weighted MRI of the spinal cord was collected from 5 subjects with implanted cervical spinal fusion hardware. Conventional and multispectral diffusion-weighted images were also collected on a normative non-instrumented control cohort and utilized for methodological stability analysis. Variance of the ADC values derived from the normative control group was then analyzed on a subject-by-subject basis and qualitatively correlated with clinical morphological interpretations. RESULTS: Normative control ADC values within the spinal cord were stable across DWI methods for a b value of 600 s/mm2, though this stability degraded at lower b value levels. Susceptibility artifacts precluded conventional DWI analysis of the cord in subjects with spinal fusion hardware in 4 of the 5 test cases. On the contrary, multispectral PROPELLER DWI produced viable ADC measurements within the cord of all 5 instrumented subjects. Instrumented cord regions without obvious pathology (N = 4) showed ADC values that were lower than expected, whereas one subject with diagnosed myelomalacia showed abnormally elevated ADC. CONCLUSIONS: In the absence of instrumentation, multispectral DWI provides quantitative capabilities that match with those of conventional DWI approaches. In a preliminary instrumented subject analysis, cord ADC values showed both expected and unexpected variations from the normative cohort. These slides can be retrieved under Electronic Supplementary Material.

Generalized simultaneous multi-orientation 2D imaging.

PURPOSE: Flexibility in slice prescription is critical for precise motion monitoring during MR-guided therapies. Adding more slices to improve spatial coverage during rapid 2D cine imaging often hampers temporal resolution. This work describes a framework to simultaneously acquire multiple arbitrarily oriented slices which share a common frequency encoding axis. This framework allows for higher frame rates for a given number of slices compared to conventional interleaved-slice multi-orientation cine imaging. THEORY AND METHODS: A framework to calculate zeroth gradient moments to be played out between sequentially excited slices with multiple orientations is described here. Experiments were performed in phantom, and in vivo in the head/neck and abdomen of patients. RESULTS: Images arbitrarily rotated relative to one another were successfully obtained in phantom and in vivo. Simultaneous multi-orientation (SMO) images were also acquired with additional in-plane acceleration to demonstrate the capability of this method to rapidly image objects moving with physiological motion. CONCLUSIONS: The technical feasibility of the generalized SMO imaging framework was tested in this study. It shows promise for continued development for motion monitoring during MR-guided therapies.