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Infiltration of CD8+ T cells and their spatial contexture, represented by immunophenotype, predict the prognosis and therapeutic response in breast cancer. However, a non-surgical method using radiomics to evaluate breast cancer immunophenotype has not been explored. Here, we assessed the CD8+ T cell-based immunophenotype in patients with breast cancer undergoing upfront surgery (n = 182). We extracted radiomic features from the four phases of dynamic contrast-enhanced magnetic resonance imaging, and randomly divided the patients into training (n = 137) and validation (n = 45) cohorts. For predicting the immunophenotypes, radiomic models (RMs) that combined the four phases demonstrated superior performance to those derived from a single phase. For discriminating the inflamed tumor from the non-inflamed tumor, the feature-based combination model from the whole tumor (RM-wholeFC) showed high performance in both training (area under the receiver operating characteristic curve [AUC] = 0.973) and validation cohorts (AUC = 0.985). Similarly, the feature-based combination model from the peripheral tumor (RM-periFC) discriminated between immune-desert and excluded tumors with high performance in both training (AUC = 0.993) and validation cohorts (AUC = 0.984). Both RM-wholeFC and RM-periFC demonstrated good to excellent performance for every molecular subtype. Furthermore, in patients who underwent neoadjuvant chemotherapy (n = 64), pre-treatment images showed that tumors exhibiting complete response to neoadjuvant chemotherapy had significantly higher scores from RM-wholeFC and lower scores from RM-periFC. Our RMs predicted the immunophenotype of breast cancer based on the spatial distribution of CD8+ T cells with high accuracy. This approach can be used to stratify patients non-invasively based on the status of the tumor-immune microenvironment.

Background: Recent emerging evidence has highlighted the potential critical role of cerebrospinal fluid (CSF) in cerebral waste clearance and immunomodulation. It is already very well-established that the central nervous system (CNS) is completely submerged in CSF on a macro-level; but to what extent is this true on a micro-level? Specifically, within the peri-neural and peri-vascular spaces within the CNS parenchyma. Therefore, the objective of this study was to use magnetic resonance imaging (MRI) to simultaneously map the presence of CSF within all peri-neural (cranial and spinal nerves) and peri-vascular spaces in vivo in humans. Four MRI protocols each with five participants were used to image the CSF in the brain and spinal cord. Our findings indicated that all CNS neuro- and vascular-communication channels are surrounded with CSF. In other words, all peri-neural spaces surrounding the cranial and spinal nerves as well as all peri-vascular spaces surrounding MRI-visible vasculature were filled with CSF. These findings suggest that anatomically, substance exchange between the brain parenchyma and outside tissues including lymphatic ones can only occur through CSF pathways and/or vascular pathways, warranting further investigation into its implications in cerebral waste clearance and immunity.

Background: Recent emerging evidence has highlighted the potential critical role of cerebrospinal fluid (CSF) in cerebral waste clearance and immunomodulation. It is already very well-established that the central nervous system (CNS) is completely submerged in CSF on a macro-level; but to what extent is this true on a micro-level? Specifically, within the peri-neural and peri-vascular spaces within the CNS parenchyma. Therefore, the objective of this study was to use magnetic resonance imaging (MRI) to simultaneously map the presence of CSF within all peri-neural (cranial and spinal nerves) and peri-vascular spaces in vivo in humans. Four MRI protocols each with five participants were used to image the CSF in the brain and spinal cord. Our findings indicated that all CNS neuro- and vascular-communication channels are surrounded with CSF. In other words, all peri-neural spaces surrounding the cranial and spinal nerves as well as all peri-vascular spaces surrounding MRI-visible vasculature were filled with CSF. These findings suggest that anatomically, substance exchange between the brain parenchyma and outside tissues including lymphatic ones can only occur through CSF pathways and/or vascular pathways, warranting further investigation into its implications in cerebral waste clearance and immunity. [ABSTRACT FROM AUTHOR]

Secondary mitral regurgitation (sMR) is characterized by left ventricular (LV) dilatation or dysfunction, resulting in failure of mitral leaflet coaptation. sMR complicates up to 35% of ischaemic cardiomyopathies (1) and 57% of dilated cardiomyopathies (2). Due to the prevalence of coronary artery disease worldwide, ischaemic cardiomyopathy is the most frequently encountered cause of sMR in clinical practice. Although mortality from cardiovascular disease has gradually fallen in Western countries, severe sMR remains an independent predictor of mortality (3) and hospitalization for heart failure (4). The presence of even mild sMR following acute MI reduces long-term survival free of major adverse events (1). Such adverse outcomes worsen as the severity of sMR increases, due to a cycle in which LV remodeling begets sMR and vice versa. Current guidelines do not recommend invasive treatment of the sMR alone as a first-line approach, due to the paucity of evidence supporting improvement in clinical outcomes. Furthermore, a lack of international consensus on the thresholds that define severe sMR has resulted in confusion amongst clinicians determining whether intervention is warranted (5, 6). The recent Cardiovascular Outcomes Assessment of the MitraClip Percutaneous Therapy for Heart Failure Patients with Functional Mitral Regurgitation (COAPT) trial (7) assessing the effectiveness of transcatheter mitral valve repair is the first study to demonstrate mortality benefit from correction of sMR and has reignited interest in identifying patients who would benefit from mitral valve intervention. Multimodality imaging, including echocardiography and cardiovascular magnetic resonance (CMR), plays a key role in helping to diagnose, quantify, monitor, and risk stratify patients for surgical and transcatheter mitral valve interventions.

Sparsity-based approaches have been popular in many applications in image processing and imaging. Compressed sensing exploits the sparsity of images in a transform domain or dictionary to improve image recovery fromundersampledmeasurements. In the context of inverse problems in dynamic imaging, recent research has demonstrated the promise of sparsity and low-rank techniques. For example, the patches of the underlying data are modeled as sparse in an adaptive dictionary domain, and the resulting image and dictionary estimation from undersampled measurements is called dictionary-blind compressed sensing, or the dynamic image sequence is modeled as a sum of low-rank and sparse (in some transform domain) components (L+S model) that are estimated from limited measurements. In this work, we investigate a data-adaptive extension of the L+S model, dubbed LASSI, where the temporal image sequence is decomposed into a low-rank component and a component whose spatiotemporal (3D) patches are sparse in some adaptive dictionary domain. We investigate various formulations and efficient methods for jointly estimating the underlying dynamic signal components and the spatiotemporal dictionary from limited measurements. We also obtain efficient sparsity penalized dictionary-blind compressed sensing methods as special cases of our LASSI approaches. Our numerical experiments demonstrate the promising performance of LASSI schemes for dynamicmagnetic resonance image reconstruction from limited k-t space data compared to recent methods such as k-t SLR and L+S, and compared to the proposed dictionary-blind compressed sensing method. [ABSTRACT FROM PUBLISHER]

Infiltration of CD8 + T cells and their spatial contexture, represented by immunophenotype, predict the prognosis and therapeutic response in breast cancer. However, a non-surgical method using radiomics to evaluate breast cancer immunophenotype has not been explored. Here, we assessed the CD8 + T cell-based immunophenotype in patients with breast cancer undergoing upfront surgery (n = 182). We extracted radiomic features from the four phases of dynamic contrast-enhanced magnetic resonance imaging, and randomly divided the patients into training (n = 137) and validation (n = 45) cohorts. For predicting the immunophenotypes, radiomic models (RMs) that combined the four phases demonstrated superior performance to those derived from a single phase. For discriminating the inflamed tumor from the non-inflamed tumor, the feature-based combination model from the whole tumor (RM-whole FC ) showed high performance in both training (area under the receiver operating characteristic curve [AUC] = 0.973) and validation cohorts (AUC = 0.985). Similarly, the feature-based combination model from the peripheral tumor (RM-peri FC ) discriminated between immune-desert and excluded tumors with high performance in both training (AUC = 0.993) and validation cohorts (AUC = 0.984). Both RM-whole FC and RM-peri FC demonstrated good to excellent performance for every molecular subtype. Furthermore, in patients who underwent neoadjuvant chemotherapy (n = 64), pre-treatment images showed that tumors exhibiting complete response to neoadjuvant chemotherapy had significantly higher scores from RM-whole FC and lower scores from RM-peri FC . Our RMs predicted the immunophenotype of breast cancer based on the spatial distribution of CD8 + T cells with high accuracy. This approach can be used to stratify patients non-invasively based on the status of the tumor-immune microenvironment., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Jeon, Kim, Na, Seo, Sohn and Lim.)

Secondary mitral regurgitation (sMR) is characterized by left ventricular (LV) dilatation or dysfunction, resulting in failure of mitral leaflet coaptation. sMR complicates up to 35% of ischaemic cardiomyopathies (1) and 57% of dilated cardiomyopathies (2). Due to the prevalence of coronary artery disease worldwide, ischaemic cardiomyopathy is the most frequently encountered cause of sMR in clinical practice. Although mortality from cardiovascular disease has gradually fallen in Western countries, severe sMR remains an independent predictor of mortality (3) and hospitalization for heart failure (4). The presence of even mild sMR following acute MI reduces long-term survival free of major adverse events (1). Such adverse outcomes worsen as the severity of sMR increases, due to a cycle in which LV remodeling begets sMR and vice versa. Current guidelines do not recommend invasive treatment of the sMR alone as a first-line approach, due to the paucity of evidence supporting improvement in clinical outcomes. Furthermore, a lack of international consensus on the thresholds that define severe sMR has resulted in confusion amongst clinicians determining whether intervention is warranted (5, 6). The recent Cardiovascular Outcomes Assessment of the MitraClip Percutaneous Therapy for Heart Failure Patients with Functional Mitral Regurgitation (COAPT) trial (7) assessing the effectiveness of transcatheter mitral valve repair is the first study to demonstrate mortality benefit from correction of sMR and has reignited interest in identifying patients who would benefit from mitral valve intervention. Multimodality imaging, including echocardiography and cardiovascular magnetic resonance (CMR), plays a key role in helping to diagnose, quantify, monitor, and risk stratify patients for surgical and transcatheter mitral valve interventions., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The handling editor declared a past co-authorship with the authors RS and SM., (Copyright © 2020 Sharma, Liu, Mahmoud-Elsayed, Myerson and Steeds.)