A pragmatic randomized controlled trial of a group self-management support program versus treatment-as-usual for anxiety disorders: study protocol.

BACKGROUND: The integration of a personal recovery-oriented practice in mental health services is an emerging principle in policy planning. Self-management support (SMS) is an intervention promoting recovery that aims at educating patients on the nature of their mental disorder, improving their strategies to manage their day-to-day symptoms, fostering self-efficacy and empowerment, preventing relapse, and promoting well-being. While SMS is well established for chronic physical conditions, there is a lack of evidence to support the implementation of structured SMS programs for common mental disorders, and particularly for anxiety disorders. This study aims to examine the effectiveness of a group-based self-management support program for anxiety disorders as an add-on to treatment-as-usual in community-based care settings. METHODS/DESIGN: We will conduct a multicentre pragmatic randomized controlled trial with a pre-treatment, post-treatment (4-month post-randomization), and follow-ups at 8, 12 and 24-months. TREATMENT AND CONTROL GROUPS: a) group self-management support (10 weekly 2.5-h group web-based sessions with 10-15 patients with two trained facilitators); b) treatment-as-usual. Participants will include adults meeting DSM-5 criteria for Panic Disorder, Agoraphobia, Social Anxiety Disorder, and/or Generalized Anxiety Disorder. The primary outcome measure will be the Beck Anxiety Inventory; secondary outcome measures will comprise self-reported instruments for anxiety and depressive symptoms, recovery, self-management, quality of life, and service utilisation. STATISTICAL ANALYSIS: Data will be analysed based on intention-to-treat with a mixed effects regression model accounting for between and within-subject variations in the effects of the intervention. DISCUSSION: This study will contribute to the limited knowledge base regarding the effectiveness of structured group self-management support for anxiety disorders. It is expected that changes in patients' self-management behaviour will lead to better anxiety management and, consequently, to improved patient outcomes. TRIAL REGISTRATION: ClinicalTrials.gov: NCT05124639 . Prospectively registered 18 November 2021.

Social Isolation in Dementia: The Effects of COVID-19.

The aim of this literature review is to identify the effects of social isolation and lonliness on persons with dementia and to highlight interventions for private homes and long-term care facilities. It includes articles published in the last 5 years for a total of 45 articles. Social isolation and/or lonliness is linked to reduced quality of life, neuropsychiatric symptoms, and psychotropic drug use in people living with demential. Interventions, including physical activity, should be individualized and patient centered.

Broadly and finely tunable hybrid silicon laser with nanosecond-scale switching speed.

We demonstrate a hybrid silicon tunable laser with wide tunability and rapid switching speed for applications in sensing and optical networks. By implementing an optimized carrier injection phase shifter design, the filters of the silicon laser cavity may be efficiently controlled, enabling both fine and broad wavelength tuning across a 56 nm range, in addition to a rapid 10 ns switching time. The laser emits up to 10 dBm output power, and the linewidth is near 200 kHz. The fast wavelength switching demonstrated here may be employed in data center and access networks, while the potential for rapid wavelength sweeping is attractive for optical sensing and imaging applications.

Altered Gray Matter Structural Covariance Networks in Early Stages of Alzheimer's Disease.

Clinical symptoms observed in Alzheimer's disease (AD) patients may reflect variations within specific large-scale brain networks, modeling AD as a disconnection syndrome. The present magnetic resonance imaging study aims to compare the organization of gray matter structural covariance networks between 109 cognitively unimpaired controls (CTRL) and 109 AD patients positive to beta-amyloid at the early stages of the disease, using voxel-based morphometry. The default-mode network (DMN; medial temporal lobe subsystem) was less extended in AD patients in comparison with CTRL, with a significant decrease in the structural association between the entorhinal cortex and the medial prefrontal and the dorsolateral prefrontal cortices. The DMN (midline core subsystem) was also less extended in AD patients. Trends toward increased structural association were observed in the salience and executive control networks. The observed changes suggest that early disruptions in structural association between heteromodal association cortices and the entorhinal cortex could contribute to an isolation of the hippocampal formation, potentially giving rise to the clinical hallmark of AD, progressive memory impairment. It also provides critical support to the hypothesis that the reduced connectivity within the DMN in early AD is accompanied by an enhancement of connectivity in the salience and executive control networks.

Exploration of the dynamics between brain regions associated with the default-mode network and frontostriatal pathway with regards to task familiarity.

Specific brain regions have consistently been reported to be activated during resting state period, and they were described as being part of a particular network called the default-mode network (DMN). It has been shown that the DMN would deactivate during goal-directed tasks, but the actual relationship between them is still a matter of debate. In a previous study, we reported a specific pattern of activation of the frontostriatal regions during a set-shifting task in which these regions were increasing their activity as set-shifts were performed continuously and decreasing when the same rule was executed repeatedly. The present study aimed at assessing the relationship between the frontostriatal regions and the DMN. We hypothesized that the DMN would be anticorrelated with the frontostriatal regions so the DMN would be more deactivated as set-shifts are executed for a long period, but would start increasing when the same rule is being executed for a long period. Here, 15 participants underwent functional magnetic resonance imaging while performing a card-sorting task. We observed increased activity in the frontostriatal regions as more set-shifts are being performed while the DMN gets more deactivated. Interestingly, as decreased activity was observed in the frontostriatal regions during the execution of the same rule for a long period, the DMN showed increasing activity. We argue that there is an anticorrelation between the frontostriatal regions and the DMN, but also that the DMN could show positive activation during performance of a familiar goal-directed task.

Imaging the electromechanical activity of the heart in vivo.

Cardiac conduction abnormalities remain a major cause of death and disability worldwide. However, as of today, there is no standard clinical imaging modality that can noninvasively provide maps of the electrical activation. In this paper, electromechanical wave imaging (EWI), a novel ultrasound-based imaging method, is shown to be capable of mapping the electromechanics of all four cardiac chambers at high temporal and spatial resolutions and a precision previously unobtainable in a full cardiac view in both animals and humans. The transient deformations resulting from the electrical activation of the myocardium were mapped in 2D and combined in 3D biplane ventricular views. EWI maps were acquired during five distinct conduction configurations and were found to be closely correlated to the electrical activation sequences. EWI in humans was shown to be feasible and capable of depicting the normal electromechanical activation sequence of both atria and ventricles. This validation of EWI as a direct, noninvasive, and highly translational approach underlines its potential to serve as a unique imaging tool for the early detection, diagnosis, and treatment monitoring of arrhythmias through ultrasound-based mapping of the transmural electromechanical activation sequence reliably at the point of care, and in real time.

Phase Aberration Correction for In Vivo Ultrasound Localization Microscopy Using a Spatiotemporal Complex-Valued Neural Network.

Ultrasound Localization Microscopy (ULM) can map microvessels at a resolution of a few micrometers ( [Formula: see text]). Transcranial ULM remains challenging in presence of aberrations caused by the skull, which lead to localization errors. Herein, we propose a deep learning approach based on recently introduced complex-valued convolutional neural networks (CV-CNNs) to retrieve the aberration function, which can then be used to form enhanced images using standard delay-and-sum beamforming. CV-CNNs were selected as they can apply time delays through multiplication with in-phase quadrature input data. Predicting the aberration function rather than corrected images also confers enhanced explainability to the network. In addition, 3D spatiotemporal convolutions were used for the network to leverage entire microbubble tracks. For training and validation, we used an anatomically and hemodynamically realistic mouse brain microvascular network model to simulate the flow of microbubbles in presence of aberration. The proposed CV-CNN performance was compared to the coherence-based method by using microbubble tracks. We then confirmed the capability of the proposed network to generalize to transcranial in vivo data in the mouse brain (n=3). Vascular reconstructions using a locally predicted aberration function included additional and sharper vessels. The CV-CNN was more robust than the coherence-based method and could perform aberration correction in a 6-month-old mouse. After correction, we measured a resolution of [Formula: see text] for younger mice, representing an improvement of 25.8%, while the resolution was improved by 13.9% for the 6-month-old mouse. This work leads to different applications for complex-valued convolutions in biomedical imaging and strategies to perform transcranial ULM.

[PAL-PRAT study: Healthcare workers' knowledge and perception of palliative practices in a Cancer Center]. / Quelle connaissance et quelle perception ont les professionnels de santé d'un Centre de lutte contre le cancer à propos des pratiques palliatives encadrées par la loi Claeys-Leonetti : étude PAL PRAT.

INTRODUCTION: The issue of end-of-life care is the subject of a sensitive debate in French society, particularly regarding the possibility for certain patients to have access to medical assistance in dying. The aim of this study was to assess the knowledge and opinion of healthcare providers on the care practices for patients at the end of life, as well as to highlight any specificities in their discourse. METHOD: A survey of healthcare providers' opinions, composed of closed and open questions, that were analyzed using a lexicometric approach, was distributed in a cancer center. RESULTS: The results of the study reveal a good knowledge of the different procedures. Professionals considered that advance directives should be systematically collected; a majority of them differentiated euthanasia from deep continuous sedation and perceived the latter as a means of relieving patients' suffering without inducing death. The different procedures related to the active assistance in dying were known by a majority of professionals and the survey did not identify a dominant trend concerning the will to practice euthanasia if the legal framework allowed it. Half of the participants considered their training insufficient, indicating the need to fill this gap. DISCUSSION: This survey underlines the importance of training and support for the professionals caring for patients in palliative situation and their relatives in France.

Equivalent-time-active-cavitation-imaging enables vascular-resolution blood-brain-barrier-opening-therapy planning.

Objective. Linking cavitation and anatomy was found to be important for predictable outcomes in focused-ultrasound blood-brain-barrier-opening and requires high resolution cavitation mapping. However, cavitation mapping techniques for planning and monitoring of therapeutic procedures either (1) do not leverage the full resolution capabilities of ultrasound imaging or (2) place constraints on the length of the therapeutic pulse. This study aimed to develop a high-resolution technique that could resolve vascular anatomy in the cavitation map.Approach. Herein, we develop BandPass-sampled-equivalent-time-active-cavitation-imaging (BP-ETACI), derived from bandpass sampling and dual-frequency contrast imaging at 12.5 MHz to produce cavitation maps prior and during blood-brain barrier opening with long therapeutic bursts using a 1.5 MHz focused transducer in the brain of C57BL/6 mice.Main results. The BP-ETACI cavitation maps were found to correlate with the vascular anatomy in ultrasound localization microscopy vascular maps and in histological sections. Cavitation maps produced from non-blood-brain-barrier disrupting doses showed the same cavitation-bearing vasculature as maps produced over entire blood-brain-barrier opening procedures, allowing use for (1) monitoring focused-ultrasound blood-brain-barrier-opening (FUS-BBBO), but also for (2) therapy planning and target verification.Significance. BP-ETACI is versatile, created high resolution cavitation maps in the mouse brain and is easily translatable to existing FUS-BBBO experiments. As such, it provides a means to further study cavitation phenomena in FUS-BBBO.

Utility of PSMA PET/CT in Staging and Restaging of Renal Cell Carcinoma: A Systematic Review and Metaanalysis.

Prostate-specific membrane antigen (PSMA) is expressed in the neovasculature of multiple solid tumors, including renal cell carcinoma (RCC). Studies have demonstrated promising results on the utility of PSMA-targeted PET/CT imaging in RCC. This report aims to provide a systematic review and metaanalysis on the utility and detection rate of PSMA PET/CT imaging in staging or evaluation of primary RCC and restaging of metastatic or recurrent RCC. Methods: Searches were performed in PubMed, Embase, and abstract proceedings (last updated, August 2023). Studies that provided a lesion-level detection rate of PSMA radiotracers in staging or restaging of RCC were included in the metaanalysis. The overall pooled detection rate with a 95% CI was estimated, and subgroup analysis was performed when feasible. Results: Nine studies comprising 152 patients (133 clear cell RCC [ccRCC], 19 other RCC subtypes) were included in the metaanalysis. The pooled detection rate of PSMA PET/CT in evaluation of primary or metastatic RCC was estimated to be 0.83 (95% CI, 0.67-0.92). Subgroup analysis showed a pooled PSMA detection rate of 0.74 (95% CI, 0.57-0.86) in staging or evaluation of primary RCC lesions and 0.87 (95% CI, 0.73-0.95) in restaging of metastatic or recurrent RCC. Analysis based on the type of radiotracer showed a pooled detection rate of 0.85 (95% CI, 0.62-0.95) for 68Ga-based PSMA tracers and 0.92 (95% CI, 0.76-0.97) for 18F-DCFPyL PET/CT. Furthermore, in metastatic ccRCC, the available data support a significantly higher detection rate for 18F-DCFPyL PET/CT than for conventional imaging modalities (2 studies). Conclusion: Our preliminary results show that PSMA PET/CT could be a promising alternative imaging modality for evaluating RCC, particularly metastatic ccRCC. Large prospective studies are warranted to confirm clinical utility in the staging and restaging of RCC.

Boosting Cardiac Color Doppler Frame Rates with Deep Learning.

Color Doppler echocardiography enables visualization of blood flow within the heart. However, the limited frame rate impedes the quantitative assessment of blood velocity throughout the cardiac cycle, thereby compromising a comprehensive analysis of ventricular filling. Concurrently, deep learning is demonstrating promising outcomes in post-processing of echocardiographic data for various applications. This work explores the use of deep learning models for intracardiac Doppler velocity estimation from a reduced number of filtered I/Q signals. We used a supervised learning approach by simulating patient-based cardiac color Doppler acquisitions and proposed data augmentation strategies to enlarge the training dataset. We implemented architectures based on convolutional neural networks. In particular, we focused on comparing the U-Net model and the recent ConvNeXt models, alongside assessing real-valued versus complex-valued representations. We found that both models outperformed the state-of-the-art autocorrelator method, effectively mitigating aliasing and noise. We did not observe significant differences between the use of real and complex data. Finally, we validated the models on in vitro and in vivo experiments. All models produced quantitatively comparable results to the baseline and were more robust to noise. ConvNeXt emerged as the sole model to achieve high-quality results on in vivo aliased samples. These results demonstrate the interest of supervised deep learning methods for Doppler velocity estimation from a reduced number of acquisitions.

Dynamic Ultrasound Localization Microscopy Without ECG-Gating.

OBJECTIVE: Dynamic Ultrasound Localization Microscopy (DULM) has first been developed for non-invasive Pulsatility measurements in the rodent brain. DULM relies on the localization and tracking of microbubbles (MBs) injected into the bloodstream, to obtain highly resolved velocity and density cine-loops. Previous DULM techniques required ECG-gating, limiting its application to specific datasets, and increasing acquisition time. The objective of this study is to eliminate the need for ECG-gating in DULM experiments by introducing a motion-matching method for time registration. METHODS: We developed a motion-matching algorithm based on tissue Doppler that leverages the cyclic tissue motion within the brain. Tissue Doppler was estimated for each group of frames in the acquisitions, at multiple locations identified as local maxima in the skin above the skull. Subsequently, each group of frames was time-registered to a reference group by delaying it based on the maximum correlation value between their respective tissue Doppler signals. This synchronization ensured that each group of frames aligned with the brain tissue motion of the reference group, and consequently, with its cardiac cycle. As a result, velocities of MBs could be averaged to retrieve flow velocity variations over time. RESULTS: Initially validated in ECG-gated acquisitions in a rat model (n = 1), the proposed method was successfully applied in a mice model in 2D (n = 3) and in a feline model in 3D (n = 1). Performing time-registration with the proposed motion-matching method or by using ECG-gating leads to similar results. For the first time, dynamic velocity and density cine-loops were extracted without the need for any information on the animal ECG, and complex dynamic markers such as the Pulsatility index were estimated. CONCLUSION: Results suggest that DULM can be performed without external gating, enabling the use of DULM on any ULM dataset where enough MBs are detectable. Time registration by motion-matching represents a significant advancement in DULM techniques, making DULM more accessible by simplifying its experimental complexity.

Supportive Care Needs of Newly Diagnosed Cancer Patients in a Comprehensive Cancer Center: Identifying Care Profiles and Future Perspectives.

The prompt introduction of supportive care for patients with cancer leads to a better quality of life, potential survival benefits, and improvements in treatment safety. Considering that patients' needs vary, descriptive assessments could serve as a compass for an efficient and prompt healthcare response. The aim of this study was to identify supportive care needs in newly diagnosed patients according to cancer type. A retrospective study was conducted by collecting data from the case consultation and medical records of a comprehensive cancer center in France. Patients' needs were divided into twelve domains: nutrition, psychological support, psychiatric support, social care, physiotherapy, addictology, pain management, palliative care, pharmacology, complementary and alternative practice (CAM), sexual health, and speech therapy. Out of 6217 newly diagnosed patients of various cancer types who sought medical care at Gustave Roussy in 2021, 2541 (41%) required supportive cancer care (SCC), and of them, 1331 patients (52%) required two or more different SCC specialist interventions. The top five interventions were dietary (for 60% of patients), physiotherapy (33%), psychology (29%), social care (28%), and pain management (16%). Subgroup analysis according to cancer department highlighted additional specific needs: CAM for breast cancer patients (11%), speech specialist (27%) and addictologist (22%) interventions for ENT patients, psychiatry consultations for neurological patients (16%), and palliative care for dermatology patients (23%). The aforementioned data suggest that an early, multidisciplinary supportive care intervention should be required. Assembling human resources at the time of diagnosis within a dedicated day unit would be the next appropriate step in developing personalized care pathways related to the highlighted needs.

Quantitative pulsatility measurements using 3D dynamic ultrasound localization microscopy.

A rise in blood flow velocity variations (i.e. pulsatility) in the brain, caused by the stiffening of upstream arteries, is associated with cognitive impairment and neurodegenerative diseases. The study of this phenomenon requires brain-wide pulsatility measurements, with large penetration depth and high spatiotemporal resolution. The development of dynamic ultrasound localization microscopy (DULM), based on ULM, has enabled pulsatility measurements in the rodent brain in 2D. However, 2D imaging accesses only one slice of the brain and measures only 2D-projected and hence biased velocities . Herein, we present 3D DULM: using a single ultrasound scanner at high frame rate (1000-2000 Hz), this method can produce dynamic maps of microbubbles flowing in the bloodstream and extract quantitative pulsatility measurements in the cat brain with craniotomy and in the mouse brain through the skull, showing a wide range of flow hemodynamics in both large and small vessels. We highlighted a decrease in pulsatility along the vascular tree in the cat brain, which could be mapped with ultrasound down to a few tens of micrometers for the first time. We also performed an intra-animal validation of the method by showing consistent measurements between the two sides of the Willis circle in the mouse brain. Our study provides the first step towards a new biomarker that would allow the detection of dynamic abnormalities in microvessels in the brain, which could be linked to early signs of neurodegenerative diseases.

Changes in regional and temporal patterns of activity associated with aging during the performance of a lexical set-shifting task.

Some older individuals seem to use compensatory mechanisms to maintain high-level performance when submitted to cognitive tasks. However, whether and how these mechanisms affect fronto-striatal activity has never been explored. The purpose of this study was to investigate how aging affects brain patterns during the performance of a lexical analog of the Wisconsin Card Sorting Task, which has been shown to strongly depend on fronto-striatal activity. In the present study, both younger and older individuals revealed significant fronto-striatal loop activity associated with planning and execution of set-shifts, though age-related striatal activity reduction was observed. Most importantly, while the younger group showed the involvement of a "cognitive loop" during the receiving negative feedback period (which indicates that a set-shift will be required to perform the following trial) and the involvement of a "motor loop" during the matching after negative feedback period (when the set-shift must be performed), older participants showed significant activation of both loops during the matching after negative feedback period only. These findings are in agreement with the "load-shift" model postulated by Velanova et al. (Velanova K, Lustig C, Jacoby LL, Buckner RL. 2007. Evidence for frontally mediated controlled processing differences in older adults. Cereb Cortex. 17:1033-1046.) and indicate that the model is not limited to memory retrieval but also applies to executive processes relying on fronto-striatal regions.

Investigating the long-lasting residual effect of a set shift on frontostriatal activity.

Previous studies have shown the involvement of the ventrolateral prefrontal cortex (PFC) and the caudate nucleus when performing a set shift. However, the effect of set shifting on the frontostriatal activity observed during the later trials within a series of same-set classifications has yet to be determined. Here, young healthy adults underwent the functional magnetic resonance imaging while performing a card-sorting task in which the classification rule was provided prior to each trial. We observed a significant activation in the dorsolateral PFC, regardless of whether a set shift occurred or not. By contrast, the ventrolateral PFC and caudate nucleus showed an increased activity in both the shifting trials versus the control and in trials where the same rule was applied for a few trials before a set shift occurred, unlike trials where the same rule was applied for a longer period. Finally, decreased activity in the caudate nucleus correlated with an increasing trial position in trials where no set shift occurred, suggesting that the more a rule is executed, the better it is established. We argue that a new rule needs to be performed multiple times until the brain areas usually associated with the set shifting are no longer significantly required anymore.

Ultrafast Cardiac Imaging Using Deep Learning for Speckle-Tracking Echocardiography.

High-quality ultrafast ultrasound imaging is based on coherent compounding from multiple transmissions of plane waves (PW) or diverging waves (DW). However, compounding results in reduced frame rate, as well as destructive interferences from high-velocity tissue motion if motion compensation (MoCo) is not considered. While many studies have recently shown the interest of deep learning for the reconstruction of high-quality static images from PW or DW, its ability to achieve such performance while maintaining the capability of tracking cardiac motion has yet to be assessed. In this article, we addressed such issue by deploying a complex-weighted convolutional neural network (CNN) for image reconstruction and a state-of-the-art speckle-tracking method. The evaluation of this approach was first performed by designing an adapted simulation framework, which provides specific reference data, i.e., high-quality, motion artifact-free cardiac images. The obtained results showed that, while using only three DWs as input, the CNN-based approach yielded an image quality and a motion accuracy equivalent to those obtained by compounding 31 DWs free of motion artifacts. The performance was then further evaluated on nonsimulated, experimental in vitro data, using a spinning disk phantom. This experiment demonstrated that our approach yielded high-quality image reconstruction and motion estimation, under a large range of velocities and outperforms a state-of-the-art MoCo-based approach at high velocities. Our method was finally assessed on in vivo datasets and showed consistent improvement in image quality and motion estimation compared to standard compounding. This demonstrates the feasibility and effectiveness of deep learning reconstruction for ultrafast speckle-tracking echocardiography.

Facing points of view: Representations on adjuvant endocrine therapy of premenopausal patients after breast cancer and their healthcare providers in France. The FOR-AD study.

PURPOSE: Adjuvant endocrine therapy (ET) for 5-10 years is the backbone of the therapeutic strategy in patients with hormone receptor positive (HR+) early breast cancer (BC). However, long-term adherence to adjuvant ET represents a major challenge for most patients. According to prior studies, side effects of adjuvant ET are an important reason for poor adherence. In contrast, better communication and relational bond between patients and healthcare providers (HCPs) may improve adherence. The FOR-AD (Focus on non-adherence) study aimed at better understanding the representation of adjuvant ET by patients and their HCPs, in order to improve the care process. METHODS: Three focus groups of premenopausal women (receiving adjuvant ET for variable amount of time) and two focus groups of HCPs (including oncologists, pharmacists, and nurses) were conducted, each including around ten participants. Thematic analyses using a general inductive approach were constructed to report participants' representations. RESULTS: Two main themes emerged across groups, and appeared of major importance. Representations on adjuvant ET were often homogenous within each group, but differed between patients and their HCPs. The relationship between both groups was considerably discussed, particularly its importance in facilitating adherence to adjuvant ET. Suggestions on improving the care process were also given, such as systematically including psychologists in follow-up care paths and having a nurse navigator follow patients under treatment with adjuvant ET. CONCLUSION: The present qualitative exploration may help buildi future tailored interventions to improve adherence to adjuvant ET, in particular regarding the role of nurse navigators.

Implementing a PROACTive Care Pathway to Empower and Support Survivors of Breast Cancer.

PURPOSE: Optimal comprehensive survivorship care is insufficiently delivered. To increase patient empowerment and maximize the uptake of multidisciplinary supportive care strategies to serve all survivorship needs, we implemented a proactive survivorship care pathway for patients with early breast cancer at the end of primary treatment phase. METHODS: Pathway components included (1) a personalized survivorship care plan (SCP), (2) face-to-face survivorship education seminars and personalized consultation for supportive care referrals (Transition Day), (3) a mobile app delivering personalized education and self-management advice, and (4) decision aids for physicians focused on supportive care needs. A mixed-methods process evaluation was performed according to the Reach, Effectiveness, Adoption, Implementation and Maintenance framework including administrative data review, pathway experience survey (patient, physician, and organization), and focus group. The primary objective was patient-perceived satisfaction with the pathway (predefined progression criteria for pathway continuation ≥70%). RESULTS: Over 6 months, 321 patients were eligible for the pathway and received a SCP and 98 (30%) attended the Transition Day. Among 126 patients surveyed, 77 (66.1%) responded. 70.1% received the SCP, 51.9% attended the Transition Day, and 59.7% accessed the mobile app. 96.1% of patients were very or completely satisfied with the overall pathway, whereas perceived usefulness was 64.8% for the SCP, 90% for the Transition Day, and 65.2% for the mobile app. Pathway implementation seemed to be positively experienced by physicians and the organization. CONCLUSION: Patients were satisfied with a proactive survivorship care pathway, and the majority reported that its components were useful in supporting their needs. This study can inform the implementation of survivorship care pathways in other centers.

Physiologic cardiovascular strain and intrinsic wave imaging.

Cardiovascular disease remains the primary killer worldwide. The heart, essentially an electrically driven mechanical pump, alters its mechanical and electrical properties to compensate for loss of normal mechanical and electrical function. The same adjustment also is performed in the vessels, which constantly adapt their properties to accommodate mechanical and geometrical changes related to aging or disease. Real-time, quantitative assessment of cardiac contractility, conduction, and vascular function before the specialist can visually detect it could be feasible. This new physiologic data could open up interactive therapy regimens that are currently not considered. The eventual goal of this technology is to provide a specific method for estimating the position and severity of contraction defects in cardiac infarcts or angina. This would improve care and outcomes as well as detect stiffness changes and overcome the current global measurement limitations in the progression of vascular disease, at little more cost or risk than that of a clinical ultrasound.