N = 30 teachers) participated in a pilot test of the usability of MTT materials across 5 months in one school year. Three teams elected to use MTT materials, and three elected to be a comparison group who continued their typical practices. Teams adopting MTT materials were observed to do so with good implementation integrity, and reported satisfaction with the intervention. Compared to typical practice teams, those using MTT were observed to spend more meeting time discussing teaching practice and less time discussing logistics/mechanics, and engaged in more video sharing and feedback to team members in the MTT sessions that explicitly encouraged this. The number of MTT meetings completed by a team, as well as spending more time discussing teaching practices and video sharing (but not feedback provided) during team meetings, predicted students’ self-reports of greater engagement and observations of higher levels of emotional support provided in the classroom. Implications for translating empirically supported interventions from the lab to real-world school settings are discussed.The My Teaching Partner-Secondary (MTPS) program demonstrated improvements in classroom interactions and student outcomes in secondary schools using one-on-one coaching between study staff and teachers. Despite promising results, the time, cost, and oversight from a university research team may pose barriers to adoption of coaching programs like MTPS at scale. The My Teaching Team (MTT) project sought to translate key ingredients from MTPS into existing professional development contexts that are already built into many middle and high school educators’ weekly schedules: co-planning or professional learning community meetings. Six teams of secondary teachers ( Engaging and motivating interpersonal interactions with classroom teachers are key to optimizing learning outcomes among adolescents . My TeacDevelopmental research indicates that adolescents’ experiences of relational support, autonomy and competence, and understanding of the relevance of academic content all promote their learning e.g., . Specifivia making personal connections, being responsive to students’ needs, and considering students’ perspectives; organizing classroom activities to maximize engagement; and offering instructional supports that encourage dialogue, analysis, and metacognition. In MTPS, the coaches are study staff members, who are trained and supervised by the research team.The MTPS program was designed to help secondary school teachers incorporate these principals into their classroom interactions. Teachers engaged in one-on-one, biweekly meetings over a school year with a dedicated coach who encouraged teachers to video record their own classroom practices. These videos (as well as video exemplars of other teachers’ classrooms) were subsequently reviewed by both the teachers themselves and their coaches . CoachesResults from several randomized trials , 2015 doMy Teaching Partner-Secondary efficacy might be driven by its focus on observing and identifying effective teacher-student interactions in videos, using the lens of the CLASS-S to focus on interactions that provide relational support, foster student autonomy, and emphasize content relevance. Indeed, teachers who spent more time reviewing and analyzing their own videos with prompts from their coach demonstrated greater changes in their classroom practice . Other sAlthough the MTPS program garnered strong empirical support in research trials, schools wanting to adopt MTPS more broadly may face challenges to making these effective supports available at scale. These challenges include schools having to change their existing professional development structure to accommodate coaching, teachers finding time outside other responsibilities to engage in coaching, monetary costs for hiring external coaches or training and supervising local coaches to ensure fidelity to the model, and acquiring enough trained coaches to implement the program. Relatedly, because the coaching occurs one-on-one betwen a study staff member and a teacher, MTPS may be less likely to become embedded in school culture, which may in term limit the potential for ripple effects into the school and the sustainability of the intervention.We therefore sought to embed the active ingredients of MTPS into an alternative delivery format that aligns with professional development opportunities that already exist in many schools. Most teachers across the United States (75–80%) participate in regular, collaborative team meetings on issues of instruction . This teGuided by existing research on teaching teams, as well as on what core ingredients made MTPS successful, we created the MTT intervention. A side-by-side comparison of MTPS and MTT logistic practices and components is provided in The structure of MTT sessions encourages teachers to engage in collaborative practices that mirror the one-on-one coaching in MTPS. These include self-reflecting on successes and challenges in interactions with students, providing supportive and actionable feedback to peers, planning to expand successful practices or engage in new practices, and recording implementation of those plans for later review and analysis using guided prompt questions. After teachers have had the opportunity to try their plans in class, sessions focus on sharing video clips of their plan implementation with their peers and asking for specific feedback.Unlike MTPS, MTT uses a group format for coaching and existing school-based personnel as group facilitators. This reduces the cost of coaching as well as increases sensitivity to specific school-level constraints, resources, and needs. Empowering teachers to lead their own discussions builds capacity within schools and holds promise for fostering teachers’ sense of professionalism, ownership, and collegiality  that canThe present study explored the feasibility and impact of translating elements of the effective MTPS program into a teacher-led team meeting format, MTT. In this pilot study, three teaching teams of secondary school teachers elected to use MTT materials, and three teams served as a comparison group who continued their typical practices.Among the teams who adopted MTT, we examined time teachers spent using MTT materials and integrity of implementation. We also compared MTT teams, relative to teams in the typical practice comparison group, in their use of research-supported collaborative practices and in what was discussed during meetings.Among the teams who adopted MTT, we collected teachers’ reports of their experiences using MTT materials, and examined whether these perceptions differed based on teacher characteristics including education level, years of experience, motivational beliefs, and perceptions of school professional learning environment.Across all teams, we examined whether the number of MTT sessions completed related to observations and student self-reports of teacher-student interactions and student engagement.We examined whether the discussion topics and collaborative practices that were more common in MTT team meetings related to observations and student self-reports of teacher-student interactions and student engagement.Participants were six pre-existing, discipline-based teacher teams (30 teachers) in two middle and two high schools within one suburban district in the southeastern United States during the 2019–2020 academic year. Three teams at three schools (19 teachers) elected to use MTT practices, and three teams in another school (11 teachers) elected to continue with their typical practices. All teams  agreed to allow the research team to collect data on their team interactions, classroom interactions, and student experiences .Teams who elected to use MTT materials voted unanimously to engage in the research project. In addition to participating in data collection, this required all team members to attend orientation meetings, try a new structure and focus in team meetings, record interactions in their classroom, review those recordings and share segments with their teammates, and additionally required the team facilitator (1 per team) to attend monthly facilitator support sessions and lead their teams through the MTT process. These teams verbally communicated to study personnel that their existing goals were well aligned with the MTT goals of sharing practices and focusing on engaging students and they saw this as an opportunity to push their agenda forward with the help of the provided suite of resources.Teams who elected to be a typical practice comparison group by continuing their existing team meeting practices but engaging in all data collection communicated to study personnel that they felt too overwhelmed by existing initiatives and demands on team meeting time to take on the extra tasks that MTT participation would involve . Nonetheless, they were invested in engaging in best practices in team meetings, their school was focused on increasing student engagement and relatedness, and they were interested in contributing to the study and in applying what was learned from the research in the future.Although teams were not randomized into conditions, teachers in the MTT and comparison groups were overall similar in level of education, years of teaching experience, self-identified gender, and self-identified race/ethnicity see . There wt(28) = 3.11, p = 0.004]). An average of 10 students per MTT classroom, and three students per comparison group classroom, participated by completing surveys about their classroom experiences. Although data on number of students enrolled in each class was not collected for all classrooms, it is very likely that differences in numbers of consented students were related to higher investment in distributing and collecting consent forms by MTT teachers in comparison with comparison group teachers, rather than reflecting systematically larger class sizes for MTT teachers.A total of 224 students from enrolled teachers’ classrooms volunteered to provide study data  met for at least 45 min weekly. We began recruitment by providing study information to secondary school principals and department specialists. Among those expressing interest, information was shared with teaching team leads, who then shared study details with all members in their teams. Teams who decided to enroll in the research study either agreed to adopt MTT materials or to be a typical practice comparison group.In October, teachers on MTT teams attended 2.5 h of orientation  with study personnel. They were given consent/assent forms to distribute to students/guardians in a “typical class” chosen by the teacher, and completed surveys about their teaching beliefs and practices. Around the end of the first semester, after teachers had begun using MTT materials , teachers permitted study staff to video-record one period of the typical class they had selected. In the second semester , consented students completed surveys about their experiences.Existing lead teachers served as their team’s MTT facilitator, guiding teams through MTT sessions and video-recording these meetings. To support implementation integrity, a defined agenda and multi-media materials were provided for each MTT session, and all teachers received handbooks that explained the MTT topics. Facilitators also met with a study staff member 1 h per month to discuss implementation and preview upcoming session materials.Teachers in comparison teams attended a 45-min orientation where research activities were explained, student/guardian consent/assent forms were provided, and teachers completed the same surveys about their teaching as MTT teachers. Teachers in the comparison group permitted project staff to video-record one period of a “typical class,” and consented students completed surveys about their experiences in the same timeframes as occurred for MTT teachers. Each team leader was asked to video-record one team meeting per quarter.In order to address Research Question 1 (feasibility of implementing MTT and impacts on use of meeting time), MTT teams were asked to submit videos of their MTT meetings; 78% of such sessions were successfully video recorded . Typical practice comparison teams submitted one team meeting per quarter for video coding.Videos were double coded for indicators of implementation integrity, discussion topics, and research-supported collaborative practices; see descriptions below. The coders were research assistants who met every other week to discuss codes and minimize drift. Intraclass correlation coefficients ICC,  between via facilitators’ reports and verified with dated video-recordings of submitted meetings. MTT teachers also reported the amount of time spent on MTT activities outside of meetings .Dosage is operationalized as the number of MTT sessions held for each team and was assessed the agenda item was not observed to be covered, 1 = the item was covered incompletely or with some lack of integrity, and 2 = the agenda item was covered with complete integrity).In MTT teams only, coders scored each session video for adherence to MTT program content (ICC = 0.749). Each scored item corresponded with a specific agenda item provided to facilitators , and other topics unrelated to teaching. The challenges and the other topics codes came from pilot findings on their prevalence in team meetings. For each session, time spent on each topic was coded on a four-point scale . ICCs for these codes ranged from 0.812 to 0.879.Both MTT and typical practice comparison group meetings were coded for the amount of meeting time teachers spent discussing six different topics. Coded topics included: shared actionable ideas about teaching, self-reflected on practices, reviewed video of team members’ teaching, provided feedback to peers, and made plans for implementing effective teaching practices. The remaining two practices, discussed student data and discussed other professional development experiences, were not part of the MTT intervention, and were included to determine the extent to which MTT might pose an opportunity cost by reducing discussions in these areas in comparison to typical practice.Seven practices highlighted by previous research  as indicdid not occur, 1 = cursory occurrence, 2 = substantive occurrence). ICCs for these codes ranged from0.613 to 0.758, with the exceptions of shared actionable ideas  and discussed other professional development (never occurred).For each session, the amount that the team engaged in each research-supported collaborative practice was coded on a three-point scale (0 = In order to address Research Question 2 (teacher perceptions of MTT usefulness and predictors of these perceptions), teachers in the MTT group completed several self-report questionnaires.strongly disagree; 5 = strongly agree). These two items were correlated at r = 0.67 and aggregated to create an overall score.Following each MTT session, teachers were asked rate (1) whether they felt the meeting was worth their time, and (2) whether they would change teaching practices as a result of the meeting, on a 1–5 Likert scale  and had high internal consistency in our sample (α = 0.97). We also adapted this scale to include four additional items that asses teacher beliefs about the malleability of teaching ability , which also showed high internal consistency in our sample (α = 0.82).As a second potential predictor of satisfaction with MTT materials, the Mindset about Intelligence scale  was giveResearch Question 3 and Research Question 4 (how MTT dosage and use of the practices that MTT promoted related to teachers’ classroom interactions with their students and student engagement) were assessed using classroom observations and student self-report questionnaires.We coded classroom videos using the CLASS- S . The CLAn = 6 classrooms) or three (n = 23 classrooms) 15–20-min segments for coding purposes. Segment codes were averaged, resulting in one data point per classroom for each CLASS-S domain. Coders were certified reliable on the CLASS-S (assigning 80% or more codes within one point of master coders on five test recordings), and the average ICC of double-coded segments in the present study (19% of segments) was 0.70. Reliability coefficients for variables used as outcomes were in the “fair” to “good” range (One approximately 45-min class period was recorded for 29 participating teachers (one classroom was not recorded due to the teacher being on leave during the recording window). This recording was divided into two . Behavioral engagement contained seven items about investment and involvement in classroom activities . Emotional engagement included six items about students’ value of and positive and negative reactions to classroom learning and activities . All demonstrated acceptable to excellent internal consistency in our sample .We assessed students’ self-reports of their engagement in class using scales from Classroom Assessment Scoring System Student Report  28.0 and Stata 15.1. For Research Question 1, we compared research supported collaborative practices and discussion topics in MTT sessions to those in typical practice comparison group sessions using Mann Whitney ur study . We ran Descriptive statistics of key study variables are in My Teaching Teams began using MTT materials in late October 2019 and were scheduled to meet approximately twice monthly until late May 2020. In March of 2020, however, all in-person instruction in the participating school district ceased due to the global pandemic, and so did our research activities. Up until March 2020, MTT teams’ meeting schedules closely approximated the recommended frequency . Before instruction ceased, MTT teams held a total of 7–12 MTT sessions (mean = 9 per team); this included four to six Focus/Plan sessions, two to five recordings of classroom practice times per teacher, and three to six Reflect/Share sessions. This placed all teams roughly on target to complete 16 sessions had the school year continued as anticipated.Between October and mid-March, MTT teachers reported spending, on average, 5 h 40 min of team meeting time participating in MTT sessions and 3 h 30 min analyzing and reflecting on their own classroom video footage. This translates to a mean time of 26 min/week spent on MTT-related activities.discussion of the MTT topic in Focus/Plan sessions and sharing classroom videos in Reflect/Share sessions.Separate ratings were calculated for implementation integrity in Focus/Plan sessions (devoted to new topics and planning implementation) and Reflect/Share sessions (devoted to reflection and sharing of implementation). Results are summarized in reviewing video of team members’ teaching and providing feedback to peers relative to comparison group sessions. MTT meetings were not rated significantly differently from comparison group meetings in self-reflection on practices, making plans to implement effective teaching practices, or discussing student data. All observed team meetings included sharing of actionable ideas about teaching and no observed team meetings included discussion of other professional development experiences.Overall, teachers in MTT teams reported high perceptions of the utility of MTT sessions, with average scores of 4.47 (SD = 0.38) on a 5-point scale ranging from strongly disagree to strongly agree see .p = 0.03]. Also, the more positively teachers perceived the learning climate at the school, the more useful they perceived MTT to be . Neither years of experience teaching , growth mindset about intelligence , or growth mindset about teaching ability , were significantly associated with perceptions of MTT utility , lity see .For this research question, we used multiple linear regression to assess whether the number of MTT sessions in which teachers participated predicted classroom experiences, including observed teacher-student interactions and student engagement, and student self-reports of their engagement and their perception of classroom interactions. For teachers in the MTT condition, we recorded the number of MTT sessions they attended before outcome measure was administered; for comparison group teachers, the number of MTT sessions attended was always zero. We combined the MTT and comparison groups in this analysis to increase sample size.Regarding assumptions for running linear regressions, we found that in the models with observed interactions, the residuals were normally distributed, there was sufficient homogeneity of variance among the residuals, and no issue was found with multi-collinearity. In the models with student-reports, the residuals were slightly positively skewed, which could contribute to the assessment of significance being less reliable. We present the results from the models without robust standard errors, but results were comparable when robust standard errors were used.p = 0.04), but not instructional support or student engagement. The number of MTT sessions that teachers attended before the student surveys occurred (range 0–9 sessions) predicted student-report of more emotional  and behavioral engagement , and instructionally supportive interactions , but did not predict their cognitive engagement, or perception of emotionally supportive interactions in the classroom. Given the slight skew of the residual distribution in these models and given the relatively large p-value, we view these findings as preliminary and in need of replication.The number of MTT sessions that teachers attended before classroom observations occurred (range 0–3 sessions) predicted more observed emotional support in the classroom , instructionally supportive interactions , and student engagement . This variable was also positively associated with students’ reports of their behavioral engagement , emotional engagement , emotionally supportive interactions , and instructionally supportive interactions . In contrast, the time teachers spent discussing logistics/mechanics was negatively associated with observed emotionally supportive interactions , instructionally supportive interactions , and student engagement , as well as students’ reports of their behavioral engagement , emotional engagement , cognitive engagement , emotionally supportive interactions , and instructionally supportive interactions .Time teachers spent discussing teaching practice in meetings was positively associated with observed emotionally supportive interactions , instructionally supportive interactions , and student engagement , as well as students’ reports of their behavioral engagement , emotional engagement , emotionally supportive interactions , and instructionally supportive interactions . However, providing feedback to peers was negatively associated with student report of emotional support .The extent to which teams shared video of team members’ classroom interactions in meetings positively predicted observed emotionally supportive interactions  could be retained when the format of the intervention was adapted to fit into a different professional development structure–team meetings led by the teachers themselves (MTT).Teams were generally able to implement the MTT protocol as designed and regarded it as useful. Before the COVID-19 pandemic caused teaching teams to devote all of their attention to transitioning to remote instruction, teams covered approximately one MTT topic per month (holding two meetings and recording classroom interactions in between meetings), and did so with reasonable implementation integrity (particularly in Reflect/Share sessions). MTT activities took about half an hour weekly of teachers’ time, which does not seem prohibitive given the national average time teachers report having to collaborate with colleagues is close to 3 h per week . Using tThe potential payoff for taking this time is that MTT teams spent a greater proportion of their meetings focused on teaching practices, and in the Reflect/Share sessions, they engaged in more sharing of videos of classroom interactions and provided more teaching focused feedback to one another. That the comparison group teams observed in this study spent less than half of their meetings discussing teaching practices and more than that focused on logistics/mechanics (such as when yearbooks would arrive or holiday celebrations would take place) resonates with previous findings that under typical circumstances, teacher teams rarely engage in transformational discussion about their teaching  or in joThere did not appear to be a significant opportunity cost of using MTT, as MTT and comparison group teams discussed student data and other professional learning at similar rates. In fact, using existing frameworks for conceptualizing teacher collaboration, our data suggest that the comparison teams were functioning at the “storytelling and scanning for ideas”  or the “Teacher perceptions of MTT utility were overall quite high. However, our findings that greater perceived utility was predicted by lower education level (bachelor’s vs. master’s degree) and a more supportive professional learning environment of the school, suggest directions for future research regarding what works for whom under what conditions see . CapitalPreliminary findings suggest that dosage of MTT, and more meeting time spent discussing teaching practice and reviewing video of team members’ teaching, are associated with multiple indicators of more positive classroom experiences, both observed and student-reported. Thus, this pilot study of MTT shows promise for supporting impactful teacher collaboration. In contrast, greater discussion of logistics/mechanics in team meetings (which was less common in teams using MTT) was consistently associated with less positive classroom outcomes. Contrary to hypotheses, teachers’ greater provision of feedback to peers in teacher team meetings was associated with less positive scores on one outcome variable: student self-reports of teacher emotional support. Perhaps our measure of providing feedback needs to be refined, such as by including specificity regarding whether the feedback is on-topic, strengths-focused, or actionable.The indications that MTT dosage and use of discussion topics and research-supported collaborative practices encouraged by MTT were associated with more positive classroom experiences could have occurred because more skilled teachers are likely to volunteer to try new team meeting protocols that require sharing of their practices. However, it could also indicate positive effects of using MTT materials more frequently and engaging in the types of interactions central to MTPS and encouraged by the MTT protocol . Specifically, these factors could contribute to more student engagement experienced at an emotional (“I look forward to class”) and behavioral level (“I keep trying even when the work gets hard”); greater student perceptions that teachers support their learning ; and higher quality observed emotional support expressed in teacher-student interactions . These indicators of effective classroom interactions and student experiences are well-established to relate to student learning outcomes , which sTranslating empirically supported treatments from university labs to real-world educational settings often requires paring down protocols to their most essential elements, offering autonomy and choice for users within well-articulated frameworks, and providing supports to practitioner-leaders that fit into their available time. The Reflect/Share MTT sessions (which were more streamlined and focused on teachers sharing their own practices) had somewhat higher implementation integrity and use of some research-supported collaborative practices in comparison with Focus/Plan sessions (which had more components and involved orienting to a new topic and articulating plans to incorporate practices related to that topic into existing lessons). In future refinements of MTT, we plan to reduce the number of components in team meetings and build in more choice points, such as allowing teams to decide which topics to cover in a given school year or how many meetings they devote to each topic. We also plan to create options for more time to be spent in Reflect/Share sessions.via video), and providing feedback as compared with comparison group meetings, these supports appear to have been successful in enhancing effective collaboration. However, future efforts may place more emphasis on ensuring that there are high-performing colleagues participating in each team (Shifting from the one-on-one coaching format of MTPS (where coaches were highly trained study staff members) to the peer-coaching approach in MTT brought tradeoffs that could influence the impact of the intervention. For example, in order to achieve support from administrators and fit into the structure of the existing school system, MTT needed to reduce intervention intensity to bi-weekly group meetings and once monthly classroom video recording and sharing as opposed to the twice monthly video recording and review that characterized the more intensive individualized coaching in MTPS. MTT also removed intervention components that may be important drivers of change, such as teachers responding to coach-selected video segments and tailored written prompts, and receiving advice from a coach extensively trained and supervised by a research team. In MTT, all these elements were provided in a self- or peer-coaching format. Although peer coaching has demonstrated positive impacts on teaching efficacy , these iach team .Another key in shifting from expert one-on-one coaching to group-based peer coaching is group leadership. In the MTT intervention design, the teacher who serves in the position of team facilitator serves a key role in ensuring that discussions are in-depth and focused, that conversations about videos provide accurate and insightful analysis, that there is sufficient psychological safety for teachers to bring their concerns to the group, and that team members will receive both accurate and non-judgmental feedback and effective suggestions for enhancing practices from peers (a role served by the coach in MTPS). In this pilot study, team facilitators received monthly support from project staff that included staff reviewing video of each MTT team meeting and highlighting effective practices observed in meetings as well as offering suggestions for strategies to enhance MTT implementation. Future efforts to support high-impact team collaborations such as MTT should include provisions to provide practice-based supports for teachers serving in the role of facilitator or team lead to ensure that these leaders have the capacity to chart a positive course for team interactions and have the skill to recognize and give feedback on both more and less effective teaching practices.An element added in the MTT delivery format that is not present in individual coaching protocols (such as MTPS) is the opportunity for teachers to receive support from multiple perspectives and from their peers. Notably, teachers may feel that their peers have more credible suggestions than do external coaches, as they share the same role, rather than being one step removed from the classroom. Relatedly, the group format of MTT adds an element of collective collaboration that may feel less prominent in individual coaching. This spirit of “joint work” , where tA strength of this pilot study was its ambition to translate an intervention established in the lab (MTPS) into a more sustainable and feasible format for adoption by schools. Another strength was the multiple sources of data obtained, including teacher and student self-reports, and observational coding of team meetings and teacher-student interactions in the classroom.Due to small numbers of participants, this pilot study has significant limitations in statistical power to detect effects and substantial restrictions to generalizability. Relatedly, we did not control for family-wise error rate across analyses, because of the pilot nature of our study. The lack of randomized assignment of teams to MTT or typical practice comparison conditions and the fact that all three comparison teams were in one school setting, whereas the MTT teams were distributed across three different schools, further prohibit causal conclusions related to observed differences in classroom experiences. The existing culture around professional learning in the comparison school may have differed from the culture in the three MTT schools, and there may have been important variability across the three MTT schools that could influence team practices, teacher-student interactions, and student engagement as well. However, we did collect data on teachers’ perceptions of the professional learning environment at their school in the fall of the school year prior to beginning the intervention and found that there were no school-level differences in teachers’ perceptions of the school learning environment  or in teachers reports of work-related stress.There were also substantial differences in numbers of students consenting to complete surveys between classrooms of teachers in the comparison group vs. in classrooms of teachers utilizing the MTT materials, which we attribute to differences in teacher enthusiasm for the research program.In addition, both the MTT intervention itself and associated data collection were truncated due to the global COVID-19 pandemic. Analyses using number of sessions held was utilized as a method for enhancing our understanding of potential impacts, but it is incomplete. Further research is necessary to tease apart whether MTT truly enhanced team practices, teaching practices, and student experiences or whether teams who initially volunteered to try the practices were already more likely to engage in effective team practices and have better classroom interactions with students.In light of all of these limitations, we consider all of these analyses to be preliminary and encourage replication.Despite these limitations, the pattern of preliminary results obtained suggests that MTT shows promise as a scalable, feasible way to embed some of the active ingredients of the successful MTPS coaching model into a teaching team meeting format, which upwards of 75% of teachers already use . The nat


Mechanical properties of the arterial walls could provide meaningful information for the diagnosis, management and treatment of cardiovascular diseases. Classically, various experimental approaches were conducted on dissected arterial tissues to obtain their stress–stretch relationship, which has limited value clinically. Therefore, there is a pressing need to obtain biomechanical behaviors of these vascular tissues in vivo for personalized treatment. This paper reviews the methods to quantify arterial mechanical properties in vivo. Among these methods, we emphasize a novel approach using image-based finite element models to iteratively determine the material properties of the arterial tissues. This approach has been successfully applied to arterial walls in various vascular beds. The mechanical properties obtained from the in vivo approach were compared to those from ex vivo experimental studies to investigate whether any discrepancy in material properties exists for both approaches. Arterial tissue stiffness values from in vivo studies generally were in the same magnitude as those from ex vivo studies, but with lower average values. Some methodological issues, including solution uniqueness and robustness; method validation; and model assumptions and limitations were discussed. Clinical applications of this approach were also addressed to highlight their potential in translation from research tools to cardiovascular disease management.  Mechanical forces play a fundamental role in the initiation, development and final critical clinical events of cardiovascular diseases (CVD) such as stroke and heart attack ,2. As diGreat effort has been exerted to perform ex vivo experiments on human arterial walls in health and disease, and important conclusions on their mechanical behaviors were drawn ,11,12. EEven though considerable ex vivo experimental data have accumulated over the years, they only provided biomechanical information of arterial diseases at one time-point, which is very limited for clinical applications for two reasons: (a) ex vivo arterial tissues isolated from the vascular tree might not represent the exact mechanical properties as in the living subjects ; (b) chaThis review paper aims to review the studies to characterize subject-specific arterial wall properties in vivo using a finite-element-model-based updating approach (FEMBUA). Material properties of the aorta, carotid and coronary arteries determined from the novel FEMBUA and classical ex vivo experimental methods were compared to investigate whether any discrepancy in material properties exists for both approaches. Several in vivo methods were proposed to characterize subject-specific material properties of arterial walls in vivo or even in situ. The principle of these methods is to acquire the arterial wall deformation and corresponding loading conditions from clinical data, and link them to obtain the arterial material properties. Thanks to the considerable advances in medical imaging technologies, dynamic vessel motion can be recorded in vivo via time-resolved imaging modalities, such as ultrasound (US), cine magnetic resonance imaging (MRI), cine intravascular ultrasound (IVUS) and electrocardiogram (ECG)-gated computed tomography (CT). Blood pressure conditions are also measured as the loading conditions to drive the vessel to pulsating deformations. Simple and sophisticated methods were proposed in the existing literature based on different assumptions. Early in vivo studies of vessel material properties assumed that the arterial wall was a straight thin-walled circular cylinder with linear elastic material properties, and its stiffness could be estimated by Peterson’s modulus (denoted as Ep) using the formula ,20: Ep =ate E as : E = ∆P Another simple and commonly used formula to estimate the Young’s modulus of the arterial wall is the Moens–Korteweg equation, which relates the Young’s modulus of the blood vessel with pulse wave velocity (PWV) from the heart to the peripheral vascular : (3)PWV=found in . These sfound in ,23. HoweTo obtain more sophisticated nonlinear anisotropic mechanical behavior of arterial walls, an analytical approach was employed with constitutive models incorporated to characterize their nonlinear stress–strain relationship by identifying the material parameters in the constitutive models . In thisThe in vivo quantification of mechanical properties of arterial tissues based on in vivo medical images is intrinsically an inverse problem ,28. The Step 1, time-resolved in vivo medical image acquisition with tissue deformation under dynamic loading conditions; Step 2, image-based FEM to simulate the tissue deformation corresponding to in vivo loading conditions with tissue material properties to be determined; Step 3, constitutive parameter identification strategy to find the correct tissue material properties so that tissue deformation in FEM would recover that on in vivo images. Full descriptions of these steps are given in the following subsections. In Vivo Clinical Data Acquisition: To visualize the vascular deformation in vivo, time-resolved imaging modality was employed to obtain a series of medical images to track arterial deformation during one cardiac cycle. Vessel/Tissue Motion Tracking: Arteries deform under time-varying loading conditions. One simple way to approximate the deformation is to calculate the changes in lumen circumference, lumen area or lumen volume between two cardiac phases and consider it as vessel deformation under two different pressure conditions. Typically, diastolic and systolic phases were selected to quantify the deformation of the arterial wall, with the diastolic phase often treated as the “reference” phase and systolic phase as the deformed phase see . This waIn the FEMBUA, image-based finite element models (FEMs) are constructed to calculate plaque stress/strain conditions, while the parameter values in those models are determined iteratively so that model solutions can satisfy measured vessel/tissue deformation conditions. The FEM models constructed to identify the material properties of the arterial wall in the literature were mainly structure-only models to expedite the updating approach detailed in Arterial Wall Geometry Reconstruction: 3D US, CT, MRI and IVUS images can show the cross-section of the arterial wall, and the images corresponding to the diastolic phase were used to reconstruct the referenced geometry of the arterial wall ,42,43. FPre-Stressing Geometry Estimation: Since medical images were acquired in vivo, the referenced geometry reconstructed were loaded with the physiological pressure on the luminal surface, axially stretched, and other loading conditions . Thus, a pre-stressing algorithm should be performed to obtain no-load geometry (corresponding to zero-pressure condition) based on the referenced geometry as the initial geometry to start the computational simulation. To this end, Guo et al., employed a pre-shrink stretch procedure by shrinking the referenced coronary artery geometry circumferentially and axially to obtain the no-load geometry . SpeelmaConstitutive Models for Arterial Wall: Arterial walls are generally treated as elastic, either anisotropic or isotropic, nearly-incompressible, homogeneous material. They could also be considered as heterogeneous material if different tissue components were included . SeveralMathematical Equations Governing Arterial Wall Motion: The mathematical equations governing arterial wall motion consist of equations of motion, strain-displacement relations and the stress–strain relations that could be derived from strain energy density functions for hyperelastic materials . With a Boundary Conditions: Proper boundary conditions were applied to FEM to mimic the loading conditions on the arterial wall in vivo. The most important loading condition that triggers vascular deformation is pulsating pressure prescribed on the luminal surface on the arterial wall . It corrSolution Method for the Finite Element Model: Finite element mesh could be generated using commercial finite element software such as ANSYS, ADINA, Abaqus or self-developed in-house software. FEM models were further solved using sophisticated numerical schemes built in these software. Mesh analysis should be performed to guarantee the accuracy of the model solution, which would affect the accuracy of material parameter estimation . To obtain vessel material properties correctly, vessel deformation from FEM should match those from in vivo medical images . A cost Cost Function Definition: Most studies constructed the cost function as the sum of the squares of the nodal deformation differences between FEM vessel morphology and vessel geometry reconstructed from images ,36. SomeOptimization Algorithm to Search Correct Material Properties: The value of the cost function abovementioned is dependent on the material parameters in FEM models. It is a nonlinear, multivariate optimization problem to find the correct constitutive parameters by minimizing the cost function ,29, espeThere are two essential difficulties  inherentOnce the constitutive parameters were found, a stress–strain (or stress–stretch ratio) relationship could be derived from the strain energy density functions. More details on the derivation can be found in the existing literature and are omitted here ,18,52. FThe framework of the FEMBUA was employed to determine individual-specific material properties of arterial tissues for mostly middle- or large-size arteries in vivo . To examThe human aorta contains a wide range of vascular course, including ascending thoracic aorta (AsA), aortic arch, descending thoracic aorta (DsA) and abdominal aorta (AA). Aortic aneurysm is a common pathological condition influencing the health state of the aorta. The stress–stretch ratio curves of healthy and aneurysmal aortic tissues listed in Based on the material curves in Among the listed in vivo studies, one study determined the material properties of both healthy and aneurysmal tissues to study the impact of pathological conditions on the material properties following the same method. This study showed that aneurysmal aortic tissues tend to have higher stiffness than non-aneurysmal aortic tissues . This coFewer studies were performed to identify the material properties of carotid and coronary arteries in vivo. Classically, mechanical experiments are conducted to quantify the mechanical properties using arterial tissues ex vivo . HoweverSince tissue samples are often not available for in vivo studies and the material properties of arterial tissues alter when taken out of living subjects, the image-based finite element modeling approach is more suitable for studies under in vivo conditions with potential clinical implementations ,23. PrioEven though in vivo and ex vivo methods follow different approaches in determining tissue properties, they are not exclusive to each other. Rather, they are complementary to each other. A hybrid approach that uses a finite element updating approach to match stress–strain data from biaxial/uniaxial experiments has been proposed to quantify the aortic aneurysmal tissue . To assess its accuracy and efficacy, comparison analysis between the novel FEMBUA and classical ex vivo experimental approaches were performed. Some representative ex vivo studies were selected, and the tissue stiffness values from these studies were compared to those from in vivo studies using the FEMBUA. For all types of arteries , the ranges of tissue stiffness were generally in the same magnitude for both methods. However, the dissected tissues from ex vivo studies were stiffer than tissue samples from in vivo studies by average. It should be noted that the limited number of ex vivo studies could influence the conclusions abovementioned, because the average tissue stiffness would change if a different set of ex vivo representative studies were chosen. Thus, the comparison was evaluated numerically, not statistically for all tissues, not for just healthy or diseased ones, in which case, the selected studies would have more influence. Nevertheless, these conclusions suggested that the FEMBUA is an accurate and effective approach for quantifying the material properties of arterial walls. However, more rigorous comparison analysis should be performed by conducting both methods on the same tissue samples as detailed in the following section. Several research groups investigated vessel material properties using both the in vivo FEMBUA method and ex vivo experiments on the same arterial tissue for validation purposes ,35,55. BReproducible, accurate determination of arterial tissue material properties is an important prerequisite for clinical applications. In a methodological study, Narayanan et al., demonstrated the reproducibility of the FEMBUA by repeating the approach for three patients to obtain their material properties. The results of material parameters from different runs were recovered with errors of 3.0 ± 4.7% . The robustness of the solution to the inverse problem remains to be an important issue. There are many uncertainties that would impact the results of mechanical property determination which include medical image resolution, on-site pressure measurement, etc. Narayanan et al., performed sensitivity analysis by applying random Gaussian noise to the original medical images. Their results showed that the errors for the material parameters were 1.3 ± 1.6% for the 5% noise addition. In addition to the noise inherent to the image-based geometry, Narayanan et al., also investigated the impact of such pressure perturbations on material property recovery. They claimed that such perturbation would result in controllable error in tissue stiffness estimation. More specifically, the relative error was equal to the relative error of the applied perturbation . There are some assumptions involved in FEM for in vivo indentation of the material properties of arterial walls, which would impact the results from the FEMBUA: (a) Axial stretch has considerable impact on the result of mechanical parameter values ,48. TherThe image-based FEMBUA has been proven to accurately and effectively determine the material properties of arterial walls in vivo. In addition, the tissue stiffness from this method was consistent with that from ex vivo experimental approaches. However, current studies mainly use image and pressure data at two cardiac phases . Imaging technologies with higher temporal resolution are desirable to obtain clinical images at more cardiac phases, so that more data points will be available to fit the complex nonlinear material models  in a least square sense. Thus, the image-based FEMBUA would be more robust and not sensitive to image noise or pressure measurement error. Biomechanical properties provide vast information regarding cardiovascular tissues in living individuals, which could guide us to a better understanding of arterial mechanics and physiology, as well as for the analysis of the mechanisms of vascular diseases. In vivo arterial tissue stiffness has already been employed in clinical settings as a risk factor for cardiovascular diseases, and has been proven to have clinical significance ,23. Sinc


The incidence rate of total joint replacement (TJR) continues to increase due to the aging population and the surgery that is very successful in providing pain relief to and improving function among patients with advanced knee or hip arthritis. Improving patient outcomes and patient satisfaction after TJR remain important goals. Wearable technologies provide a novel way to capture patient function and activity data and supplement clinical measures and patient-reported outcome measures in order to better understand patient outcomes after TJR.We examined the current literature to evaluate the potential role of wearable devices and compare them with existing methods for monitoring and improving patient rehabilitation and outcomes following TJR.We performed a literature search by using the research databases supported by the University of Massachusetts Chan Medical School’s Lamar Soutter Library, including PubMed and Scopus, supplemented with the Google Scholar search engine. A specific search strategy was used to identify articles discussing the use of wearable devices in measuring and affecting postoperative outcomes of patients who have undergone TJR. Selected papers were organized into a spreadsheet and categorized for our qualitative literature review to assess how wearable data correlated with clinical measures and patient-reported outcome measures.A total of 9 papers were selected. The literature showed the impact of wearable devices on evaluating and improving postoperative functional outcomes. Wearable-collected data could be used to predict postoperative clinical measures, such as range of motion and Timed Up and Go times. When predicting patient-reported outcomes, specifically Hip Disability and Osteoarthritis Outcome Scores/Knee Injury and Osteoarthritis Outcome Scores and Veterans RAND 12-Item Health Survey scores, strong associations were found between changes in sensor-collected data and changes in patient-reported outcomes over time. Further, the step counts of patients who received feedback from a wearable improved over time when compared to those of patients who did not receive feedback.These findings suggest that wearable technology has the potential to remotely measure and improve postoperative orthopedic patient outcomes. We anticipate that this review will facilitate further investigation into whether wearable devices are viable tools for guiding the clinical management of TJR rehabilitation. Total joint replacement (TJR) has proven to be highly effective in relieving joint pain and improving physical function for millions of patients with advanced knee or hip osteoarthritis and continues to be one of the most commonly performed surgical procedures in the United States -3. As thWearable technologies provide a novel way to capture patient function and activity data and supplement clinical measures and PRO measures (PROMs) to better understand patient recovery after TJR. Wearable technologies, in the context of health care, refer to devices that can record real-time data from an individual while worn. These devices include accelerometers, which capture the acceleration of a limb or the entire body; gyroscopes, which measure orientation and angular velocity; and inertial measurement units—a more sophisticated technology that combines an accelerometer, gyroscope, and magnetometer and is capable of reporting the movement, orientation, and position in space of a person or object . Many coTo promote wearable use as part of rehabilitation programs following TJR, their impact on postoperative patient outcomes, as well as their accuracy in measuring these outcomes, must be further investigated. This paper seeks to review the current landscape of orthopedic wearables literature and assess the effectiveness of available devices with respect to evaluating and improving postoperative outcomes.A literature search was conducted by using the research databases supported by the University of Massachusetts Chan Medical School’s Lamar Soutter Library, including PubMed and Scopus, supplemented with the Google Scholar search engine. Articles published in English from 2004 to 2021 were reviewed. The search terms used to identify these articles are defined in Term groupings and search termsWearable devices(“wearable”) AND (“devices” OR “technology”)Patient AND “outcomes”Rehabilitation“rehabilitation” OR “recovery”The inclusion criteria included English-language articles, research studies, and studies with wearable technology that focused on comparing wearable-collected data with clinical measures or PROMs or affecting patient outcomes. The exclusion criteria were articles focusing on wearable device design, study protocols, theoretical articles, books, or book chapters. Titles and abstracts of identified articles were screened to determine eligibility based on the inclusion and exclusion criteria. Since only a limited number of papers met the inclusion criteria, a full reading was conducted for all of the eligible papers.The information was tabulated via a standardized Excel (Microsoft Corporation) form that was developed for this review, which included the first author’s name, year of publication, name and type of the wearable device, location where the device was worn, number of patients in the study, outcome measures, and study findings . A narraThe standard postoperative TJR outcome measures in this literature review included (1) assessments typically conducted in clinical settings, such as range of motion (ROM) assessments and the TUG test, and (2) PROMs, such as joint-specific outcome measures (Hip Disability and Osteoarthritis Outcome Score/Knee Injury and Osteoarthritis Outcome Score [HOOS/KOOS]), global health measures , patient satisfaction, and activity adherence.A total of 9 articles that met the inclusion criteria were identified. The articles evaluated the mobility and activity data collected through the wearable devices and compared them with standard clinical outcome measures and PROMs.In evaluating ROM and TUG time, the wearables varied in accuracy. Kwasnicki et al  observedData from wearable devices may correlate with PROMs. Bendich et al  aimed toThe authors of 2 articles discussed the impact of the use of wearable devices on postoperative TJR patient outcomes. Specifically, the researchers investigated how the ability of devices to offer feedback on exercise and rehabilitation to patients may impact patient outcomes. Van der Walt et al  randomizPatients reported high satisfaction with and adherence for the use of wearable devices. A study by Chiang et al  found thSeveral devices were found to be generally accurate in counting steps. Battenberg et al  tested tPostoperative TJR recovery remains a black box to health care providers until patients report to a clinic or respond to a survey. With adequate implementation and the ability to collect data continuously, even from a remote setting, wearable devices can help health care providers to monitor progress consistently and detect early problems in rehabilitation . The litThere has also been some support in the literature for the use of monitoring insoles, particularly for the purpose of load and gait analysis. Although preliminary findings suggest that monitoring insoles have good accuracy in measuring foot load distribution and natural gait, the few studies that have been performed are limited by small sample sizes ,26. AddiIn addition to generating data that correlate with established outcomes, wearables can also be used to improve outcomes overall by more actively engaging patients in exercise and activity ,27. IndeAs orthopedic clinical research has progressed, more data sources have emerged from which to monitor and guide patient rehabilitation and care following TJR. Whereas most patient data previously originated from electronic health records, direct patient-generated data in the form of PROMs or outcomes tracked and collected by wearables aptly supplement clinically collected data. Particularly, the ability of wearables to generate objective, continuous data showing trends in patient progress is unique in comparison to PROMs, which provide subjective data from predetermined time points, and electronic health record data, which are only collected during patients’ point-of-care visits and require medical professionals’ involvement. Moreover, with the increased emphasis on telemedicine, particularly since the COVID-19 pandemic, the remote monitoring of patient recovery via wearables represents a potential new path toward collecting patient data and guiding clinical decision-making ,31. ThesThere are still challenges to the implementation of wearable technology. Technical support will be needed for device calibration and data collection. Some research teams have assisted in the use of wearables during appointments scheduled at patients’ homes , hospitaThis review discusses the current state of the literature regarding the effectiveness of wearable devices in measuring and improving TJR outcomes, as well as the future directions of wearable device use. Wearable technologies have great potential for assessing and enhancing patients’ postoperative physical function. Wearables can be effective, alternative tools for evaluating TJR outcomes, as early findings have shown correlations among wearable-recorded data, PROMs, and clinical outcomes. The implementation and standardization of wearables should be addressed in future research.


Mindfulness-based cognitive therapy and isometric exercise training (IET) interventions are relatively new approaches to maintain physical functioning, alleviate pain, prevent joint stiffness and muscular atrophy, and positively influence other postoperative care outcomes.The aim of this review was to identify the impacts of mindfulness-based interventions (MBIs) and IET and, more specifically, their combination, which have not previously been assessed to our knowledge.Studies were identified by searching the PubMed and Cochrane databases within the PRISMA  algorithm format and using relevant keyword combinations, which resulted in 39 studies meeting the inclusion criteria.In general, MBI was shown to positively impact both pain relief and physical functioning, while IET positively impacted physical functioning. Numerous other benefits, including improved quality of life and decreased postoperative opioid use, were also described from both interventions; however, further research is needed to confirm these findings as well as to determine other possible benefits. No studies were found that combined MBI and IET.Despite many positive results from each individual intervention, there is a lack of information about how the combination of MBI and IET might impact postoperative care. The combination of these two interventions might prove to be more effective than each individual intervention alone, and the findings from this review show that they could even be complementary. Going forward, research should be expanded to study the possible benefits of the combination of MBI and IET in postoperative care routines as well as other possible combinations. Postoperative care routines are particularly important in determining the long-term outcomes of many surgical procedures. Occupational therapy and physical therapy are examples of postoperative care with proven utmost importance not only in situations where the musculoskeletal system is the primary focus of the surgery but also in other surgeries on the breast, abdomen, genital, cardiovascular, and pulmonary systems, as well as other organs -3. NumerPatients naturally feel stressed before surgery and during recovery. MBCT is employed as a group-based intervention, combining mindfulness meditation trainings with cognitive behavioral therapy elements . AlthougIET interventions are used similarly to mindfulness-based interventions (MBIs) regarding pain relief, but may be more influential in postoperative physical functioning. IET is performed by increasing muscle tension while preventing joint motion, most often by providing unmoving resistance during an exercise . A meta-Since MBI is more centered around the mental aspects of postoperative recovery and IET around the physical aspects of postoperative recovery, it is hypothesized that the combination of these interventions may result in even more positive postoperative results in comparison to the results observed when used individually. While other postoperative interventions are also used (which are briefly mentioned in the Discussion section), we decided to focus solely on MBI and IET for simplicity, and as an overarching example of the importance of combining mental and physical interventions in postoperative settings. Future research should expand upon this review and include other intervention types in varying combinations compared with the individual physical and mental interventions.Thus, the aim of this systematic review was to examine the currently published medical literature on MBI and IET, and evaluate the impact of such interventions overall and specifically the overarching benefits of their inclusion in the postoperative care setting.This systematic review implemented an algorithmic approach to review all of the currently available English medical literature on MBI or isometric exercises in the setting of postoperative care using the PRISMA  principles . A comprWe finally included 39 full manuscripts that met our inclusion criteria. Many of the papers included in this aspect of the review cited two main benefits of MBI use: pain relief (as measured through pain medication use) and improvements in physical functioning. In comparison to other interventions such as “hypnotic suggestion” and “cognitive behavioral pain education,” MBI decreased pain medication desire and anxiety, and increased postoperative physical function in a randomized controlled trial on total joint arthroplasty with 258 patients . The stuOther studies showed less conclusive results regarding the influence of MBI on pain relief and physical functioning. One study reported no difference in opioid use but decreased postoperative pain 1 month after lumbar spine surgery in the MBI patient group , indicatBesides pain relief and physical function, numerous other benefits were discussed in introducing MBI in postoperative care routines. One study found that MBI effectively decreased depressive and sleep disorder symptoms both 1 month and 3 months post breast cancer surgery . SimilarTwo studies employed newer technological innovations to introduce MBI to the postoperative care routine. The first study employed a “self-care toolkit” that consisted of “guided audio mind-body” techniques, an acupressure wristband, and a journal . The resIET interventions were found to be utilized most commonly following cardiac and orthopedic surgeries. In fact, IET and its impact in the postoperative setting of any other surgical procedure were not discussed by any published article. Extending this type of intervention to other surgical procedures will be an important step in understanding the overall impact of IET on postoperative care in general. In the meantime, the benefits of IET will only be known for cardiac and orthopedic surgeries, which are discussed below.Numerous studies cited in this review demonstrated that IET aids in postoperative recovery from cardiac surgeries. Doppler ultrasound maturation, which is indicative of blood flow efficiency, is an especially important measurement taken after cardiac surgeries. An older study used Doppler measurements and showed that isometric exercise is well-tolerated by postoperative heart transplant patients . SeveralSimilar benefits were also found when applying IET in orthopedic postoperative care settings with different measures of their effects. Patients in the IET group that underwent surgery for nonarticular tibia fractures were found to have significantly higher amounts of mean bone-specific alkaline phosphatase (indicative of improved osteoblastic activity) and lower Hummer scale callus scores, which are both correlated with shortened healing time . SimilarThe specific patient populations and their prerequisites may also influence the ideal targeted intervention, which could impact their postoperative outcomes. Defining such a modality may require extensive preoperative evaluations of the target group and in-depth knowledge of the expected postoperative changes and recovery demands. For example, elderly patients may have increased difficulty in recovering from surgery and with overall pain management than other patients, and thus may benefit from targeted postoperative care. For this population, IET resulted in greater maximal lift weights and therefore more improved physical functioning post lower limb surgery . SimilarAlthough most reports of postoperative IET showed beneficial outcomes, one study did not report a strong positive effect. In this study, exercises specifically tailored for relaxation were not found to influence pain scores or shoulder function after arthroscopic rotator cuff repair . The onlIn addition to the results discussed above, there are also numerous clinical trials employing variations of MBI or IET during postoperative care that are currently undergoing patient recruitment and/or are in the follow-up stage. Twelve examples of currently ongoing clinical trials are described in Although there are numerous benefits to MBIs and IET in postoperative care routines, namely surrounding pain relief and physical functioning, we found that none of the studies combined the two techniques. This was a particularly interesting finding, especially given the wide range of possible benefits each patient can obtain from each individual modality, and the potential synergistic impact that patients could gain from the combination of these two techniques. For example, patients exposed to both interventions might demonstrate increased pain relief (as seen from the MBI results) and physical functioning (as seen from the MBI and IET results) as well as other postoperative outcomes in comparison to exposure to only one of the interventions. Although MBI and IET use in postoperative settings has begun only recently, it is important to understand the benefits of their combination going forward to fully maximize postoperative patient care. We believe that the combination of interventions mainly focused on the mind settings (MBI) and physical-based interventions, especially those that can be used in the immediate postoperative period even with different immobilization settings , could make an ideal combination in the postoperative setting. Further research is needed to support this hypothesis and studies going forward should examine this combination in a well-controlled setting.As touched upon briefly, any measure that can help lower pain scores, improve mobility, or help with other postoperative outcomes should be utilized. This is especially true for higher-risk surgeries in which patients may learn via an MBCT on how to prepare for surgery, be better able to tolerate the surgical procedure’s impact, and use IET to facilitate their recovery from the surgery. In particular, these interventions may also be important for cancer patients who are recovering from surgery, since this patient group has been shown to demonstrate lower mindfulness scores than average, although with extensive variability . Thus, cOther intervention types outside the scope of this review were also found in the literature search. These include “Healing Touch” , hypnosiAs technology continues to advance, it is also important for postoperative care interventions to keep up with new innovations. This was demonstrated in this review through studies that used virtual reality settings and mobile platforms to reach their participants. As technology will continue to advance in the coming years, further innovative approaches would need to be tested to find their true benefits in advancing the postsurgical care outcome. More patient populations can be reached using technological innovations, and this has become even more important during the COVID-19 pandemic as many patients were forced into home-based programs. As an example, the Perioperative Pain Self-Management (PePS) program was created to conduct cognitive behavioral therapy sessions over the phone with rural veterans who may not have had access to this type of care otherwise . SimilarIt is clear from the studies discussed in this review that there are numerous benefits to including an MBI or IET in postoperative care settings. These effects notably include pain relief and physical functioning, and may be influential in determining various other long-term outcomes. However, there were no studies found to date that combined MBI and IET. This was surprising since the combination of these two interventions might prove to be more effective than each individual intervention alone, and the findings from this review show that they could even be complementary . As previously noted, it is also important to tailor postoperative care to individual patients and some patients might benefit more from combining interventions. Going forward, research should be expanded to study the possible benefits of the combination of MBI and IET in postoperative care routines as well as other possible combinations.


Intraoperative radiation therapy is evolving towards new treatment regimens, including ultrahigh dose rates, while in-room imaging systems are increasingly being used for treatment planning and verification. Furthermore, the combination of multiple treatment modalities is being investigated and suggested in some studies, with the aim to improve clinical outcomes. This evolution calls for newly designed treatment planning systems in which several features shall be integrated. In this article, an attempt is made to identify emerging needs and foresee the possible evolution of treatment planning technology and strategies for intraoperative radiation therapy in the near future.As opposed to external beam radiation therapy (EBRT), treatment planning systems (TPS) dedicated to intraoperative radiation therapy (IORT) were not subject to radical modifications in the last two decades. However, new treatment regimens such as ultrahigh dose rates and combination with multiple treatment modalities, as well as the prospected availability of dedicated in-room imaging, call for important new features in the next generation of treatment planning systems in IORT. Dosimetric accuracy should be guaranteed by means of advanced dose calculation algorithms, capable of modelling complex scattering phenomena and accounting for the non-tissue equivalent materials used to shape and compensate electron beams. Kilovoltage X-ray based IORT also presents special needs, including the correct description of extremely steep dose gradients and the accurate simulation of applicators. TPSs dedicated to IORT should also allow real-time imaging to be used for treatment adaptation at the time of irradiation. Other features implemented in TPSs should include deformable registration and capability of radiobiological planning, especially if unconventional irradiation schemes are used. Finally, patient safety requires that the multiple features be integrated in a comprehensive system in order to facilitate control of the whole process. The last two decades have seen unparalleled development in treatment planning for external beam radiation therapy (EBRT) . EvolutiThe same cannot be said for treatment planning in intraoperative radiation therapy. Treatment planning solutions, in this case, are not characterized by diverse strategies nor are they implemented with the richness of options currently available in EBRT. The difficult modelling of the anatomical district to treat through proper imaging techniques—unlike EBRT, where pre-treatment accurate imaging solutions are available—seriously hinders the capacity of treatment planning systems to produce reliable, predictive and robust dose distributions. Beam shaping devices (applicators) and protective gear such as disk-shaped shields to use downstream the electron beam interfere with imaging devices and pose dosimetric issues due to their high-Z chemical composition .On the other hand, IORT is administered in one single fraction so no inter-fraction modifications occur, thus eliminating the need for inter-fraction treatment adaptation and simplifying the whole process. Intrafraction motion is also radically reduced compared to EBRT: another potential advantage over treatment planning systems designed for fractionated external irradiation.Treatment planning for kilovoltage X-ray based IORT  is relatThe time is probably ripe for a change. Availability of accurate dose calculation algorithms for clinical use, such as real-time Monte Carlo calculation ,5,6, theIn the following sections, after an analysis of currently available technology, an attempt will be made to focus on the needs and foresee the possible evolution of treatment planning systems and strategies dedicated to intraoperative radiation therapy in the near future.Dedicated IORT systems have seen a continuous technological evolution in recent years. However, there has been no dramatic change in the general scheme of operation of IORT equipment, and treatment planning systems could therefore be adapted accordingly.Nonetheless, dose calculation algorithms in current systems may lack the accuracy that characterizes analogous devices dedicated to EBRT. Monte Carlo dose calculation is currently implemented in treatment planning systems dedicated to electron-beam IORT ,5,6,9,10In-room imaging systems are not routinely used in intraoperative radiation therapy. Several studies can be found in the literature that propose imaging tools aimed at capturing the real-time anatomical situation and therefore adapt treatment planning online , but nonAll these aspects  may need a sudden change, for the reasons outlined in the following paragraphs.Matching the dosimetric accuracy of EBRT is probably the most compelling need in modern IORT. Inaccuracy due to the irregular anatomical environment, dynamically evolving e.g., due to fluid filling of cavities, and complex scattering phenomena demand fine modelling, accuracy of dose calculation and fast adaptation . Dose diThe availability of in-vivo dosimetry in IORT  will proThese challenging points are even exacerbated in case of dose escalation protocols and novel irradiation paradigms, e.g., flash therapy ,19,20. SIORT can be combined to external beam photon irradiation, which might be administered at different time points. In such cases, it is important to have a tool capable of dose accumulation to calculate and visualize the dose distribution emerging from the combination of treatments. This is probably one of the key points in an ideal treatment planning system dedicated to IORT. The possible combination of IORT and EBRT or even brachytherapy  in new tBeam modifiers and shields have been used since the very first experiences in IORT. Nonetheless, the prospected use of 3-D printed beam modifiers and compensators  offers tFrom the technological standpoint, a most important development would be the availability of devices for in-room real-time imaging. This should be paralleled by appropriate capabilities of the treatment planning system: seamless import of 3D datasets , calculX-ray based IORT shares some of the above but has special needs. The extremely steep dose gradient typical of kilovoltage systems  compared to electron beam IORT requires a very high spatial accuracy. Furthermore, accounting for the actual tissue composition and the material of the applicators normally used with such sources requires high dosimetric accuracy. In contrast, treatment planning systems provided by vendors typically calculate dose distributions in water, without considering any of the heterogeneities present. Deviations from intended dose prescription have been described, up to 34% in the case of breast irradiation and larger than 300% in bone ,32. TherDevelopments will probably come both from the industry and academic research. However, the wide adoption of advanced treatment planning tools would only be possible if manufacturers chose to implement the most recent developments in commercially available systems. Transfer of currently available technology used for EBRT should be a seamless way to offer advanced TPS capacity in IORT.Implementation of pure Monte Carlo dose calculation algorithms would require higher computational capacity compared to current systems. The industry should be aware that this is a critical aspect for treatment planning and consequently be prepared to offer adequate tools. Stand-alone workstations may be replaced by cloud-based systems, provided that stable network connection is guaranteed where needed.A most important strategy to raise the quality level of IORT would be the adoption of imaging devices in the operating room, dedicated to monitoring the anatomical situation of the region to irradiate and to acquiring images and data for real-time adaptation of the treatment plan. This includes portable imaging devices as well as dedicated fixed systems ,33. ConeInteroperability between existing system is necessary, for example to allow dose accumulation estimates in case of multiple treatments that may include EBRT. This task necessarily involves deformable registration, for example to map the dose distribution administered in IORT to the anatomy at the time of a subsequent external beam treatment. Deformable image registration (DIR) shall also be used when pre-surgical imaging is adapted to the situation in the operating room. Using DIR is a complex task that requires skilled operators and robust algorithms: for example, balancing the amount of deformation with the necessary regularization of the underlying spatial transformation is a critical aspect that needs both experience and reliable algorithms to prevent errors. Special attention should be put by manufacturers to the implementation of DIR: solutions already available for EBRT treatment planning systems might be inadequate for the special needs of IORT.Finally, it is desirable that the foreseen solutions would be implemented into a fully integrated TPS with advanced image processing tools, including reliable DIR. Integration guarantees that the workflow in the operating room does not suffer from weak points that might represent increased factors of risk. The safe use of radiation sources for medical applications requires that every step of the process is clearly defined and effectively controlled: dealing with multiple, non-integrated systems is feasible and sometimes necessary, but is not an optimal strategy as far as patient safety is concerned.New treatment regimens such as ultrahigh dose rates and combination with multiple treatment modalities, as well as the increasing availability of dedicated in-room imaging systems, are the factors that will probably shape the next generation of treatment planning systems in IORT. Interoperability between systems is also a key factor that should be guaranteed in newly developed TPSs. Features should include reliable DIR and capability of radiobiological planning, especially if unconventional irradiation schemes are used.The need for dosimetric accuracy should encourage the implementation of fast yet accurate Monte Carlo dose calculation algorithms, fast enough to be routinely used in the clinical setting.Finally, patient safety requires that the multiple features be integrated in a comprehensive system in order to facilitate control of the process.


Adrenal incidentalomas are incidentally discovered adrenal masses greater than one centimeter in diameter. An association between insulin resistance and adrenal incidentalomas has been established. However, the pathophysiological link between these two conditions remains incompletely characterized. This review examines the literature on the interrelationship between insulin resistance and adrenal masses, their subtypes, and related pathophysiology. Some studies show that functional and non-functional adrenal masses elicit systemic insulin resistance, whereas others conclude the inverse. Insulin resistance, hyperinsulinemia, and the anabolic effects on adrenal gland tissue, which have insulin and insulin-like growth factor-1 receptors, offer possible pathophysiological links. Conversely, autonomous adrenal cortisol secretion generates visceral fat accumulation and insulin resistance. Further investigation into the mechanisms and timing of these two pathologies as they relate to one another is needed and could be valuable in the prevention, detection, and treatment of both conditions. An adrenal incidentaloma (AI) is an adrenal mass found incidentally using imaging, independent of an endocrinological investigation  1]. Tec. Tec1]. Some studies suggest that adrenal tumors elicit systemic insulin resistance; whereas others indicate the opposite pathway—that autonomous adrenal cortisol secretion may generate insulin resistance and obesity. It is plausible that both are true in a reciprocal triad . This reThere are key overlapping downstream effects of cortisol secreting adrenal incidentalomas that are hypothesized to underlie the reciprocal relationship between insulin resistance and adrenal incidentaloma. Downstream effects of benign functioning adrenal masses include subclinical hypercortisolism , CushingMethods: Initially, major medical databases including PUBMED and MEDLINE were queried using the search terms adrenal incidentaloma and insulin resistance; the search was limited to developments from the past five to ten years. Subsequent in-depth, searches as topics and relationships were uncovered included topics specific to the pathology, radiology, etiology, and symptomatology of adrenal incidentalomas and insulin resistance as well as associated key pathophysiological interactions. Original research articles published radiological and clinical research studies, and literature reviews were all included in the current study. Key knowledge gaps in the literature were identified and evidence-based recommendations were formulated based on the collective expertise of the authorship and medical literature. Original figures were created using the Biorender platform.Adrenal incidentalomas (AIs) are masses of the adrenal gland measuring greater than one cm in diameter found unexpectedly on imaging performed for indications other than evaluation of adrenal pathology . The detAlthough some studies have reported AIs to occur more frequently in female patients ,40,41, dBy definition, incidentalomas are discovered in asymptomatic patients or patients being evaluated for an unrelated condition. Potential etiologies of AI include but are not limited to adrenocortical adenoma, adrenocortical carcinoma, pheochromocytoma, and metastatic cancer . Most AIACS typically presents as subclinical sequelae of hypercortisolism  which maThe clinical signs and symptoms of functional adrenal mass differ depending on the hormone being secreted in excess . SubclinConceptualizing the relationship between adrenal incidentalomas and insulin resistance requires an appreciation of the role of insulin. Insulin is an endogenous anabolic peptide hormone secreted by pancreatic beta-cells and does not require a transport protein to travel throughout the body, where it can act on various organs through the insulin receptor . The insInsulin resistance is defined as a decreased response to a given amount of insulin and is a central contributing factor to the pathogenesis of type 2 diabetes mellitus (T2DM) . The impAlthough the exact mechanism of insulin resistance (IR) is not completely understood, adipose tissue is known to play a central role in the desensitization of this critical hormone . AdiposeOne study showed that mRNA expression levels of TNF-α in adipose tissue in obese individuals are strongly implicated in the pathogenesis of insulin resistance through impairment of insulin signaling in hepatocytes and adipose tissue . In muriAs a result of the cell’s inability to respond to normal insulin levels in the blood (insulin resistance), the human body raises the level of insulin in the blood to compensate for the insensitivity. Hyperinsulinemia is a term for chronically high levels of circulating insulin, which is typically linked to obesity and T2DM. Because insulin is recognized for its growth capabilities, it’s possible that a state of excess insulin, such as hyperinsulinemia caused by insulin resistance, could result in the birthing of diverse masses throughout the body ,82,83,84Insulin plays a major role in the activation of different receptors in the adrenal gland that lead to growth and development ,86. AddiAnother plausible mechanism that may lead to an adrenal incidentaloma is the upregulation of hepatic growth hormone receptors by hyperinsulinemia. Leung et al.  elucidatCell growth and mitogenic effects that may lead to cancer have also been shown to come from insulin receptors (IRs) . PreviouInsulin’s effect on the liver’s production of insulin-like growth factor binding proteins (IGFBPs) is another pathway that has been reported as a route for cellular proliferation. Brismar et al.  studied Insulin also interacts with hyaluronan, which leads to tumor progression. Hyaluronan is an essential polysaccharide component of the extracellular matrix. It performs essential functions that help organize tissue architecture and additionally regulates cellular proliferation and migration. It does so by interacting with cell-surface receptors and by adhering to other molecules . TwarockCortisol is normally secreted in a diurnal manner  and is uCortisol stimulates hepatic gluconeogenesis through enzyme expression . Under nGlucocorticoid action is known to involve pre-receptor metabolism by enzymes such as 11β-Hydroxysteroid Dehydrogenase Type 1 (11β-HSD-1) that converts inactive glucocorticoids to their active form. Mice overexpressing 11β-HSD-1 in adipose tissue were shown to be obese and insulin-resistant . AsensioIn addition to stimulating its own production and activation, cortisol release from the adrenal glands acts directly on the pancreas to decrease the release of insulin from beta-cells while simultaneously acting on α-cells to stimulate the release of glucagon . GlucagoThe indirect effects of hypercortisolism and its action on insulin resistance involve hyperlipidemia-induced cell stress . OxidatiGlucocorticoid-induced hyperlipidemia and intracellular oxidative stress are potentially augmented by a subsequent decrease in plasma levels of adiponectin. Adiponectin is an adipokine that has been proven to influence metabolism and inflammation . AdiponeGlucocorticoid release from the adrenal cortex is seen in response to pathological processes that increase stress on the body, including malnutrition, infection, depression, and anxiety . IncreasFurther research is needed to elucidate the mechanism of action in both pathways. A significant majority of substantive original research took place in the 1980s and 1990s, with few original studies performed in the last 10 years despite the parallel rise in prevalence of both AI and IR. Importantly, the timing and onset of adrenal incidentaloma by subtype compared to the history of IR and IR onset would be valuable to better characterize this dynamic, multifaceted interrelationship. Investigation of the specific insulin receptors on adrenal cortical tissue and receptor variation in AI is needed, as are further studies into the mechanisms of excess glucocorticoid-mediated destruction or dysregulation of pancreatic beta-cells. These mechanisms may play a critical role in identifying and producing a correlative analysis of AI-predisposing and IR risk factors. Not all patients with IR develop AI, but nearly all patients with AI develop IR. Therefore, a Mendelian randomization process may be useful to investigate causative links between the pathologies.There is significant clinical and basic biochemical evidence suggesting that AI can induce IR and that IR can promote AI. The direct and indirect effects of ACS on systemic insulin resistance are well characterized, including direct and indirect effects of cortisol on body tissues and pancreatic beta-cells. Cortisol-secreting adrenal masses may appropriately be included in differential diagnoses when considering clinical insulin resistance. The pathophysiological pathway of insulin resistance causing adrenal mass is less well characterized, although mechanisms for this pathway have been proposed, including the stimulation of IGF-1 and IGF-2 receptors. Furthermore, while the mechanisms of IR leading to increased mitotic activity and tumor proliferation are sufficiently established in the literature, causation has not been proven. Nevertheless, despite gaps in the underlying mechanism, there is sufficient data such that clinical insulin resistance and glucose monitoring should be considered when an incidental adrenal mass is discovered. After review of the literature, there is no currently accepted single thread to tie AI and IR together. The relationship can be characterized as reciprocal and self-enhancing in its progression with risk for severe disease if left to its natural course. Further investigation into the mechanisms and timing of the interrelationship is needed and could be valuable in the prevention, detection, and treatment of both conditions.


Epilepsy is a common disabling chronic neurological disorder characterized by an enduring propensity for the generation of seizures that result from abnormal hypersynchronous firing of neurons in the brain. Over 20–30% of epilepsy patients fail to achieve seizure control or soon become resistant to currently available therapies. Prolonged seizures or uncontrolled chronic seizures would give rise to neuronal damage or death, astrocyte activation, reactive oxygen species production, and mitochondrial dysfunction. Stem cell therapy is potentially a promising novel therapeutic strategy for epilepsy. The regenerative properties of stem cell-based treatment provide an attractive approach for long-term seizure control, particularly in drug-resistant epilepsy. Embryonic stem cells (ESCs), mesenchymal stem cells (MSCs), neural stem cells (NSCs), induced pluripotent stem cells (iPSCs), and adipose-derived regenerative cells (ADRCs) are capable of differentiating into specialized cell types has been applied for epilepsy treatment in preclinical animal research and clinical trials. In this review, we focused on the advances in stem cell therapy for epilepsies. The goals of stem cell transplantation, its mechanisms underlying graft effects, the types of grafts, and their therapeutic effects were discussed. The cell and animal models used for investigating stem cell technology in epilepsy treatment were summarized. Epilepsy is a spectrum of heterogenous chronic brain disorders characterized by an enduring propensity for the generation of seizures which are the recurrent abnormal and hypersynchronous firing of neurons from dysfunctional brain circuits. Epilepsy remains one of the most prevalent neurological conditions affecting approximately 50–60 million people worldwide WHO, . EpilepsStem cells are “undifferentiated” cells that have not yet engaged in a developmental path to form a specific cell type or tissue. These cells have the potential to be differentiated into a variety of specialized post-mitotic cell lineages , glial-derived neurotrophic factor (GDNF), insulin-like growth factor-1 (IGF-1) and microRNA to support neuron survival, neurogenesis and maintain normal neuronal function  but also involves glia such as astrocytes and microglia. Various sources and many types of cells have been tested as a novel treatment in epilepsy to explore the therapeutic potency and safety of stem cell therapy, particularly for drug-resistant epilepsy.Embryonic stem cells are pluripotent that can be differentiated into almost any cell lineage. Cortical inhibitory interneurons mainly originate from the embryonic medial and caudal ganglionic eminences in the forebrain during development  which mainly involves the hippocampus is often medically refractory. Animal models mimic mesial temporal lobe epilepsy including kainic acid and pilocarpine rodent models are commonly used in chronic epilepsy models for stem cell research  and the Ministry of Science and Technology, Taiwan .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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.