1
|
Steen-Olsen EB, Pappot H, Hjerming M, Hanghoej S, Holländer-Mieritz C. Monitoring Adolescent and Young Adult Patients With Cancer via a Smart T-Shirt: Prospective, Single-Cohort, Mixed Methods Feasibility Study (OncoSmartShirt Study). JMIR Mhealth Uhealth 2024; 12:e50620. [PMID: 38717366 PMCID: PMC11084117 DOI: 10.2196/50620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 01/25/2024] [Accepted: 02/01/2024] [Indexed: 05/12/2024] Open
Abstract
Background Wearables that measure vital parameters can be potential tools for monitoring patients at home during cancer treatment. One type of wearable is a smart T-shirt with embedded sensors. Initially, smart T-shirts were designed to aid athletes in their performance analyses. Recently however, researchers have been investigating the use of smart T-shirts as supportive tools in health care. In general, the knowledge on the use of wearables for symptom monitoring during cancer treatment is limited, and consensus and awareness about compliance or adherence are lacking. objectives The aim of this study was to evaluate adherence to and experiences with using a smart T-shirt for the home monitoring of biometric sensor data among adolescent and young adult patients undergoing cancer treatment during a 2-week period. Methods This study was a prospective, single-cohort, mixed methods feasibility study. The inclusion criteria were patients aged 18 to 39 years and those who were receiving treatment at Copenhagen University Hospital - Rigshospitalet, Denmark. Consenting patients were asked to wear the Chronolife smart T-shirt for a period of 2 weeks. The smart T-shirt had multiple sensors and electrodes, which engendered the following six measurements: electrocardiogram (ECG) measurements, thoracic respiration, abdominal respiration, thoracic impedance, physical activity (steps), and skin temperature. The primary end point was adherence, which was defined as a wear time of >8 hours per day. The patient experience was investigated via individual, semistructured telephone interviews and a paper questionnaire. Results A total of 10 patients were included. The number of days with wear times of >8 hours during the study period (14 d) varied from 0 to 6 (mean 2 d). Further, 3 patients had a mean wear time of >8 hours during each of their days with data registration. The number of days with any data registration ranged from 0 to 10 (mean 6.4 d). The thematic analysis of interviews pointed to the following three main themes: (1) the smart T-shirt is cool but does not fit patients with cancer, (2) the technology limits the use of the smart T-shirt, and (3) the monitoring of data increases the feeling of safety. Results from the questionnaire showed that the patients generally had confidence in the device. Conclusions Although the primary end point was not reached, the patients' experiences with using the smart T-shirt resulted in the knowledge that patients acknowledged the need for new technologies that improve supportive cancer care. The patients were positive when asked to wear the smart T-shirt. However, technical and practical challenges in using the device resulted in low adherence. Although wearables might have potential for home monitoring, the present technology is immature for clinical use.
Collapse
Affiliation(s)
- Emma Balch Steen-Olsen
- Department of Oncology, Centre for Cancer and Organ Diseases, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Helle Pappot
- Department of Oncology, Centre for Cancer and Organ Diseases, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Maiken Hjerming
- Department of Oncology, Centre for Cancer and Organ Diseases, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Signe Hanghoej
- Department of Oncology, Centre for Cancer and Organ Diseases, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Cecilie Holländer-Mieritz
- Department of Oncology, Centre for Cancer and Organ Diseases, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
- Department of Oncology, Zealand University Hospital, Naestved, Denmark
| |
Collapse
|
2
|
Pappot H, Steen-Olsen EB, Holländer-Mieritz C. Experiences with Wearable Sensors in Oncology during Treatment: Lessons Learned from Feasibility Research Projects in Denmark. Diagnostics (Basel) 2024; 14:405. [PMID: 38396444 PMCID: PMC10887889 DOI: 10.3390/diagnostics14040405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 02/02/2024] [Accepted: 02/08/2024] [Indexed: 02/25/2024] Open
Abstract
BACKGROUND The fraction of elderly people in the population is growing, the incidence of some cancers is increasing, and the number of available cancer treatments is evolving, causing a challenge to healthcare systems. New healthcare tools are needed, and wearable sensors could partly be potential solutions. The aim of this case report is to describe the Danish research experience with wearable sensors in oncology reporting from three oncological wearable research projects. CASE STUDIES Three planned case studies investigating the feasibility of different wearable sensor solutions during cancer treatment are presented, focusing on study design, population, device, aim, and planned outcomes. Further, two actual case studies performed are reported, focusing on patients included, data collected, results achieved, further activities planned, and strengths and limitations. RESULTS Only two of the three planned studies were performed. In general, patients found the technical issues of wearable sensors too challenging to deal with during cancer treatment. However, at the same time it was demonstrated that a large amount of data could be collected if the framework worked efficiently. CONCLUSION Wearable sensors have the potential to help solve challenges in clinical oncology, but for successful research projects and implementation, a setup with minimal effort on the part of patients is requested.
Collapse
Affiliation(s)
- Helle Pappot
- Department of Oncology, Centre for Cancer and Organ Diseases, Copenhagen University Hospital, Rigshospitalet, 2100 Copenhagen, Denmark (C.H.-M.)
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, 2100 Copenhagen, Denmark
| | - Emma Balch Steen-Olsen
- Department of Oncology, Centre for Cancer and Organ Diseases, Copenhagen University Hospital, Rigshospitalet, 2100 Copenhagen, Denmark (C.H.-M.)
| | - Cecilie Holländer-Mieritz
- Department of Oncology, Centre for Cancer and Organ Diseases, Copenhagen University Hospital, Rigshospitalet, 2100 Copenhagen, Denmark (C.H.-M.)
- Department of Oncology, Zealand University Hospital, 4700 Naestved, Denmark
| |
Collapse
|
3
|
Izmailova ES, Wagner JA, Bakker JP, Kilian R, Ellis R, Ohri N. A proposed multi-domain, digital model for capturing functional status and health-related quality of life in oncology. Clin Transl Sci 2024; 17:e13712. [PMID: 38266055 PMCID: PMC10774540 DOI: 10.1111/cts.13712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 11/22/2023] [Accepted: 12/07/2023] [Indexed: 01/26/2024] Open
Abstract
Whereas traditional oncology clinical trial endpoints remain key for assessing novel treatments, capturing patients' functional status is increasingly recognized as an important aspect for supporting clinical decisions and assessing outcomes in clinical trials. Existing functional status assessments suffer from various limitations, some of which may be addressed by adopting digital health technologies (DHTs) as a means of collecting both objective and self-reported outcomes. In this mini-review, we propose a device-agnostic multi-domain model for oncology capturing functional status, which includes physical activity data, vital signs, sleep variables, and measures related to health-related quality of life enabled by connected digital tools. By using DHTs for all aspects of data collection, our proposed model allows for high-resolution measurement of objective data as patients navigate their daily lives outside of the hospital setting. This is complemented by electronic questionnaires administered at intervals appropriate for each instrument. Preliminary testing and practical considerations to address before adoption are also discussed. Finally, we highlight multi-institutional pre-competitive collaborations as a means of successfully transitioning the proposed digitally enabled data collection model from feasibility studies to interventional trials and care management.
Collapse
Affiliation(s)
| | | | - Jessie P. Bakker
- Departments of Medicine and Neurology, Brigham and Women's HospitalBostonMassachusettsUSA
- Division of Sleep Medicine, Harvard Medical SchoolBostonMassachusettsUSA
| | - Rachel Kilian
- Koneksa HealthNew YorkNew YorkUSA
- SSI StrategyNew YorkNew YorkUSA
| | | | - Nitin Ohri
- Montefiore Medical Center, Albert Einstein College of MedicineBronxNew YorkUSA
| |
Collapse
|
4
|
Schuler T, King C, Matsveru T, Back M, Clark K, Chin D, Lilian R, Gallego B, Coiera E, Currow DC. Wearable-Triggered Ecological Momentary Assessments Are Feasible in People With Advanced Cancer and Their Family Caregivers: Feasibility Study from an Outpatient Palliative Care Clinic at a Cancer Center. J Palliat Med 2023. [PMID: 37134212 DOI: 10.1089/jpm.2022.0535] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/05/2023] Open
Abstract
Background: Emerging digital health approaches could play a role in better personalized palliative care. Aim: We conducted a feasibility study testing wearable sensor (WS)-triggered ecological momentary assessments (EMAs) and electronic patient-reported outcomes in community palliative care with patient-caregiver dyads. Design: All wore consumer-grade WS for five weeks. Sensor-detected "stress" (heart rate variability algorithm) that passed individualized thresholds triggered a short smartphone survey. Daily sleep surveys, weekly symptom surveys (Integrated Palliative care Outcome Scale), and a poststudy experience survey were conducted. Setting/Participants: Fifteen dyads (n = 30) were recruited from an outpatient palliative care clinic for people with cancer. Results: Daytime sensor wear-time had 73% adherence. Participants perceived value in this support. Quantity and severity of "stress" events were higher in patients. Sleep disturbance was similar but for different reasons: patients (physical symptoms) and caregivers (worrying about the patient). Conclusions: EMAs are feasible and valued in community palliative care.
Collapse
Affiliation(s)
- Thilo Schuler
- Department of Radiation Oncology, Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, New South Wales, Australia
- Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney, New South Wales, Australia
| | - Claire King
- Department of Radiation Oncology, Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, New South Wales, Australia
| | - Teresia Matsveru
- NSLHD Supportive and Palliative Care Network, Royal North Shore Hospital, Sydney, New South Wales, Australia
| | - Michael Back
- Department of Radiation Oncology, Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, New South Wales, Australia
- Northern Clinical School, University of Sydney, Sydney, New South Wales, Australia
| | - Katherine Clark
- NSLHD Supportive and Palliative Care Network, Royal North Shore Hospital, Sydney, New South Wales, Australia
- Northern Clinical School, University of Sydney, Sydney, New South Wales, Australia
| | - Dylan Chin
- Department of Radiation Oncology, Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, New South Wales, Australia
| | - Ruth Lilian
- Sydney Partnership for Health, Education, Research and Enterprise, Sydney, New South Wales, Australia
| | - Blanca Gallego
- Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney, New South Wales, Australia
- Centre for Big Data Research in Health, University of New South Wales, Sydney, New South Wales, Australia
| | - Enrico Coiera
- Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney, New South Wales, Australia
| | - David C Currow
- Faculty of Science, Medicine and Health, University of Wollongong, Wollongong, New South Wales, Australia
| |
Collapse
|
5
|
Wood WA, Bailey C, Castrogivanni B, Mehedint D, Bryant AL, Lavin K, Tan X, Richardson J, Qian Y, Tan KR, Kent EE. Piloting HealthScore: Feasibility and acceptability of a clinically integrated health coaching program for people living with cancer. Cancer Med 2023; 12:8804-8814. [PMID: 36647557 PMCID: PMC10134320 DOI: 10.1002/cam4.5625] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Revised: 12/13/2022] [Accepted: 01/03/2023] [Indexed: 01/18/2023] Open
Abstract
BACKGROUND Cancer supportive care interventions often have limited generalizability, goal misalignment, and high costs. We developed and piloted a health coaching intervention, UNC HealthScore, in patients undergoing cancer treatment (ClinicalTrials.gov identifier NCT04923997). We present feasibility, acceptability, and preliminary outcome data. METHODS HealthScore is a six-month, theory-based, multicomponent intervention delivered through participant-driven coaching sessions. For the pilot study, participants were provided a Fitbit, responded to weekly symptom and physical function digital surveys, and met with a health coach weekly to develop and monitor goals. Coaching notes were discussed in weekly interdisciplinary team meetings and provided back to the treating oncology team. Symptom alerts were monitored and triaged through a study resource nurse to relevant supportive care services. Feasibility was determined based on intervention enrollment and completion. Acceptability was based on satisfaction with coaching and Fitbit-wearing and was informed by semistructured exit interviews. Outcomes evaluated for signs of improvement included several PROMIS (Patient-Reported Outcomes Measurement Information System) measures, including the primary intervention target, physical function. RESULTS From May 2020 to March 2022, 50 participants completed the single-arm pilot. Feasibility was high: 66% enrolled and 71% completed the full intervention. Participants reported an average of 4.8 and 4.7 (out of 5) on the acceptability of coaching calls and using the Fitbit, respectively. Physical function scores rose 3.1 points (SE = 1.1) from baseline to 3 months, and 4.3 (SE = 1.0) from baseline to 6 months, above established minimal clinically important difference (MCID). Improvements above MCID were also evident in anxiety and depression, and smaller improvements were demonstrated for emotional support, social isolation, cognitive function, symptom burden, and self-efficacy. DISCUSSION HealthScore shows feasibility, acceptability, and promising preliminary outcomes. Randomized studies are underway to determine the efficacy of preserving physical function in patients with advanced cancer.
Collapse
Affiliation(s)
- William A. Wood
- Lineberger Comprehensive Cancer CenterUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
- Department of Medicine, School of MedicineUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
| | - Carly Bailey
- Lineberger Comprehensive Cancer CenterUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
| | - Brianna Castrogivanni
- Lineberger Comprehensive Cancer CenterUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
| | - Diana Mehedint
- Department of MedicineDuke University School of MedicineDurhamNorth CarolinaUSA
| | - Ashley Leak Bryant
- Lineberger Comprehensive Cancer CenterUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
- School of NursingUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
| | - Kyle Lavin
- Lineberger Comprehensive Cancer CenterUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
- Department of Psychiatry, School of MedicineUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
| | - Xianming Tan
- Lineberger Comprehensive Cancer CenterUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
- Department of Biostatistics, Gillings School of Global Public HealthUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
| | - Jaime Richardson
- Lineberger Comprehensive Cancer CenterUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
| | - Yiqing Qian
- Department of Health Behavior, Gillings School of Global Public HealthUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
| | - Kelly R. Tan
- Lineberger Comprehensive Cancer CenterUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
| | - Erin E. Kent
- Lineberger Comprehensive Cancer CenterUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
- Department of Health Policy and Management, Gillings School of Global Public HealthUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
| |
Collapse
|
6
|
Izmailova ES, Maguire RP, McCarthy TJ, Müller MLTM, Murphy P, Stephenson D. Empowering drug development: Leveraging insights from imaging technologies to enable the advancement of digital health technologies. Clin Transl Sci 2023; 16:383-397. [PMID: 36382716 PMCID: PMC10014695 DOI: 10.1111/cts.13461] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 09/27/2022] [Accepted: 11/03/2022] [Indexed: 11/17/2022] Open
Abstract
The US Food and Drug Administration (FDA) has publicly recognized the importance of improving drug development efficiency, deeming translational biomarkers a top priority. The use of imaging biomarkers has been associated with increased rates of drug approvals. An appropriate level of validation provides a pragmatic way to choose and implement these biomarkers. Standardizing imaging modality selection, data acquisition protocols, and image analysis (in ways that are agnostic to equipment and algorithms) have been key to imaging biomarker deployment. The best known examples come from studies done via precompetitive collaboration efforts, which enable input from multiple stakeholders and data sharing. Digital health technologies (DHTs) provide an opportunity to measure meaningful aspects of patient health, including patient function, for extended periods of time outside of the hospital walls, with objective, sensor-based measures. We identified the areas where learnings from the imaging biomarker field can accelerate the adoption and widespread use of DHTs to develop novel treatments. As with imaging, technical validation parameters and performance acceptance thresholds need to be established. Approaches amenable to multiple hardware options and data processing algorithms can be enabled by sharing DHT data and by cross-validating algorithms. Data standardization and creation of shared databases will be vital. Pre-competitive consortia (public-private partnerships and professional societies that bring together all stakeholders, including patient organizations, industry, academic experts, and regulators) will advance the regulatory maturity of DHTs in clinical trials.
Collapse
|
7
|
Feasibility of Using Wearables for Home Monitoring during Radiotherapy for Head and Neck Cancer-Results from the OncoWatch 1.0 Study. Cancers (Basel) 2023; 15:cancers15020422. [PMID: 36672370 PMCID: PMC9857313 DOI: 10.3390/cancers15020422] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 01/02/2023] [Accepted: 01/04/2023] [Indexed: 01/11/2023] Open
Abstract
Background: Consumer wearables allow objective health data monitoring, e.g., of physical activity and heart rate, which might change over a cancer treatment course. Patients with head and neck cancer (HNC) receiving radiotherapy (RT) with curative intent typically experience side effects such as pain, decreased appetite, and dehydration, which may lead to hospitalizations. Therefore, health data monitoring could be important to understand a patient’s condition outside the hospital. The OncoWatch 1.0 study investigated the feasibility of using smartwatches for patients with HNC receiving RT. Methods: This study was a prospective, single-cohort feasibility study. The inclusion criteria were patients ≥ 18 years of age who planned to receive curatively intended radiotherapy for HNC. Consenting patients were asked to wear a smartwatch during RT and until two weeks after the end of RT. The primary endpoint was adherence. The secondary endpoints were data acquisition and variations in heart rate and physical activity. Results: Ten patients were included, with a median age of 62 years and eight males. The adherence rate for wearing the watch >12 h/d over the study period was 31%. The data acquisition rate was 61%. Conclusions: Although the primary endpoint was not reached, new knowledge has been established, including the secure data setup and key points that need to be addressed in future studies.
Collapse
|
8
|
Wood WA, Dilip D, Derkach A, Grover NS, Elemento O, Levine R, Thanarajasingam G, Batsis JA, Bailey C, Kannappan A, Devine SM, Artz AS, Ligibel JA, Basch E, Kent E, Glass J. Wearable sensor-based performance status assessment in cancer: A pilot multicenter study from the Alliance for Clinical Trials in Oncology (A19_Pilot2). PLOS DIGITAL HEALTH 2023; 2:e0000178. [PMID: 36812616 PMCID: PMC9931326 DOI: 10.1371/journal.pdig.0000178] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Accepted: 12/06/2022] [Indexed: 01/27/2023]
Abstract
Clinical performance status is designed to be a measure of overall health, reflecting a patient's physiological reserve and ability to tolerate various forms of therapy. Currently, it is measured by a combination of subjective clinician assessment and patient-reported exercise tolerance in the context of daily living activities. In this study, we assess the feasibility of combining objective data sources and patient-generated health data (PGHD) to improve the accuracy of performance status assessment during routine cancer care. Patients undergoing routine chemotherapy for solid tumors, routine chemotherapy for hematologic malignancies, or hematopoietic stem cell transplant (HCT) at one of four sites in a cancer clinical trials cooperative group were consented to a six-week prospective observational clinical trial (NCT02786628). Baseline data acquisition included cardiopulmonary exercise testing (CPET) and a six-minute walk test (6MWT). Weekly PGHD included patient-reported physical function and symptom burden. Continuous data capture included use of a Fitbit Charge HR (sensor). Baseline CPET and 6MWT could only be obtained in 68% of study patients, suggesting low feasibility during routine cancer treatment. In contrast, 84% of patients had usable fitness tracker data, 93% completed baseline patient-reported surveys, and overall, 73% of patients had overlapping sensor and survey data that could be used for modeling. A linear model with repeated measures was constructed to predict the patient-reported physical function. Sensor-derived daily activity, sensor-derived median heart rate, and patient-reported symptom burden emerged as strong predictors of physical function (marginal R2 0.429-0.433, conditional R2 0.816-0.822). Trial Registration: Clinicaltrials.gov Id NCT02786628.
Collapse
Affiliation(s)
- William A. Wood
- Lineberger Comprehensive Cancer Center and School of Medicine, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Deepika Dilip
- Memorial Sloan Kettering Cancer Center, New York, New York, United States of America
| | - Andriy Derkach
- Memorial Sloan Kettering Cancer Center, New York, New York, United States of America
| | - Natalie S. Grover
- Lineberger Comprehensive Cancer Center and School of Medicine, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Olivier Elemento
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, New York, United States of America
| | - Ross Levine
- Memorial Sloan Kettering Cancer Center, New York, New York, United States of America
| | - Gita Thanarajasingam
- Division of Hematology, Mayo Clinic, Rochester, Minnesota, United States of America
| | - John A. Batsis
- School of Medicine and Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Charlotte Bailey
- Lineberger Comprehensive Cancer Center and School of Medicine, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Arun Kannappan
- Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado, Aurora, Colorado, United States of America
| | - Steven M. Devine
- National Marrow Donor Program (NMDP)/Be The Match, Minneapolis, Minnesota, United States of America
| | - Andrew S. Artz
- Department of Hematology and Hematopoietic Cell Transplantation, City of Hope, Duarte, California
| | - Jennifer A. Ligibel
- Dana Farber Cancer Institute, Boston, Massachusetts, United States of America
| | - Ethan Basch
- Lineberger Comprehensive Cancer Center and School of Medicine, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Erin Kent
- Lineberger Comprehensive Cancer Center and Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Jacob Glass
- Memorial Sloan Kettering Cancer Center, New York, New York, United States of America
| |
Collapse
|
9
|
Wu C, Lorenzo G, Hormuth DA, Lima EABF, Slavkova KP, DiCarlo JC, Virostko J, Phillips CM, Patt D, Chung C, Yankeelov TE. Integrating mechanism-based modeling with biomedical imaging to build practical digital twins for clinical oncology. BIOPHYSICS REVIEWS 2022; 3:021304. [PMID: 35602761 PMCID: PMC9119003 DOI: 10.1063/5.0086789] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Accepted: 04/29/2022] [Indexed: 12/11/2022]
Abstract
Digital twins employ mathematical and computational models to virtually represent a physical object (e.g., planes and human organs), predict the behavior of the object, and enable decision-making to optimize the future behavior of the object. While digital twins have been widely used in engineering for decades, their applications to oncology are only just emerging. Due to advances in experimental techniques quantitatively characterizing cancer, as well as advances in the mathematical and computational sciences, the notion of building and applying digital twins to understand tumor dynamics and personalize the care of cancer patients has been increasingly appreciated. In this review, we present the opportunities and challenges of applying digital twins in clinical oncology, with a particular focus on integrating medical imaging with mechanism-based, tissue-scale mathematical modeling. Specifically, we first introduce the general digital twin framework and then illustrate existing applications of image-guided digital twins in healthcare. Next, we detail both the imaging and modeling techniques that provide practical opportunities to build patient-specific digital twins for oncology. We then describe the current challenges and limitations in developing image-guided, mechanism-based digital twins for oncology along with potential solutions. We conclude by outlining five fundamental questions that can serve as a roadmap when designing and building a practical digital twin for oncology and attempt to provide answers for a specific application to brain cancer. We hope that this contribution provides motivation for the imaging science, oncology, and computational communities to develop practical digital twin technologies to improve the care of patients battling cancer.
Collapse
Affiliation(s)
- Chengyue Wu
- Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, Texas 78712, USA
| | | | | | | | - Kalina P. Slavkova
- Department of Physics, The University of Texas at Austin, Austin, Texas 78712, USA
| | | | | | - Caleb M. Phillips
- Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, Texas 78712, USA
| | - Debra Patt
- Texas Oncology, Austin, Texas 78731, USA
| | - Caroline Chung
- Department of Radiation Oncology, MD Anderson Cancer Center, University of Texas, Houston, Texas 77030, USA
| | | |
Collapse
|
10
|
Williams S, Layard Horsfall H, Funnell JP, Hanrahan JG, Khan DZ, Muirhead W, Stoyanov D, Marcus HJ. Artificial Intelligence in Brain Tumour Surgery-An Emerging Paradigm. Cancers (Basel) 2021; 13:cancers13195010. [PMID: 34638495 PMCID: PMC8508169 DOI: 10.3390/cancers13195010] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Revised: 10/02/2021] [Accepted: 10/03/2021] [Indexed: 01/01/2023] Open
Abstract
Artificial intelligence (AI) platforms have the potential to cause a paradigm shift in brain tumour surgery. Brain tumour surgery augmented with AI can result in safer and more effective treatment. In this review article, we explore the current and future role of AI in patients undergoing brain tumour surgery, including aiding diagnosis, optimising the surgical plan, providing support during the operation, and better predicting the prognosis. Finally, we discuss barriers to the successful clinical implementation, the ethical concerns, and we provide our perspective on how the field could be advanced.
Collapse
Affiliation(s)
- Simon Williams
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK; (H.L.H.); (J.P.F.); (J.G.H.); (D.Z.K.); (W.M.); (H.J.M.)
- Wellcome/Engineering and Physical Sciences Research Council (EPSRC) Centre for Interventional and Surgical Sciences (WEISS), London W1W 7TY, UK;
- Correspondence:
| | - Hugo Layard Horsfall
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK; (H.L.H.); (J.P.F.); (J.G.H.); (D.Z.K.); (W.M.); (H.J.M.)
- Wellcome/Engineering and Physical Sciences Research Council (EPSRC) Centre for Interventional and Surgical Sciences (WEISS), London W1W 7TY, UK;
| | - Jonathan P. Funnell
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK; (H.L.H.); (J.P.F.); (J.G.H.); (D.Z.K.); (W.M.); (H.J.M.)
- Wellcome/Engineering and Physical Sciences Research Council (EPSRC) Centre for Interventional and Surgical Sciences (WEISS), London W1W 7TY, UK;
| | - John G. Hanrahan
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK; (H.L.H.); (J.P.F.); (J.G.H.); (D.Z.K.); (W.M.); (H.J.M.)
- Wellcome/Engineering and Physical Sciences Research Council (EPSRC) Centre for Interventional and Surgical Sciences (WEISS), London W1W 7TY, UK;
| | - Danyal Z. Khan
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK; (H.L.H.); (J.P.F.); (J.G.H.); (D.Z.K.); (W.M.); (H.J.M.)
- Wellcome/Engineering and Physical Sciences Research Council (EPSRC) Centre for Interventional and Surgical Sciences (WEISS), London W1W 7TY, UK;
| | - William Muirhead
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK; (H.L.H.); (J.P.F.); (J.G.H.); (D.Z.K.); (W.M.); (H.J.M.)
- Wellcome/Engineering and Physical Sciences Research Council (EPSRC) Centre for Interventional and Surgical Sciences (WEISS), London W1W 7TY, UK;
| | - Danail Stoyanov
- Wellcome/Engineering and Physical Sciences Research Council (EPSRC) Centre for Interventional and Surgical Sciences (WEISS), London W1W 7TY, UK;
| | - Hani J. Marcus
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK; (H.L.H.); (J.P.F.); (J.G.H.); (D.Z.K.); (W.M.); (H.J.M.)
- Wellcome/Engineering and Physical Sciences Research Council (EPSRC) Centre for Interventional and Surgical Sciences (WEISS), London W1W 7TY, UK;
| |
Collapse
|