Due to copyright issues, an electronic copy of the thesis must be ordered from the faculty. For the faculty to have time to process the order, the order must be received by the faculty at the latest 2 days before the public defence. Orders received later than 2 days before the defence will not be processed. After the public defence, please address any inquiries regarding the thesis to the candidate.
Trial Lecture – time and place
See Trial Lecture.
Adjudication committee
- First opponent: Professor John Simpson, Evelinas London Hospital, UK
- Second opponent: Associate Professor Phan Kiet Tran, Lund University, Sweden
- Third member and chair of the evaluation committee: Associate Professor Anette Ramm-Pettersen, University of Oslo
Chair of the Defence
Professor Emeritus Harald Lindberg, University of Oslo
Principal Supervisor
Consultant Pediatric Cardiologist Henrik Brun, Oslo University Hospital
Summary
Structural heart disease can result in an abnormal heart architecture that holds actual or potential functional significance. Structural abnormalities affect up to 1% of newborns. The prevalence of congenital heart defects in adults has risen as diagnostic and management techniques have improved over recent decades. Nonetheless, residual postsurgical lesions often necessitate additional surgeries or impose lifestyle limitations, particularly in cases of complex morphologies. A crucial aspect is the visualisation of defects to facilitate early diagnosis of complications and to plan further management. Until now, visualisation has been limited to flat screens, lacking true depth perception.
This thesis sought to enhance cardiac 3D visualisation in patients with anatomic digital twins, which were developed through a combination of artificial intelligence for image processing and mixed reality "holograms." Across several studies, we investigated the potential future applications of this technology and its impact on clinical decision-making and patient outcomes.
In the first study, we examined the incidence of one of the most complex structural defects, double outlet right ventricle, in Norway and detailed patient outcomes. Annually, 1.18 per 10,000 live births are affected by this defect. Postoperative complications and the need for redo surgeries are anticipated to be significant, with total mortality occurring in nearly one in ten patients and postoperative complications in one in three.
In the second study, we developed a deep learning algorithm to create anatomic digital twins, significantly reducing the time required to integrate this technology into the clinical workflow. Several technical aspects have been optimized to meet clinical needs.
In the third study, we challenged the conventional approach to clinical decision-making and patient outcomes by incorporating additional cardiac anatomic digital twins into standardized interdisciplinary heart team meetings. In two-thirds of the cases, the decision was altered to some extent, and participants expressed enthusiasm for this technology. There was also a trend toward fewer complications.
In the fourth study, we developed digital heart patches tailored for various structural heart defects and assessed their performance against intraoperative findings. The "holopatches" proved to be comparable and showed potential in enhancing adaptation to complex anatomical structures.
In conclusion, this study has demonstrated that static anatomic digital twins significantly enhance and refine diagnostic accuracy in preoperative planning, thereby paving the way for the integration of this technology into real-world applications.
Additional information
Contact the research support staff.