Clinical Trial Details
— Status: Completed
Administrative data
| NCT number |
NCT05037383 |
| Other study ID # |
S65658 |
| Secondary ID |
|
| Status |
Completed |
| Phase |
N/A
|
| First received |
|
| Last updated |
|
| Start date |
September 27, 2021 |
| Est. completion date |
June 19, 2022 |
Study information
| Verified date |
November 2022 |
| Source |
Universitaire Ziekenhuizen KU Leuven |
| Contact |
n/a |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Interventional
|
Clinical Trial Summary
During minimally invasive surgery (MIS), surgeons manipulate sharp and stiff instruments in
the vicinity of fragile tissue, blood vessels, and critical nerves, where poor depth
perception can have dramatic consequences. Since typically, 2-dimensional visualization is
offered, to correctly infer the 3rd dimension, surgeons rely on their anatomical knowledge
and experience. During unforeseen events, correct depth information can make the difference
between success and failure. This explains the steep and long learning curve for surgeons.
The absence of proper depth information slows down execution and leads to an unnecessary
large mental load.
A recent document from the European Association of Endoscopic Surgery showed that 3D shortens
operative time and learning curves and reduces complications. 'What the best way is to
visualize 3D content' remains an open question. Near-to-eye displays provide small screens in
front of each eye, while stereoscopic displays use glasses to project the 3D content to the
eyes. The Da Vinci surgical system uses two individual optical panels. These systems are
bulky, or restrict head movement, thus users have remarks on the ergonomics. The glasses for
stereoscopic displays obscure the view, reduce brightness, and alter the color. Correct color
is crucial to recognize tissue types and details or parts in shaded areas. Stereoscopic 3D
displays lead to headache and eye-fatigue, called visually induced motion sickness in 11-22%
of surgeons after several surgeries.
Autostereoscopic Visualization (ASV) is appealing for medical applications. Besides the
improvement of depth perception, it allows 'glasses-free' operation. One of the key
components of such displays is eye-tracking, that locates the eyes of the user to be able to
render the 3D image to that viewpoint. ASV is a single-viewer application, which can be
challenging in an operating room, with multiple people present. Therefore, a rigorous
investigation is needed to maximize the performance of the algorithm and ensure the quality
of service needed for medical use. It is crucial to collect data from real scenarios by
recording the operation, the pose, motion of surgeons and the entire staff. These recordings
will deliver solid understanding of the circumstances and rate of occurrences where
eye-tracking and 3D visualization fails (or could fail). Furthermore, patterns can be
recognized that could help to develop a robust eye-tracking algorithm and safety features for
ASV.
Description:
1. Aim of the study
The aim of this study is to analyze the movement and direction of vision of the
surgeon's eyes during gynecological interventions. The assessment is done by making
video recordings of the medical staff during the procedure. The measured data consists
of:
- Position and movement of the medical personnel, and
- Position and movement of the displays/screens being used, and
- Light intensity during the surgical procedure A novel 3D visualization system is
being developed to improve the safety of minimally invasive surgery. For this
development, it is critical to understand current clinical practice during surgery.
The videos recorded during this study will directly help to determine the design
requirements for the development of the display.
2. Medical condition or intervention under investigation
Gynecological laparoscopic interventions that involve suturing or extensive dissection,
including hysterectomy, sacrocolpopexy and niche repair.
3. Study schedule
Eligible patients and involved staff members (i.e. surgeon, first assistant, nurse
handling the instruments) will be informed on the purpose and nature of the trial. When
consenting in written, intra-operative recordings will be carried out.
Since no patient data or follow-up on their condition is involved in the trial, the
study ends for all involved at the end of the operation.
4. Equipment used during the trial
Within the trial, video recording will be carried out by 4 depth cameras mounted in the
operating room. The depth cameras will be mounted on top of the displays used by the
operating staff. Each camera will be powered by a Raspberry Pi single board computer.
The members of the operating staff will be labeled with a visual marker on the head cap
to be able to track their movement. Markers will also be installed on the wall or
equipment within the field of view of the cameras, where they will be visible throughout
the operation. To be able to assess the change in visual circumstances during operation,
a LUX meter will be used. The videos will be streamed to a laptop where they will be
stored. The equipment is connected via a wireless manner, so no cables will be required.
5. Potential risks
No clinical risks are introduced by the study. The hardware and software are not in
contact with the patient or clinical staff, they are at a safe distance from the
surgical field, and there is no interference with other hardware used in the operation.
6. Assessment of pose
Assessment of the pose and movement of the displays and staff members will be
continuously registered by the depth camera and visual markers, which will also allow
identification of the roles of the personnel involved.
7. Video recordings
The video recordings will start only after the patient is installed and draped for
surgery, hence completely covered. Recordings will stop as soon as the operation is
finished, while the patient is still covered. If the surgeon decides that a part of the
recording is too sensitive or would violate the rights of any person involved, the
recordings will be paused for that period, or even discontinued entirely.
For the operating staff, their faces will be visible on the videos.
8. Selection of participants
Participants will be recruited at the Gynecology Department of the University Hospital
Leuven. All visiting women undergoing one of the selected surgeries and fulfilling the
inclusion criteria will be invited to participate unless the supervising clinician does
not think it is appropriate. Eligibility check of the patient can be as early as when
planning of the patient's surgery, or at the latest at hospital admission. She will be
informed about the study and may sign the informed consent when she opts into the study.
The operating staff at the Gynecological Department will be invited to participate. The
operating staff is informed about the study and may sign the informed consent or decide
not to take part in the study. For each operation to be eligible for the study,
voluntary informed consent is required from all staff members involved.
9. Sample size statistics
The study uses an adaptive sample size. First, an estimation of the order of magnitude
of the sample size was made based on literature, where videography was used to assess
staff behavior and motion analysis of surgeons with statistically significant results.
Then, a method for adjusting the sample size based on accumulating data will be used.
1. Anticipation of sample size based on literature review
Azevedo-Coste et al. made an assessment of the movements of clinical staff using an
optical motion tracking system, while the movement of the doors was monitored with
a wireless network of inertial sensors. Markers were placed on the staff members'
surgical cap based on their roles. The authors determined 30 recordings of
orthopedic and cardiac surgeries to obtain statistically significant results. Zheng
et al. conducted video recordings of laparoscopic Nissen fundoplication to examine
team cooperation among surgeons. Overall, 28 operations were required.
In conclusion, we anticipate that around 20-30 recordings may be needed, i.e. 60 to
90 recordings for the three operation types.
2. Adjustment of sample size based on accumulating data
In order to enable early stopping, we propose to perform interim analysis and
perform, based on accumulating data, the measurement of saturation based on the
method described by Guest et al. For each type of intervention, the recorded data
will be first evaluated after 5 recordings, which will be considered as a base of
collected information. Then, the dataset will be reevaluated after each new
recording. If the new information from all recorded metrics falls below a ≤5%
threshold, the new dataset will be considered to be similar, thus providing no new
information. The recorded dataset will be processed to extract the following
metrics from the data:
- Motion of operating staff
- Number of people present and the distance between the people
- Size and shape of the workspace (the space that is traveled) of the tracked
people in x,y and z coordinates
- walking pattern: trajectory of tracked people
- Distance of people from the displays
- Direction of gaze, which is estimated based on head orientation
- Movement of the display
- Size and shape of the workspace of the displays
- In x,y and z coordinates
- Illumination levels Each recording dataset will be compared to the union of
all the previously recorded datasets of the same surgical intervention and
based on the metrics below. For example, the second recording will be compared
to the first recording, while the third recording will be compared to both the
first and second recordings.
If 5 consecutive recordings of the investigated intervention show similarity, then
saturation is reached for that intervention, and the recordings will come to an
endpoint.
We also will stop further inclusion and recordings when 50 surgeries of each type
are studied.
3. Summary of sample size
An adaptive sample size will be used. Following 5 recordings of each type of operation,
the first calculation is made, and a first interim analysis is done after one additional
patient (minimum number: 3*6 = 18). The maximum is 3*50 = 150 recordings.
10. Statistical analysis
When saturation is reached, each type of operation will be analyzed statistically for
the metrics described above. More precisely, for each type of operation the mean and
standard deviation will be calculated for (if applicable, units are given between
brackets):
- Number of people present in the OR.
- The distance between people [m].
- Size of the workspace of people [m3].
- Walking pattern: travelled distance [m].
- Distance of people from the displays [m].
- Direction of the gaze, expressed as the distance between the center of the screen
and the point of focus on the screen [cm].
- Size of the workspace of the displays [m3].
- Illumination level [lx].
11. Collected data
All recorded data are labeled with a study number; one study includes all recordings
from all the cameras, hence includes visual information on patient and staff. The
recorded data contains color and depth video files. The coding of the recorded data is
different for staff members and patients.
Though data on each operation could be processed anonymously, we assume that the data of
participants are de facto pseudonymized: the data are "time- and date-stamped", so
identification of the patient or participating staff is theoretically possible via that
identifier. Moreover, on the recordings the faces of the staff are visible.
The principal investigator however will not keep a list of study numbers and
corresponding patient medical record numbers.
Recognition of patients As to visual recognition of the patient on the video-material,
recording is only made while the patient is draped, thus patients will not be
recognizable on the footages. The research team is obliged to protect the data from
disclosure outside the research according to the terms of the research protocol and the
informed consent document. No patient records will be stored for this study.
Recognition of staff members The data of participating staff members cannot be
anonymized. The faces of the personnel will be visible, thus individuals will be
recognizable on the footages. Furthermore, the visual markers will carry information on
their roles. The research team is obliged to protect the data from disclosure outside
the research according to the terms of the research protocol and the informed consent
document.
12. Data management and handling
Clinical information will not be released without the written permission of the
participant, except as necessary for monitoring, auditing, or inspection by the relevant
authorities.
The recording system used to collect the data has limited access measures by usernames
and passwords. Data will be collected electronically and the saved data will be hosted
at UZ Leuven, in the domain allocated to the PI. This is a password-protected domain and
access will be only possible to the personnel involved in the study (PI,
sub-investigator, administrator). Published results will not contain any personal data
that could allow the identification of individual participants.
13. Ethics and regulatory approvals
The trial will be conducted in compliance with the principles of the Declaration of Helsinki
(2013), the principles of GCP and in accordance with all applicable regulatory requirements.
This protocol and related documents will be submitted for review to Ethics Committee of the
University Hospital Leuven.
The study is conducted only on the basis of prior informed consent by the subjects to
participate in the study. The investigator shall obtain a signed informed consent form (ICF)
for all patients prior to their enrolment and participation in the study in compliance with
all applicable laws, regulations and the approval of the Ethics Committee. The investigator
shall retain such ICFs in accordance with the requirements of all applicable regulatory
agencies and laws.
The Investigators shall treat all information and data relating to the study disclosed to
them on this study as confidential and shall not disclose such information to any third
parties or use such information for any purpose other than the performance of the study. The
collection, processing and disclosure of personal data, such as patient health and medical
information are subject to compliance with applicable personal data protection and the
processing of personal data (The General Data Protection Regulation (EU) 2016/679 (GDPR)).
