Clinical Trial Details
— Status: Completed
Administrative data
| NCT number |
NCT03994341 |
| Other study ID # |
NEC-01 |
| Secondary ID |
|
| Status |
Completed |
| Phase |
|
| First received |
|
| Last updated |
|
| Start date |
August 13, 2019 |
| Est. completion date |
April 2, 2020 |
Study information
| Verified date |
November 2020 |
| Source |
Ottawa Hospital Research Institute |
| Contact |
n/a |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Observational
|
Clinical Trial Summary
Necrotizing enterocolitis (NEC) is a devastating disease affecting the intestines of
premature infants. It involves intestine swelling, tissue destruction, infection, and even
death. Improved outcome is highly dependent on early recognition and treatment, however the
signs and symptoms of NEC in early stages are not obvious making it difficult to diagnose.
Abdominal x-rays and ultrasound can be non-specific and may not show signs of the disease
until late in its course.
Infrared imaging is a non-invasive, non-radiation method that can measure the heat given off
of the surface of the body and create heat maps. It is being used clinically in other
situations but is still under investigation for use in preterm infants with suspected NEC.
Computer analysis of the measured heat maps can be used to detect changes in the intestine
such as the swelling or tissue destruction involved in NEC.
Our group has previously performed a pilot study that showed that infrared imaging on babies
in the NICU can be used to create heat maps that are different between normal babies and
those with NEC when analyzed using specialized computer programs. In this study the
investigators will improve the imaging process by using special vision sensors to automate
the imaging process and make it easier for bedside staff to use this technology. Special
programs will be developed to automatically select areas of interest over which temperature
maps will be analyzed. The investigators will use this new imaging technique to study a
population of newborns diagnosed with definitive NEC and a healthy population of newborns
without NEC, and compare the heat maps obtained from each group. From the analysis of the
images obtained from these two populations, the investigators will determine the suitability
and necessary fine-tuning of this new imaging technique with the hopes that this technology
can someday aid in the early diagnosis of NEC.
Description:
Background information about NEC:
The best prognosis requires early recognition and treatment of NEC. Perforation or ongoing
deterioration may require surgical intervention. Mortality has improved in recent years but
is still about 15-30 % for non-surgical NEC and up to 50% for surgical NEC. Survivors may
suffer significant complications including long-term damage to bowel function.
The initial diagnosis is based on clinical exam and diagnostic imaging, usually involving
abdominal x-rays +/- ultrasound. Bell's staging criteria incorporates clinical, laboratory,
and radiographic findings, and is used to discern suspected NEC from definitive NEC. Bell's
stage 2 denotes proven NEC and involves the presence of pneumatosis intestinalis and/or
portal venous gas on x-ray.
The main difficulty when diagnosing NEC is that early/suspected stages of NEC present
clinically and radiographically in a similar way to benign feeding intolerance seen with
prematurity. Abdominal x-rays involve exposure of the patient to ionizing radiation and
ultrasound imaging is disruptive to the patient, takes time to perform, and requires skilled
operators who have limited availability. These modalities will only show non-specific changes
in early stages of NEC. Late findings are more discerning, however by the time these findings
are apparent the optimal time frame to initiate treatment is often missed.
Background Information About Medical Thermography:
Medical infrared (IR) imaging is a combination of medical technology, infrared camera
technology and computer multimedia technology. Infrared imaging devices record the human
thermal fields. The human body is a natural biological heating source and an infrared thermal
imager converts the far-infrared light wave radiated by the human body to an electrical
signal which is then converted into a digital quantity by analog/digital conversion. The
signals are processed by multimedia image processing technology into a color heat map,
showing the body's temperature field. A normal, healthy body has a characteristic heat map
while an abnormal body exhibits deviations from this heat map. Thus, comparing the
similarities and differences between the two, in combination with clinical diagnosis, doctors
and researchers can infer the nature and extent of a disease.
The investigators investigated various methods of computerized assessment of thermal images
obtained from premature babies with definitive NEC compared with normal babies with no
symptoms of feeding intolerance. The investigators showed that the discriminating power of
the surface temperature evolution data between healthy control babies and those who were
diagnosed with NEC was promising, with fairly high classification rate and a simple linear
classification scheme. In addition, our results suggested a slower rate of decrease of
abdominal skin temperature in the NEC babies, which might be explained by the presence of
inflamed bowel. Rice et al. also used medical thermography to help detect NEC in newborn
infants admitted to the NICU. By comparing temperature distribution over abdominal segments
to those of the chest, they were able to determine differences in normal babies vs those
diagnosed with NEC.
Background Information About Medical Microsoft Kinect Sensor:
The Kinect sensor is a widely used, consumer-grade, and safe color and depth camera
commercially marketed for use in computer gaming. It measures near infrared light reflected
off the body to form a surface map of the environment. The RGB-D Kinect sensor has recently
been applied to healthcare in a variety of applications where it has shown to be effective,
including the field of medical rehabilitation, where Kinect sensors are used for active
exercise training and rehabilitation of patients,for safe and automated radiotherapy
delivery, for chest wall motion analysis in cystic fibrosis patients, for facial feature
analysis of posture control in rehabilitation patients, in ICU patients for automated
mobility measurements, and even automated apnea monitoring in infants and children.
In this study, the RGB-D Kinect sensor's role will essentially consist of supporting the
automated segmentation, and retrieval of thermal distribution data from the co-located and
calibrated IR FLIR imager. Thanks to the color and depth maps that will be made available,
classical and robust image processing techniques will be leveraged to identify regions of
interest (the baby's body and eventually abdomen). This sort of precise segmentation cannot
be reliably performed solely from IR images, as it is well established that computer vision
and image processing techniques are not well adapted for IR images. Early laboratory tests
have already been conducted to determine that the operation of the RGB-D sensor in an
overlapping field of view with that of the IR imager does not influence the data collected in
the heat map. The combined operation is therefore safe and will provide an accurate thermal
distribution as if the IR imager was operating alone. The end goal is to combine the
strengths of three imaging technologies to improve medical diagnosis.
Study Rationale:
Previous studies investigating thermography and diagnosing NEC only used an infrared camera
to acquire images. Although the investigators were able to derive thermal distributions for
babies of various GA's, our previous study did not adopt a strict protocol for positioning
the IR sensor in an optimal configuration, leading to more variations in image quality and
size of region of interest. These limitations made it difficult to automate the selection of
accurate regions of interest within the thermal image and required manual intervention from
an image processing expert. In our current study the image acquisition process will be
improved upon and standardized; a Microsoft Kinect sensor utilizing thermal, color and active
depth vision will be integrated into a thermographic camera to allow for automated selection
of regions of interest and will facilitate ease of use by medical personal at the patient's
bedside. Embedded image processing algorithms will be developed to exploit the multi-spectral
nature of collected information in order to automatically segment and unclutter the region of
interest over which thermal distributions of relevance will be monitored.
Initial development of this system, including apparatus integration and assembly, rigorous
camera calibration procedures in between the RGB-D and IR sensors, and complete testing will
be performed in a laboratory environment, using only mock-up models of the clinical
environment. Then, in order to fully validate the application of this automated infrared
image processing system for early diagnosis of NEC, acquisition of relevant images from human
subjects is needed. The study will be pursued in the NICU environment to further validate the
newly developed non-invasive and automated imaging protocol on babies of various sizes and GA
in the NICU, since NEC can occur in babies ranging from extremely premature to those born at
term. Since the investigators hope to use this technology someday to help improve the
diagnosis of NEC, the experimental imaging procedure will be performed on two patient
populations. The investigators will first image the abdomens of a group of healthy newborns
with the newly developed apparatus and image processing protocol to set up a standard thermal
distribution. Then, the investigators will also image the abdomens of a group of newborns
with proven NEC, using the same equipment. From the analysis of images from these two
populations, the investigators will determine the suitability and necessary fine-tuning of
the proposed automated infrared imaging tools, with the objective of augmenting the
precision, usability, and reliability of the procedure for early diagnosis of NEC.
Objectives:
1. Develop an automated approach to the imaging and analysis of preterm infants' abdomens
using thermographic sensors and embedded image processing algorithms.
2. Derive thermographic temperature distributions of the abdomens of two groups of babies:
those who are normal (have no signs of feeding intolerance or signs of NEC), and those
who have been diagnosed with proven NEC.
3. Determine if the automated image processing algorithms can discern a statistically
significant difference between the normal thermal distributions and those derived from
babies with NEC.
