Thyroid DiseasesPREVENTNCT04745793
Precise Recognition With Enhanced Vision of Endocrine Neck Targets
An observational study of Thyroid Diseases and Parathyroid Diseases, run by IHU Strasbourg at 1 site in France.
Trial summary
Iatrogenic injuries to the parathyroid glands during thyroid surgery or to the recurrent laryngeal nerve (RLN) do still occur, requiring often specialized management. Recently, it has been demonstrated that the parathyroid gland shows a significant autofluorescence. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Thyroid Diseases, Parathyroid Diseases
- What is being tested?
- Hyperspectral and Fluobeam acquisition
- How many people
- 54 participants
- Where
- 1 siteFrance
- Study dates
- 20 Jan 2021to 15 Oct 2021
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Adult patients of both sexes for whom a total or partial thyroid or parathyroid resection for a benign or malignant pathology is programmed
Who may be able to join
- Man or woman over 18 years old.
- Patient with benign or malignant pathology of the thyroid or parathyroid gland
- Patient with no contraindication to anesthesia and surgery
- Patient able to receive and understand information related to the study
- Patient affiliated to the French social security system.
Who cannot join
- Patient who needs an emergency surgery
- Pregnant or lactating patient.
- Patient under guardianship or trusteeship.
- Patient under the protection of justice.
Trial locations and contacts
1 site in 1 country.
France1 site
Service de Chirurgie Digestive et Endocrinienne, NHC
Strasbourg, 67000
About this study
Iatrogenic injuries to the parathyroid glands during thyroid surgery or to the recurrent laryngeal nerve (RLN) do still occur, requiring often specialized management.
Recently, it has been demonstrated that the parathyroid gland shows a significant autofluorescence. Using a commercially available Near-InfraRed (NIR) camera (Fluobeam®, Fluoptics©, France), the parathyroid glands can be clearly visualized by contrast-free fluorescence imaging. However it lacks real-time quantification of the fluorescence intensity.
Read more
The hyperspectral imaging (HSI), which is a technology that combines a spectrometer to a camera system, examines the optical properties of a large area in a wavelength range from NIR to visual light (VIS). It provides spatial information real time, in a contact-free, non-ionizing manner. The HSI technology would add the spatial information, thus enormously enhancing the intraoperative performance.
The aim of the proposed study is to identify the spectral features of the important neck target structures, in particular the parathyroid glands, using an appropriate deep learning algorithm, to perform an automated parathyroid recognition. Additionally, this study proposes to compare the detection rate of the hyperspectral based parathyroid recognition with the already existing NIR autofluorescence based recognition.
Read the detailed description
The major challenge in thyroid and parathyroid procedures, is the safe identification of the recurrent laryngeal nerve (RLN) and the localization of the parathyroid glands (to be preserved or to be selectively removed). Iatrogenic injuries to the parathyroid glands during thyroid surgery (resulting in transient or permanent hypocalcemia) or to the RLN (resulting in hoarseness, dysphonia, dyspnea) do still occur, requiring often specialized management.
The percentage of incidental parathyroidectomies, in specialized endocrine centers, is around 16%. In these cases, it is more likely to observe clinical relevant hypocalcemia than after planned parathyroidectomy for hyperparathyroidism. Therefore, there is a critical need for an intra-operative method enabling a precise, real-time parathyroid identification.
Recently, it has been demonstrated that the parathyroid gland shows a significant autofluorescence, which is caused by the optical properties of a still unknown intrinsic fluorophore. When the gland is excited by a light source with a wavelength ranging from 750-785 nm, it emits a fluorescence peak around 820 nm. Taking advantage of this property, Falco et al., using a commercially available NIR camera (Fluobeam®, Fluoptics©, France), could clearly visualize the parathyroid glands by contrast-free fluorescence imaging and could easily discriminate them from the thyroid and the surrounding tissue. The drawback with this autofluorescence-based imaging is that it lacks real-time quantification of the fluorescence intensity.
The hyperspectral imaging (HSI), which is a technology that combines a spectrometer to a camera system, examines the optical properties of a large area in a wavelength range from near infrared (NIR) to visual light (VIS). It provides diagnostic information about the tissue physiology, composition and perfusion. The fact that the HSI produces pictures, thus providing spatial information real time, in a contact-free, non-ionizing manner, makes it potentially a very valuable tool for the intraoperative use.
HSI has exhibited its great potential in the medical field especially in the diagnosis of various neoplasia (e.g. of the cervix, breast, colon, brain), in the detection of perfusion pattern in patients with peripheral arterial disease and in the area of wound diagnostic.
As previously shown, it is possible to discriminate the thyroid from the parathyroid glands according to the spectral characteristics, but the HSI technology would add the spatial information, thus enormously enhancing the intraoperative performance.
In collaboration with the University of Leipzig, Germany, the investigators performed a clinical pilot trial on 8 patients, which showed promising results. Hyperspectral images during benign endocrine surgery procedures were able to demonstrate that thyroid and parathyroid have specific hyperspectral signatures. Furthermore, the parathyroid glands showed usually less oxygenated than the thyroid. A discrimination of the parathyroid glands based on these characteristics is proven to be possible.
The aim of the proposed study is to identify the spectral features of the important neck target structures, in particular the parathyroid glands, using an appropriate deep learning algorithm, to perform an automated parathyroid recognition. Additionally, this study proposes to compare the detection rate of the hyperspectral based parathyroid recognition with the already existing NIR autofluorescence based recognition.
- Conditions
- Thyroid Diseases, Parathyroid Diseases
- Being tested
- Hyperspectral and Fluobeam acquisition
- Keywords
- Hyperspectral Imaging, Deep learning, Autonomous tissue recognition, Tissue spectral signature, Autofluorescence
- Medical subject headings
- Thyroid Diseases, Parathyroid Diseases
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Hyperspectral and Fluobeam acquisitionOther
Once enough exposure of the operative site is achieved, an RGB (Red Green Blue) picture will be taken and the surgeon will depict the parathyroid glands on it, this picture will act as "ground truth". At this point, without changing the surgical exposure, a second surgeon involved in the study will attempt once to detect the parathyroid glands intraoperatively using the HSI system and the Fluobeam® alternatively. The number and the position of the parathyroid glands visualized with each tool will be compared to the number and position of the glands previously visualized by the operating surgeon. The procedure will be repeated every time the surgeon attempts to visualize the parathyroid glands. The order of the detection tools randomized for each case will be preserved in case of repeated visualizations.
| Study group | Role | What they receive |
|---|---|---|
| Thyroids | The aim is to identify and preserve the parathyroid glands during the total or partial removal of the thyroid. Repeating of the procedure for each lobe Receives: Other: Hyperspectral and Fluobeam acquisition | |
| Parathyroids | The aim is to selectively remove the pathological parathyroid gland(s). Repeating of the procedure for each removed gland Receives: Other: Hyperspectral and Fluobeam acquisition |
What is being measured
The primary outcome is the main question the study is designed to answer.
Comparison of the intraoperative detection rate between the automated HSI-based parathyroid recognition against the surgeon's clinical appreciation.
Detection rate of the parathyroids by the automated HSI-based parathyroid recognition against the visual identification by the operating surgeon (clinical ground truth) and, if required by the surgeon, against the histopathological examination (extemporaneous anatomopathology = histological ground truth). Also, final pathology will be used as ground truth.
Measured: 1 day
Comparison of the intraoperative detection rate between the Fluobeam®, against the surgeon's clinical appreciation.
Detection rate of the parathyroids by the Fluobeam® against the visual identification by the operating surgeon (clinical ground truth) and, if required by the surgeon, against the histopathological examination (extemporaneous anatomopathology = histological ground truth). Also, final pathology will be used as ground truth.
Measured: 1 day
Secondary outcomes (5)
in vivo collection of HSI spectral features of the parathyroid and thyroid glands to successively enable automated recognition.
Collection of clean and consistent datasets of the parathyroid and thyroid glands
Measured: 1 day
in vivo collection of HSI spectral signatures of other tissues routinely exposed during neck surgery, such as thyroid, fat, muscle, cartilage and nerves will be collected.
Collection of clean and consistent datasets of other tissues exposed during neck surgery. The information will be implemented in the machine learning algorithm in order to allow in the future an automated recognition of the different target structures during neck surgery.
Measured: 1 day
Recognition of possible pathology specific HSI spectral features of pathological parathyroid or thyroid glands.
The ability to predict pathological parathyroid or thyroid glands from the spectral tissue information, based on the final histopathological reports.
Measured: 1 month
Difference in time to recognition between human eye, Fluobeam® and HSI
Comparison between the time of recognition using the HSI algorithm and the Fluobeam®
Measured: 1 day
Detection rate of the recurrent laryngeal nerve against the clinical impression and the intraoperative neuromonitoring.
Number of times the recurrent laryngeal nerve is detected by the automated identification against the number of time it is visually identified by the operating surgeon and confirmed with the Intraoperative neuromonitoring (IONM).
Measured: 1 day
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted9 Feb 2021
- Study start20 Jan 2021
- Primary completion15 Oct 2021
- Study completion15 Oct 2021
Why it stopped: Data acquisition not possible anymore
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (18)Papers the sponsor has linked to this study.
- Other trials for Thyroid DiseasesStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 54 participants (actual)
Sponsor and investigators
- Lead sponsor
- IHU Strasbourg
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Michele DIANA, MD, PhD, Principal investigator, Service de Chirurgie Digestive et Endocrinienne, NHC, Strasbourg
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04745793
- Sponsor's protocol ID
- 20-007
- Acronym
- PREVENT
- Status last verified
- Jan 2024
- First submitted
- 4 Feb 2021
- Last updated
- 9 Jan 2024
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Mohebati A, Shaha AR. Anatomy of thyroid and parathyroid glands and neurovascular relations. Clin Anat. 2012 Jan;25(1):19-31. doi: 10.1002/ca.21220. Epub 2011 Jul 28.
PubMed 21800365Christou N, Mathonnet M. Complications after total thyroidectomy. J Visc Surg. 2013 Sep;150(4):249-56. doi: 10.1016/j.jviscsurg.2013.04.003. Epub 2013 Jun 6.
PubMed 23746996Nair CG, Babu MJ, Menon R, Jacob P. Hypocalcaemia following total thyroidectomy: An analysis of 806 patients. Indian J Endocrinol Metab. 2013 Mar;17(2):298-303. doi: 10.4103/2230-8210.109718.
PubMed 23776907Yazici P, Bozkurt E, Citgez B, Kaya C, Mihmanli M, Uludag M. Incidental parathyroidectomy as a cause of postoperative hypocalcemia after thyroid surgery: reality or illusion? Minerva Chir. 2014 Dec;69(6):315-320. Epub 2014 Sep 22.
PubMed 25242004Berber E, Parikh RT, Ballem N, Garner CN, Milas M, Siperstein AE. Factors contributing to negative parathyroid localization: an analysis of 1000 patients. Surgery. 2008 Jul;144(1):74-9. doi: 10.1016/j.surg.2008.03.019. Epub 2008 May 21.
PubMed 18571587Falco J, Dip F, Quadri P, de la Fuente M, Prunello M, Rosenthal RJ. Increased identification of parathyroid glands using near infrared light during thyroid and parathyroid surgery. Surg Endosc. 2017 Sep;31(9):3737-3742. doi: 10.1007/s00464-017-5424-1. Epub 2017 Mar 31.
PubMed 28364157Falco J, Dip F, Quadri P, de la Fuente M, Rosenthal R. Cutting Edge in Thyroid Surgery: Autofluorescence of Parathyroid Glands. J Am Coll Surg. 2016 Aug;223(2):374-80. doi: 10.1016/j.jamcollsurg.2016.04.049. Epub 2016 May 20.
PubMed 27212004Li Q, He X, Wang Y, Liu H, Xu D, Guo F. Review of spectral imaging technology in biomedical engineering: achievements and challenges. J Biomed Opt. 2013 Oct;18(10):100901. doi: 10.1117/1.JBO.18.10.100901.
PubMed 24114019Lu G, Fei B. Medical hyperspectral imaging: a review. J Biomed Opt. 2014 Jan;19(1):10901. doi: 10.1117/1.JBO.19.1.010901.
PubMed 24441941Siddiqi AM, Li H, Faruque F, Williams W, Lai K, Hughson M, Bigler S, Beach J, Johnson W. Use of hyperspectral imaging to distinguish normal, precancerous, and cancerous cells. Cancer. 2008 Feb 25;114(1):13-21. doi: 10.1002/cncr.23286.
PubMed 18213691Panasyuk SV, Yang S, Faller DV, Ngo D, Lew RA, Freeman JE, Rogers AE. Medical hyperspectral imaging to facilitate residual tumor identification during surgery. Cancer Biol Ther. 2007 Mar;6(3):439-46. doi: 10.4161/cbt.6.3.4018. Epub 2007 Mar 16.
PubMed 17374984Kumashiro R, Konishi K, Chiba T, Akahoshi T, Nakamura S, Murata M, Tomikawa M, Matsumoto T, Maehara Y, Hashizume M. Integrated Endoscopic System Based on Optical Imaging and Hyperspectral Data Analysis for Colorectal Cancer Detection. Anticancer Res. 2016 Aug;36(8):3925-32.
PubMed 27466495Fabelo H, Ortega S, Ravi D, Kiran BR, Sosa C, Bulters D, Callico GM, Bulstrode H, Szolna A, Pineiro JF, Kabwama S, Madronal D, Lazcano R, J-O'Shanahan A, Bisshopp S, Hernandez M, Baez A, Yang GZ, Stanciulescu B, Salvador R, Juarez E, Sarmiento R. Spatio-spectral classification of hyperspectral images for brain cancer detection during surgical operations. PLoS One. 2018 Mar 19;13(3):e0193721. doi: 10.1371/journal.pone.0193721. eCollection 2018.
PubMed 29554126Sumpio BJ, Citoni G, Chin JA, Sumpio BE. Use of hyperspectral imaging to assess endothelial dysfunction in peripheral arterial disease. J Vasc Surg. 2016 Oct;64(4):1066-73. doi: 10.1016/j.jvs.2016.03.463. Epub 2016 Jun 4.
PubMed 27266597Khaodhiar L, Dinh T, Schomacker KT, Panasyuk SV, Freeman JE, Lew R, Vo T, Panasyuk AA, Lima C, Giurini JM, Lyons TE, Veves A. The use of medical hyperspectral technology to evaluate microcirculatory changes in diabetic foot ulcers and to predict clinical outcomes. Diabetes Care. 2007 Apr;30(4):903-10. doi: 10.2337/dc06-2209. Epub 2007 Feb 15.
PubMed 17303790
Study at a glance
From the registry record, last updated by the sponsor on 9 Jan 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Precise Recognition With Enhanced Vision of Endocrine Neck Targets
- ClinicalTrials.gov ID
- NCT04745793
- Acronym / sponsor ID
- PREVENT / 20-007
- Conditions
- Thyroid Diseases, Parathyroid Diseases
- Keywords
- Hyperspectral Imaging, Deep learning, Autonomous tissue recognition, Tissue spectral signature, Autofluorescence
- Study type
- Observational
- Recruitment status
- TerminatedReason stopped: Data acquisition not possible anymore
- Enrolment
- 54 participants (actual)
- Lead sponsor
- IHU StrasbourgUniversity, hospital or other
- Study start
- 20 Jan 2021 (actual)
- Primary completion
- 15 Oct 2021 (actual)
- Study completion
- 15 Oct 2021 (actual)
- First posted
- 9 Feb 2021 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Iatrogenic injuries to the parathyroid glands during thyroid surgery or to the recurrent laryngeal nerve (RLN) do still occur, requiring often specialized management.
Recently, it has been demonstrated that the parathyroid gland shows a significant autofluorescence. Using a commercially available Near-InfraRed (NIR) camera (Fluobeam®, Fluoptics©, France), the parathyroid glands can be clearly visualized by contrast-free fluorescence imaging. However it lacks real-time quantification of the fluorescence intensity.
The hyperspectral imaging (HSI), which is a technology that combines a spectrometer to a camera system, examines the optical properties of a large area in a wavelength range from NIR to visual light (VIS). It provides spatial information real time, in a contact-free, non-ionizing manner. The HSI technology would add the spatial information, thus enormously enhancing the intraoperative performance.
The aim of the proposed study is to identify the spectral features of the important neck target structures, in particular the parathyroid glands, using an appropriate deep learning algorithm, to perform an automated parathyroid recognition. Additionally, this study proposes to compare the detection rate of the hyperspectral based parathyroid recognition with the already existing NIR autofluorescence based recognition.
Detailed description
The major challenge in thyroid and parathyroid procedures, is the safe identification of the recurrent laryngeal nerve (RLN) and the localization of the parathyroid glands (to be preserved or to be selectively removed). Iatrogenic injuries to the parathyroid glands during thyroid surgery (resulting in transient or permanent hypocalcemia) or to the RLN (resulting in hoarseness, dysphonia, dyspnea) do still occur, requiring often specialized management.
The percentage of incidental parathyroidectomies, in specialized endocrine centers, is around 16%. In these cases, it is more likely to observe clinical relevant hypocalcemia than after planned parathyroidectomy for hyperparathyroidism. Therefore, there is a critical need for an intra-operative method enabling a precise, real-time parathyroid identification.
Recently, it has been demonstrated that the parathyroid gland shows a significant autofluorescence, which is caused by the optical properties of a still unknown intrinsic fluorophore. When the gland is excited by a light source with a wavelength ranging from 750-785 nm, it emits a fluorescence peak around 820 nm. Taking advantage of this property, Falco et al., using a commercially available NIR camera (Fluobeam®, Fluoptics©, France), could clearly visualize the parathyroid glands by contrast-free fluorescence imaging and could easily discriminate them from the thyroid and the surrounding tissue. The drawback with this autofluorescence-based imaging is that it lacks real-time quantification of the fluorescence intensity.
The hyperspectral imaging (HSI), which is a technology that combines a spectrometer to a camera system, examines the optical properties of a large area in a wavelength range from near infrared (NIR) to visual light (VIS). It provides diagnostic information about the tissue physiology, composition and perfusion. The fact that the HSI produces pictures, thus providing spatial information real time, in a contact-free, non-ionizing manner, makes it potentially a very valuable tool for the intraoperative use.
HSI has exhibited its great potential in the medical field especially in the diagnosis of various neoplasia (e.g. of the cervix, breast, colon, brain), in the detection of perfusion pattern in patients with peripheral arterial disease and in the area of wound diagnostic.
As previously shown, it is possible to discriminate the thyroid from the parathyroid glands according to the spectral characteristics, but the HSI technology would add the spatial information, thus enormously enhancing the intraoperative performance.
In collaboration with the University of Leipzig, Germany, the investigators performed a clinical pilot trial on 8 patients, which showed promising results. Hyperspectral images during benign endocrine surgery procedures were able to demonstrate that thyroid and parathyroid have specific hyperspectral signatures. Furthermore, the parathyroid glands showed usually less oxygenated than the thyroid. A discrimination of the parathyroid glands based on these characteristics is proven to be possible.
The aim of the proposed study is to identify the spectral features of the important neck target structures, in particular the parathyroid glands, using an appropriate deep learning algorithm, to perform an automated parathyroid recognition. Additionally, this study proposes to compare the detection rate of the hyperspectral based parathyroid recognition with the already existing NIR autofluorescence based recognition.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Thyroids | – | Other: Hyperspectral and Fluobeam acquisitionThe aim is to identify and preserve the parathyroid glands during the total or partial removal of the thyroid. Repeating of the procedure for each lobe |
| Parathyroids | – | Other: Hyperspectral and Fluobeam acquisitionThe aim is to selectively remove the pathological parathyroid gland(s). Repeating of the procedure for each removed gland |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Adult patients of both sexes for whom a total or partial thyroid or parathyroid resection for a benign or malignant pathology is programmed
Key inclusion criteria (5 listed)
- Man or woman over 18 years old.
- Patient with benign or malignant pathology of the thyroid or parathyroid gland
- Patient with no contraindication to anesthesia and surgery
- Patient able to receive and understand information related to the study
- Patient affiliated to the French social security system.
Key exclusion criteria (4 listed)
- Patient who needs an emergency surgery
- Pregnant or lactating patient.
- Patient under guardianship or trusteeship.
- Patient under the protection of justice.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Hyperspectral and Fluobeam acquisitionOnce enough exposure of the operative site is achieved, an RGB (Red Green Blue) picture will be taken and the surgeon will depict the parathyroid glands on it, this picture will act as "ground truth". At this point, without changing the surgical exposure, a second surgeon involved in the study will attempt once to detect the parathyroid glands intraoperatively using the HSI system and the Fluobeam® alternatively. The number and the position of the parathyroid glands visualized with each tool will be compared to the number and position of the glands previously visualized by the operating surgeon. The procedure will be repeated every time the surgeon attempts to visualize the parathyroid glands. The order of the detection tools randomized for each case will be preserved in case of repeated visualizations. | Other | Parathyroids, Thyroids |
Primary outcome
Comparison of the intraoperative detection rate between the automated HSI-based parathyroid recognition against the surgeon's clinical appreciation.
Time frame: 1 day
Detection rate of the parathyroids by the automated HSI-based parathyroid recognition against the visual identification by the operating surgeon (clinical ground truth) and, if required by the surgeon, against the histopathological examination (extemporaneous anatomopathology = histological ground truth). Also, final pathology will be used as ground truth.
Comparison of the intraoperative detection rate between the Fluobeam®, against the surgeon's clinical appreciation.
Time frame: 1 day
Detection rate of the parathyroids by the Fluobeam® against the visual identification by the operating surgeon (clinical ground truth) and, if required by the surgeon, against the histopathological examination (extemporaneous anatomopathology = histological ground truth). Also, final pathology will be used as ground truth.
5 secondary outcomes
in vivo collection of HSI spectral features of the parathyroid and thyroid glands to successively enable automated recognition.
Time frame: 1 day
in vivo collection of HSI spectral signatures of other tissues routinely exposed during neck surgery, such as thyroid, fat, muscle, cartilage and nerves will be collected.
Time frame: 1 day
Recognition of possible pathology specific HSI spectral features of pathological parathyroid or thyroid glands.
Time frame: 1 month
Difference in time to recognition between human eye, Fluobeam® and HSI
Time frame: 1 day
Detection rate of the recurrent laryngeal nerve against the clinical impression and the intraoperative neuromonitoring.
Time frame: 1 day
Results and safety
The study was stopped early (reason given: Data acquisition not possible anymore). Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 9 Jan 2024.
- Background: PubMed 21800365Mohebati A, Shaha AR. Anatomy of thyroid and parathyroid glands and neurovascular relations. Clin Anat. 2012 Jan;25(1):19-31. doi: 10.1002/ca.21220. Epub 2011 Jul 28.
- Background: PubMed 23746996Christou N, Mathonnet M. Complications after total thyroidectomy. J Visc Surg. 2013 Sep;150(4):249-56. doi: 10.1016/j.jviscsurg.2013.04.003. Epub 2013 Jun 6.
- Background: PubMed 23776907Nair CG, Babu MJ, Menon R, Jacob P. Hypocalcaemia following total thyroidectomy: An analysis of 806 patients. Indian J Endocrinol Metab. 2013 Mar;17(2):298-303. doi: 10.4103/2230-8210.109718.
- Background: PubMed 25242004Yazici P, Bozkurt E, Citgez B, Kaya C, Mihmanli M, Uludag M. Incidental parathyroidectomy as a cause of postoperative hypocalcemia after thyroid surgery: reality or illusion? Minerva Chir. 2014 Dec;69(6):315-320. Epub 2014 Sep 22.
- Background: PubMed 18571587Berber E, Parikh RT, Ballem N, Garner CN, Milas M, Siperstein AE. Factors contributing to negative parathyroid localization: an analysis of 1000 patients. Surgery. 2008 Jul;144(1):74-9. doi: 10.1016/j.surg.2008.03.019. Epub 2008 May 21.
- Background: PubMed 28364157Falco J, Dip F, Quadri P, de la Fuente M, Prunello M, Rosenthal RJ. Increased identification of parathyroid glands using near infrared light during thyroid and parathyroid surgery. Surg Endosc. 2017 Sep;31(9):3737-3742. doi: 10.1007/s00464-017-5424-1. Epub 2017 Mar 31.
- Background: PubMed 27212004Falco J, Dip F, Quadri P, de la Fuente M, Rosenthal R. Cutting Edge in Thyroid Surgery: Autofluorescence of Parathyroid Glands. J Am Coll Surg. 2016 Aug;223(2):374-80. doi: 10.1016/j.jamcollsurg.2016.04.049. Epub 2016 May 20.
- Background: PubMed 24114019Li Q, He X, Wang Y, Liu H, Xu D, Guo F. Review of spectral imaging technology in biomedical engineering: achievements and challenges. J Biomed Opt. 2013 Oct;18(10):100901. doi: 10.1117/1.JBO.18.10.100901.
- Background: PubMed 24441941Lu G, Fei B. Medical hyperspectral imaging: a review. J Biomed Opt. 2014 Jan;19(1):10901. doi: 10.1117/1.JBO.19.1.010901.
- Background: PubMed 18213691Siddiqi AM, Li H, Faruque F, Williams W, Lai K, Hughson M, Bigler S, Beach J, Johnson W. Use of hyperspectral imaging to distinguish normal, precancerous, and cancerous cells. Cancer. 2008 Feb 25;114(1):13-21. doi: 10.1002/cncr.23286.
- Background: PubMed 17374984Panasyuk SV, Yang S, Faller DV, Ngo D, Lew RA, Freeman JE, Rogers AE. Medical hyperspectral imaging to facilitate residual tumor identification during surgery. Cancer Biol Ther. 2007 Mar;6(3):439-46. doi: 10.4161/cbt.6.3.4018. Epub 2007 Mar 16.
- Background: PubMed 27466495Kumashiro R, Konishi K, Chiba T, Akahoshi T, Nakamura S, Murata M, Tomikawa M, Matsumoto T, Maehara Y, Hashizume M. Integrated Endoscopic System Based on Optical Imaging and Hyperspectral Data Analysis for Colorectal Cancer Detection. Anticancer Res. 2016 Aug;36(8):3925-32.
- Barberio et al. Hyperspectral based discrimination of thyroid and parathyroid during surgery. Current Directions in Biomedical Engineering (2018)4:399-402Link provided by the sponsor.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Michele DIANA, MD, PhD principal investigator
Service de Chirurgie Digestive et Endocrinienne, NHC, Strasbourg
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Thyroid Diseases and Parathyroid Diseases, run by IHU Strasbourg at 1 site in France.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 5 inclusion and 4 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: stopped early, as of the sponsor's last update on 9 Jan 2024. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in France. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study was stopped early (reason given: Data acquisition not possible anymore). Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Comparison of the intraoperative detection rate between the automated HSI-based parathyroid recognition against the surgeon's clinical appreciation. (time frame: 1 day). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT04745793, which also lists 18 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 9 Jan 2024.