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This project aims at assessing two MRI acquisition methods, neurography and tractography, for the visualization of pelvic nerves. The goal is to optimize both methods and to test them on a pool of volunteers to assess if nerves can be delineated, so as to provide an individualized mapping of nerves to surgeons before an intervention and avoid postoperative complications.
Nerves of the autonomic nervous system are frequently damaged during pelvic surgery, and those injuries may lead to postoperative complications like incontinence or impotence. This study aims at developing an imaging protocol providing images where nerves can be visualized and segmented. A simple preoperative MRI exam might yield an individualized mapping of pelvic nerves that would be combined to augmented reality, thereby providing a valuable support to guide surgeons during an intervention by indicating location of the nerves that have to be preserved.
Up to now, investigations have been carried out with a 1.5 Tesla (1.5T) MRI system on an animal model (pig). MRI is non irradiant and non invasive imaging modality that proved to be a valuable method to visualize small structures like nerves. Investigations focused on MRI neurography, an anatomical imaging method highlighting nerves, and MRI tractography, a diffusion-tensor-based imaging method allowing reconstruction of nervous fibers. However, the swine model is not ideal due to major differences with human, more particularly the fact that the human pelvis contains a lot of fat unlike the swine pelvis, which is an interesting feature as there is a good contrast between fat and tissue in MRI. Therefore, it is important to perform new investigations in healthy volunteers to refine and assess the MRI acquisitions. Those investigations will be performed with a 3Tesla (3T) system from the same manufacturer, providing the same sequences but a higher field strength which should offer higher signal. There will be no injection of contrast agent. The protocol will use standard sequences from the manufacturer with parameters adjusted for the purposes of the study. The image quality will be scored on a 5-point Likert scale (0 = no possible delineation to 4=nerves are entirely visible).
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| MRI acquisition - no contrast agent | Experimental | Volunteers will have an MRI with a 3T clinical system. Installation will be performed according to standard protocols. Different neurography and tractography sequences will be acquired in order to get different contrasts. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| MRI acquisition - no contrast agent | Procedure | No surgery. Volunteers will have an MRI with a 3T clinical system. Installation will be performed according to standard protocols. Different neurography and tractography sequences will be acquired in order to get different contrasts. |
| Measure | Description | Time Frame |
|---|---|---|
| Assessment of image quality to delineate and identify nerves | The assessment of image quality to delineate and identify nerves will be scored on a five-point Likert scale by the operator, and independently reviewed by a radiologist. | At the time of exam |
| Measure | Description | Time Frame |
|---|---|---|
| Image quality at 1.5T and 3T by comparison of signal-to-noise ratios | Assessment of signal-to-noise ratios to compare 1.5T and 3T fields. | At the time of exam |
| Comparative evaluation score for neurography and tractography methods |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Daniel Grucker, MD, PhD | Institut de Physique Biologique - Laboratoire iCube UMR 7357 UdS/CNRS Strasbourg | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Institut de Physique Biologique - Laboratoire iCube UMR 7357 UdS/CNRS | Strasbourg | 67000 | France |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 9488510 | Background | Porter GA, Soskolne CL, Yakimets WW, Newman SC. Surgeon-related factors and outcome in rectal cancer. Ann Surg. 1998 Feb;227(2):157-67. doi: 10.1097/00000658-199802000-00001. | |
| 12589666 | Background | Baader B, Herrmann M. Topography of the pelvic autonomic nervous system and its potential impact on surgical intervention in the pelvis. Clin Anat. 2003 Mar;16(2):119-30. doi: 10.1002/ca.10105. |
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Neurography and tractography methods will be scored on a five-point Lickert scale.
| Through study completion, an average of 1 year |
| Acquisition time for neurography and tractography methods | Required acquisition time for neurography and tractography methods will be compared if evaluation scores are equivalent. | At the time of exam |
| 19147343 | Background | Lange MM, Marijnen CA, Maas CP, Putter H, Rutten HJ, Stiggelbout AM, Meershoek-Klein Kranenbarg E, van de Velde CJ; Cooperative clinical investigators of the Dutch. Risk factors for sexual dysfunction after rectal cancer treatment. Eur J Cancer. 2009 Jun;45(9):1578-88. doi: 10.1016/j.ejca.2008.12.014. Epub 2009 Jan 13. |
| 22498730 | Background | Lim KS, Tan CH. Diffusion-weighted MRI of adult male pelvic cancers. Clin Radiol. 2012 Sep;67(9):899-908. doi: 10.1016/j.crad.2012.01.016. Epub 2012 Apr 11. |
| 19959077 | Background | Shihab OC, Heald RJ, Rullier E, Brown G, Holm T, Quirke P, Moran BJ. Defining the surgical planes on MRI improves surgery for cancer of the low rectum. Lancet Oncol. 2009 Dec;10(12):1207-11. doi: 10.1016/S1470-2045(09)70084-1. |
| 8095572 | Background | Filler AG, Howe FA, Hayes CE, Kliot M, Winn HR, Bell BA, Griffiths JR, Tsuruda JS. Magnetic resonance neurography. Lancet. 1993 Mar 13;341(8846):659-61. doi: 10.1016/0140-6736(93)90422-d. |
| 18796657 | Background | Takahara T, Hendrikse J, Yamashita T, Mali WP, Kwee TC, Imai Y, Luijten PR. Diffusion-weighted MR neurography of the brachial plexus: feasibility study. Radiology. 2008 Nov;249(2):653-60. doi: 10.1148/radiol.2492071826. Epub 2008 Sep 16. |
| 22705377 | Background | van der Jagt PK, Dik P, Froeling M, Kwee TC, Nievelstein RA, ten Haken B, Leemans A. Architectural configuration and microstructural properties of the sacral plexus: a diffusion tensor MRI and fiber tractography study. Neuroimage. 2012 Sep;62(3):1792-9. doi: 10.1016/j.neuroimage.2012.06.001. Epub 2012 Jun 13. |
| 24838739 | Background | Bertrand MM, Macri F, Mazars R, Droupy S, Beregi JP, Prudhomme M. MRI-based 3D pelvic autonomous innervation: a first step towards image-guided pelvic surgery. Eur Radiol. 2014 Aug;24(8):1989-97. doi: 10.1007/s00330-014-3211-0. Epub 2014 May 17. |
| 24812598 | Background | Soler L, Nicolau S, Pessaux P, Mutter D, Marescaux J. Real-time 3D image reconstruction guidance in liver resection surgery. Hepatobiliary Surg Nutr. 2014 Apr;3(2):73-81. doi: 10.3978/j.issn.2304-3881.2014.02.03. |
| 19001653 | Background | Chang KJ, Kamel IR, Macura KJ, Bluemke DA. 3.0-T MR imaging of the abdomen: comparison with 1.5 T. Radiographics. 2008 Nov-Dec;28(7):1983-98. doi: 10.1148/rg.287075154. |
| 29435745 | Result | Wijsmuller AR, Giraudeau C, Leroy J, Kleinrensink GJ, Rociu E, Romagnolo LG, Melani AGF, Agnus V, Diana M, Soler L, Dallemagne B, Marescaux J, Mutter D. A step towards stereotactic navigation during pelvic surgery: 3D nerve topography. Surg Endosc. 2018 Aug;32(8):3582-3591. doi: 10.1007/s00464-018-6086-3. Epub 2018 Feb 12. |