Contributions
Abstract: P1120
Type: Poster Sessions
Abstract Category: Pathology and pathogenesis of MS - MRI and PET
Introduction: Mean upper cervical cord cross-sectional area (UCCA) and upper cervical cord atrophy have the potential to become important biomarkers in MS. In this work, we assess the feasibility of a fully automated measurement approach of UCCA and atrophy for group analyses and patient-individual diagnosis support.
Methods: Cranial 3D T1-weighted magnetic resonance (MR) images (1.25x1.25x1.5mm³ resolution) of 33 RRMS patients with regular follow-up visits over 3 years and 12 test-retest measurements of normal controls (NC; for each measurement, test and retest within 2 days) were evaluated. Data was acquired within the non-interventional INSPIRATION-MRI study, which included quality-controlled MR imaging. Images were evaluated using a previously described fully automated software. The method for automatic UCCA measurement has been integrated into a software for clinical trial support and patient-individual evaluations including image upload, pseudonymisation, automatic image identification, quality assessment, and atrophy calculation from follow-up data. It allowed to analyze the segments C1-C2 and C3 separately and combined (C1-C3). Development has been supported by the German Ministry of Education and Research (BMBF; project “MS-ATROPHIE”).
Results: The mean value of percentage change of UCCA between test and retest in NCs was 1.7% for C1-C3 (1.4% for C1-C2 alone). The patient cohort UCCA for C1-C3 was 0.71 cm², ±0.10 cm² standard deviation (0.75±0.09 for C1-C2). NCs had a mean UCCA of 0.83±0.11 cm² (0.81±0.22). Patients showed a mean annual UCCA decline of 0.5% (0.9%). In 11 of 98 patient evaluations, C3 segment was not fully covered in the cranial image, and only C1-C2 was evaluated.
Conclusion: The variability between test and retest is relevant for patient-individual analyses in clinical routine because it includes the influence of different head and neck positioning between two separate examinations. These variations are lower in C1-C2 alone as compared to C1-C3. With the variability of 1.4% (C1-C2), the method allows to discriminate between patients with RRMS and healthy subjects (difference of group means >10%) and is promising to assess atrophy, but not sufficient within 1-year follow-up (annual RRMS atrophy rate < 1%). The numbers of UCCA and atrophy for RRMS patients and NCs match very well with recent results of other groups using semi-automated methods. The software can therefore be used straightforward for group analyses and cohort studies.
Disclosure: J. Gregori is Managing Director of mediri GmbH, Heidelberg, Germany.
C. Cornelissen is a payed employee of the Novartis Pharma GmbH, Nuremberg, Germany.
S. Hoffmann: nothing to disclose
M. Treiber: nothing to disclose
S. Randoll: nothing to disclose
S. Heldmann: nothing to disclose
J. Klein: nothing to disclose
R. Opfer: nothing to disclose
L. Spies: nothing to disclose
A. Gass has received honoraria for lecturing, travel expenses for attending meetings, and financial support for research from Novartis, Biogen, Merck Serono, Sanofi-Genzyme, Roche.
T. Ziemssen has received consulting fees and speaker honoraria from Bayer, Biogen, Novartis, Genzyme, Teva, Merck, MSD, Roche, Synthon.
H. Kitzler served on scientific advisory boards for Novartis, has received speaker honoraria from Novartis, Biogen Idec and TEVA Pharmaceutical Industries Ltd, and has research agreements with Novartis Pharma GmbH and the Siemens AG.
F. Weiler: nothing to disclose
Abstract: P1120
Type: Poster Sessions
Abstract Category: Pathology and pathogenesis of MS - MRI and PET
Introduction: Mean upper cervical cord cross-sectional area (UCCA) and upper cervical cord atrophy have the potential to become important biomarkers in MS. In this work, we assess the feasibility of a fully automated measurement approach of UCCA and atrophy for group analyses and patient-individual diagnosis support.
Methods: Cranial 3D T1-weighted magnetic resonance (MR) images (1.25x1.25x1.5mm³ resolution) of 33 RRMS patients with regular follow-up visits over 3 years and 12 test-retest measurements of normal controls (NC; for each measurement, test and retest within 2 days) were evaluated. Data was acquired within the non-interventional INSPIRATION-MRI study, which included quality-controlled MR imaging. Images were evaluated using a previously described fully automated software. The method for automatic UCCA measurement has been integrated into a software for clinical trial support and patient-individual evaluations including image upload, pseudonymisation, automatic image identification, quality assessment, and atrophy calculation from follow-up data. It allowed to analyze the segments C1-C2 and C3 separately and combined (C1-C3). Development has been supported by the German Ministry of Education and Research (BMBF; project “MS-ATROPHIE”).
Results: The mean value of percentage change of UCCA between test and retest in NCs was 1.7% for C1-C3 (1.4% for C1-C2 alone). The patient cohort UCCA for C1-C3 was 0.71 cm², ±0.10 cm² standard deviation (0.75±0.09 for C1-C2). NCs had a mean UCCA of 0.83±0.11 cm² (0.81±0.22). Patients showed a mean annual UCCA decline of 0.5% (0.9%). In 11 of 98 patient evaluations, C3 segment was not fully covered in the cranial image, and only C1-C2 was evaluated.
Conclusion: The variability between test and retest is relevant for patient-individual analyses in clinical routine because it includes the influence of different head and neck positioning between two separate examinations. These variations are lower in C1-C2 alone as compared to C1-C3. With the variability of 1.4% (C1-C2), the method allows to discriminate between patients with RRMS and healthy subjects (difference of group means >10%) and is promising to assess atrophy, but not sufficient within 1-year follow-up (annual RRMS atrophy rate < 1%). The numbers of UCCA and atrophy for RRMS patients and NCs match very well with recent results of other groups using semi-automated methods. The software can therefore be used straightforward for group analyses and cohort studies.
Disclosure: J. Gregori is Managing Director of mediri GmbH, Heidelberg, Germany.
C. Cornelissen is a payed employee of the Novartis Pharma GmbH, Nuremberg, Germany.
S. Hoffmann: nothing to disclose
M. Treiber: nothing to disclose
S. Randoll: nothing to disclose
S. Heldmann: nothing to disclose
J. Klein: nothing to disclose
R. Opfer: nothing to disclose
L. Spies: nothing to disclose
A. Gass has received honoraria for lecturing, travel expenses for attending meetings, and financial support for research from Novartis, Biogen, Merck Serono, Sanofi-Genzyme, Roche.
T. Ziemssen has received consulting fees and speaker honoraria from Bayer, Biogen, Novartis, Genzyme, Teva, Merck, MSD, Roche, Synthon.
H. Kitzler served on scientific advisory boards for Novartis, has received speaker honoraria from Novartis, Biogen Idec and TEVA Pharmaceutical Industries Ltd, and has research agreements with Novartis Pharma GmbH and the Siemens AG.
F. Weiler: nothing to disclose