Effect of the identification group size and image resolution on the diagnostic performance of metabolic Alzheimer's disease-related pattern

被引:0
|
作者
Stokelj, Eva [1 ]
Tomse, Petra [2 ]
Tomanic, Tadej [1 ]
Dhawan, Vijay [3 ]
Eidelberg, David [3 ]
Trost, Maja [2 ,4 ,5 ]
Simoncic, Urban [1 ,6 ]
机构
[1] Univ Ljubljana, Fac Math & Phys, Jadranska Ulica 19, Ljubljana 1000, Slovenia
[2] Univ Med Ctr Ljubljana, Dept Nucl Med, Zaloska Cesta 7, Ljubljana 1000, Slovenia
[3] Feinstein Inst Med Res, Ctr Neurosci, 350 Community Dr, Manhasset, NY 11030 USA
[4] Univ Med Ctr Ljubljana, Dept Neurol, Zaloska Cesta 2, Ljubljana 1000, Slovenia
[5] Univ Ljubljana, Fac Med, Vrazov Trg 2, Ljubljana 1000, Slovenia
[6] Jozef Stefan Inst, Jamova Cesta 39, Ljubljana 1000, Slovenia
关键词
Alzheimer's disease; Metabolic brain pattern; 2-[F-18]FDG-PET; Image resolution; Cohort size; Network analysis; COGNITIVE IMPAIRMENT; BRAIN NETWORK; DEMENTIA;
D O I
10.1186/s13550-023-01001-5
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
BackgroundAlzheimer's disease-related pattern (ADRP) is a metabolic brain biomarker of Alzheimer's disease (AD). While ADRP is being introduced into research, the effect of the size of the identification cohort and the effect of the resolution of identification and validation images on ADRP's performance need to be clarified.Methods240 2-[F-18]fluoro-2-deoxy-d-glucose positron emission tomography images [120 AD/120 cognitive normals (CN)] were selected from the Alzheimer's disease neuroimaging initiative database. A total of 200 images (100 AD/100 CN) were used to identify different versions of ADRP using a scaled subprofile model/principal component analysis. For this purpose, five identification groups were randomly selected 25 times. The identification groups differed in the number of images (20 AD/20 CN, 30 AD/30 CN, 40 AD/40 CN, 60 AD/60 CN, and 80 AD/80 CN) and image resolutions (6, 8, 10, 12, 15 and 20 mm). A total of 750 ADRPs were identified and validated through the area under the curve (AUC) values on the remaining 20 AD/20 CN with six different image resolutions.ResultsADRP's performance for the differentiation between AD patients and CN demonstrated only a marginal average AUC increase, when the number of subjects in the identification group increases (AUC increase for about 0.03 from 20 AD/20 CN to 80 AD/80 CN). However, the average of the lowest five AUC values increased with the increasing number of participants (AUC increase for about 0.07 from 20 AD/20 CN to 30 AD/30 CN and for an additional 0.02 from 30 AD/30 CN to 40 AD/40 CN). The resolution of the identification images affects ADRP's diagnostic performance only marginally in the range from 8 to 15 mm. ADRP's performance stayed optimal even when applied to validation images of resolution differing from the identification images.ConclusionsWhile small (20 AD/20 CN images) identification cohorts may be adequate in a favorable selection of cases, larger cohorts (at least 30 AD/30 CN images) shall be preferred to overcome possible/random biological differences and improve ADRP's diagnostic performance. ADRP's performance stays stable even when applied to the validation images with a resolution different than the resolution of the identification ones.
引用
收藏
页数:19
相关论文
共 50 条
  • [1] Effect of the identification group size and image resolution on the diagnostic performance of metabolic Alzheimer’s disease-related pattern
    Eva Štokelj
    Petra Tomše
    Tadej Tomanič
    Vijay Dhawan
    David Eidelberg
    Maja Trošt
    Urban Simončič
    [J]. EJNMMI Research, 13
  • [2] The Alzheimer's Disease-Related Glucose Metabolic Brain Pattern
    Teune, Laura K.
    Strijkert, Fijanne
    Renken, Remco J.
    Izaks, Gerbrand J.
    de Vries, Jeroen J.
    Segbers, Marcel
    Roerdink, Jos B. T. M.
    Dierckx, Rudi A. J. O.
    Leenders, Klaus L.
    [J]. CURRENT ALZHEIMER RESEARCH, 2014, 11 (08) : 725 - 732
  • [3] Identification and validation of Alzheimer's disease-related metabolic brain pattern in biomarker confirmed Alzheimer's dementia patients
    Perovnik, Matej
    Tomse, Petra
    Jamsek, Jan
    Emersic, Andreja
    Tang, Chris
    Eidelberg, David
    Trost, Maja
    [J]. SCIENTIFIC REPORTS, 2022, 12 (01)
  • [4] Identification and validation of Alzheimer’s disease-related metabolic brain pattern in biomarker confirmed Alzheimer’s dementia patients
    Matej Perovnik
    Petra Tomše
    Jan Jamšek
    Andreja Emeršič
    Chris Tang
    David Eidelberg
    Maja Trošt
    [J]. Scientific Reports, 12
  • [5] Alzheimer's Disease-Related Metabolic Pattern in Diverse Forms of Neurodegenerative Diseases
    Lau, Angus
    Beheshti, Iman
    Modirrousta, Mandana
    Kolesar, Tiffany A.
    Goertzen, Andrew L.
    Ko, Ji Hyun
    [J]. DIAGNOSTICS, 2021, 11 (11)
  • [6] Identification of diagnostic biomarkers in Alzheimer's disease using metabolic-pathway related genes
    Al-Bzour, Nour
    Ahmed, Yaman
    Al-Khalili, Anas
    Hamza, Ammar
    Ibrahim, Ruaa
    Al-Bzour, Ayah
    [J]. NEUROLOGY, 2023, 100 (17)
  • [7] Identification of Alzheimer's Disease-Related Genes Based on Data Integration Method
    Hu, Yang
    Zhao, Tianyi
    Zang, Tianyi
    Zhang, Ying
    Cheng, Liang
    [J]. FRONTIERS IN GENETICS, 2019, 9
  • [8] Diagnostic value of Alzheimer's disease-related individual structural volume measurements using IBASPM
    Han, Su-Hyun
    Lee, Min-A
    An, Seong Soo
    Ahn, Suk-Won
    Youn, Young Chul
    Park, Kwang-Yeol
    [J]. JOURNAL OF CLINICAL NEUROSCIENCE, 2014, 21 (12) : 2165 - 2169
  • [9] Identification of age- and disease-related alterations in circulating miRNAs in a mouse model of Alzheimer's disease
    Garza-Manero, Sylvia
    Arias, Clorinda
    Bermudez-Rattoni, Federico
    Vaca, Luis
    Zapeda, Angelica
    [J]. FRONTIERS IN CELLULAR NEUROSCIENCE, 2015, 9
  • [10] Identification of Autophagy-Related Biomarkers and Diagnostic Model in Alzheimer's Disease
    Xu, Wei
    Su, Xi
    Qin, Jing
    Jin, Ye
    Zhang, Ning
    Huang, Shasha
    [J]. GENES, 2024, 15 (08)