Prognostic validation of a 17-segment score derived from a 20-segment score for myocardial perfusion spect interpretation View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2004-07

AUTHORS

Daniel S. Berman, Aiden Abidov, Xingping Kang, Sean W. Hayes, John D. Friedman, Maria G. Sciammarella, Ishac Cohen, James Gerlach, Parker B. Waechter, Guido Germano, Rory Hachamovitch

ABSTRACT

BackgroundRecently, a 17-segment model of the left ventricle has been recommended as an optimally weighted approach for interpreting myocardial perfusion single photon emission computed tomography (SPECT). Methods to convert databases from previous 20-to new 17-segment data and criteria for abnormality for the 17-segment scores are needed.Methods and ResultsInitially, for derivation of the conversion algorithm, 65 patients were studied (algorithm population) (pilot group, n = 28; validation group, n = 37). Three conversion algorithms were derived: algorithm 1, which used mid, distal, and apical scores; algorithm 2, which used distal and apical scores alone; and algorithm 3, which used maximal scores of the distal septal, lateral, and apical segments in the 20-segment model for 3 corresponding segments of the 17-segment model. The prognosis population comprised 16,020 consecutive patients (mean age, 65 ± 12 years; 41% women) who had exercise or vasodilator stress technetium 99m sestamibi myocardial perfusion SPECT and were followed up for 2.1 ± 0.8 years. In this population, 17-segment scores were derived from 20-segment scores by use of algorithm 2, which demonstrated the best agreement with expert 17-segment reading in the algorithm population. The prognostic value of the 20- and 17-segment scores was compared by converting the respective summed scores into percent myocardium abnormal. Conversion algorithm 2 was found to be highly concordant with expert visual analysis by the 17-segment model (r = 0.982; k = 0.866) in the algorithm population. In the prognosis population, 456 cardiac deaths occurred during follow-up. When the conversion algorithm was applied, extent and severity of perfusion defects were nearly identical by 20- and derived 17-segment scores. The receiver operating characteristic curve areas by 20- and 17-segment perfusion scores were identical for predicting cardiac death (both 0.77 ± 0.02, P = not significant). The optimal prognostic cutoff value for either 20- or derived 17-segment models was confirmed to be 5% myocardium abnormal, corresponding to a summed stress score greater than 3. Of note, the 17-segment model demonstrated a trend toward fewer mildly abnormal scans and more normal and severely abnormal scans.ConclusionAn algorithm for conversion of 20-segment perfusion scores to 17-segment scores has been developed that is highly concordant with expert visual analysis by the 17-segment model and provides nearly identical prognostic information. This conversion model may provide a mechanism for comparison of studies analyzed by the 17-segment system with previous studies analyzed by the 20-segment approach. More... »

PAGES

414-423

Identifiers

URI

http://scigraph.springernature.com/pub.10.1016/j.nuclcard.2004.03.033

DOI

http://dx.doi.org/10.1016/j.nuclcard.2004.03.033

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1034051507

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/15295410


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26 schema:description BackgroundRecently, a 17-segment model of the left ventricle has been recommended as an optimally weighted approach for interpreting myocardial perfusion single photon emission computed tomography (SPECT). Methods to convert databases from previous 20-to new 17-segment data and criteria for abnormality for the 17-segment scores are needed.Methods and ResultsInitially, for derivation of the conversion algorithm, 65 patients were studied (algorithm population) (pilot group, n = 28; validation group, n = 37). Three conversion algorithms were derived: algorithm 1, which used mid, distal, and apical scores; algorithm 2, which used distal and apical scores alone; and algorithm 3, which used maximal scores of the distal septal, lateral, and apical segments in the 20-segment model for 3 corresponding segments of the 17-segment model. The prognosis population comprised 16,020 consecutive patients (mean age, 65 ± 12 years; 41% women) who had exercise or vasodilator stress technetium 99m sestamibi myocardial perfusion SPECT and were followed up for 2.1 ± 0.8 years. In this population, 17-segment scores were derived from 20-segment scores by use of algorithm 2, which demonstrated the best agreement with expert 17-segment reading in the algorithm population. The prognostic value of the 20- and 17-segment scores was compared by converting the respective summed scores into percent myocardium abnormal. Conversion algorithm 2 was found to be highly concordant with expert visual analysis by the 17-segment model (r = 0.982; k = 0.866) in the algorithm population. In the prognosis population, 456 cardiac deaths occurred during follow-up. When the conversion algorithm was applied, extent and severity of perfusion defects were nearly identical by 20- and derived 17-segment scores. The receiver operating characteristic curve areas by 20- and 17-segment perfusion scores were identical for predicting cardiac death (both 0.77 ± 0.02, P = not significant). The optimal prognostic cutoff value for either 20- or derived 17-segment models was confirmed to be 5% myocardium abnormal, corresponding to a summed stress score greater than 3. Of note, the 17-segment model demonstrated a trend toward fewer mildly abnormal scans and more normal and severely abnormal scans.ConclusionAn algorithm for conversion of 20-segment perfusion scores to 17-segment scores has been developed that is highly concordant with expert visual analysis by the 17-segment model and provides nearly identical prognostic information. This conversion model may provide a mechanism for comparison of studies analyzed by the 17-segment system with previous studies analyzed by the 20-segment approach.
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33 schema:keywords Algorithm 1
34 Algorithm 2
35 BackgroundRecently
36 ConclusionAn algorithm
37 Conversion algorithm 2
38 ResultsInitially
39 SPECT
40 SPECT interpretation
41 abnormal scans
42 abnormalities
43 agreement
44 algorithm
45 algorithm 3
46 algorithm population
47 analysis
48 apical scores
49 apical segments
50 approach
51 area
52 cardiac death
53 characteristic curve area
54 comparison
55 comparison of studies
56 consecutive patients
57 conversion
58 conversion algorithm
59 conversion model
60 corresponding segments
61 criteria
62 curve area
63 cutoff value
64 data
65 database
66 death
67 defects
68 derivation
69 emission
70 exercise
71 expert 17-segment reading
72 expert visual analysis
73 extent
74 good agreement
75 identical prognostic information
76 information
77 interpretation
78 left ventricle
79 maximal score
80 mechanism
81 method
82 model
83 myocardial perfusion SPECT
84 myocardial perfusion single photon emission
85 myocardial perfusion spect interpretation
86 myocardium
87 note
88 optimal prognostic cutoff value
89 patients
90 percent myocardium
91 perfusion SPECT
92 perfusion defects
93 perfusion score
94 perfusion single photon emission
95 perfusion spect interpretation
96 photon emission
97 population
98 previous studies
99 prognosis population
100 prognostic cutoff value
101 prognostic information
102 prognostic validation
103 prognostic value
104 reading
105 receiver
106 scans
107 scores
108 segments
109 sestamibi myocardial perfusion SPECT
110 severity
111 single photon emission
112 stress scores
113 stress technetium
114 study
115 summed stress score
116 system
117 technetium
118 tomography
119 trends
120 use
121 validation
122 values
123 vasodilator stress technetium
124 ventricle
125 visual analysis
126 years
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