<p>The golden ratio (<InlineEquation ID="IEq1"><EquationSource Format="TEX">\(\varphi \approx 1.618\)</EquationSource></InlineEquation>) exhibits unique autosimilarity properties that appear throughout biological systems, including human physiology and neural organization. The Tree Drawing Test (TDT), a simple cognitive assessment tool that mainly implies visuospatial, praxic and executive functions, may capture <InlineEquation ID="IEq2"><EquationSource Format="TEX">\(\varphi\)</EquationSource></InlineEquation>-based organizational principles that become disrupted in neurodegenerative conditions. This study examined the relationship between golden ratio proportions and cognitive impairment in tree drawings through quantitative analysis of a large cohort of cognitively impaired patients. We evaluated 613 Alzheimer’s disease (AD) patients, 328 mild cognitive impairment (MCI) patients, and 438 healthy controls who completed the TDT. Five novel golden ratio-based deviation indices were developed to quantify proportional relationships between trunk and crown dimensions; among these, the trunk-based index <InlineEquation ID="IEq3"><EquationSource Format="TEX">\(H/\varphi - T\)</EquationSource></InlineEquation>showed the most consistent group separation (Distance-to-Diameter Ratio <InlineEquation ID="IEq4"><EquationSource Format="TEX">\(=0{.}546\)</EquationSource></InlineEquation>; Fisher Ratio <InlineEquation ID="IEq5"><EquationSource Format="TEX">\(=0{.}561\)</EquationSource></InlineEquation>), with all three pairwise diagnostic comparisons reaching <InlineEquation ID="IEq6"><EquationSource Format="TEX">\(p&lt;0{.}0001\)</EquationSource></InlineEquation> (Mann–Whitney <i>U</i>, Bonferroni-corrected) in the full sample and across sex and education strata. Within a multinomial logistic regression framework with stratified 5-fold cross-validation, <InlineEquation ID="IEq7"><EquationSource Format="TEX">\(H/\varphi - T\)</EquationSource></InlineEquation>retained independent discriminative value after adjustment for age, education, and the established Space Occupation (SO) index, reaching a macro-averaged AUC of 0.834 (AD vs. rest: 0.855, 95% CI <InlineEquation ID="IEq8"><EquationSource Format="TEX">\([0{.}835,\,0{.}873]\)</EquationSource></InlineEquation>; CNTRL vs. rest: 0.911, 95% CI <InlineEquation ID="IEq9"><EquationSource Format="TEX">\([0{.}894,\,0{.}927]\)</EquationSource></InlineEquation>; MCI vs. rest: 0.736); the Likelihood Ratio Test confirmed that <InlineEquation ID="IEq10"><EquationSource Format="TEX">\(H/\varphi - T\)</EquationSource></InlineEquation>contributes information not captured by SO, age, and education combined (<InlineEquation ID="IEq11"><EquationSource Format="TEX">\(\Lambda =121{.}91\)</EquationSource></InlineEquation>, <InlineEquation ID="IEq12"><EquationSource Format="TEX">\(p&lt;0{.}0001\)</EquationSource></InlineEquation>), and convergent results under two independent matched-subgroup strategies indicated that age and education differences do not explain this signal. Pre-specified operational cut-offs derived from the cohort yielded clinically interpretable sensitivity/specificity trade-offs, with AUC <InlineEquation ID="IEq13"><EquationSource Format="TEX">\(= 0.911\)</EquationSource></InlineEquation> [0.894, 0.927] for healthy-control identification using the full multivariate model. As a secondary descriptive observation, group means of <InlineEquation ID="IEq14"><EquationSource Format="TEX">\(H/\varphi - T\)</EquationSource></InlineEquation>approximated the Fibonacci values <i>F</i>(5), <i>F</i>(7), <i>F</i>(9); a permutation-based null model (B <InlineEquation ID="IEq15"><EquationSource Format="TEX">\(=10{,}000\)</EquationSource></InlineEquation>, <InlineEquation ID="IEq16"><EquationSource Format="TEX">\(\hat{p}&lt;0{.}0001\)</EquationSource></InlineEquation>) and a Fibonacci-vs-Lucas specificity comparison (100% vs. 0% confidence-interval containment) indicated that this alignment is unlikely to arise by chance and is specific to <InlineEquation ID="IEq17"><EquationSource Format="TEX">\(\varphi\)</EquationSource></InlineEquation>-convergent sequences, although the algebraic link between <InlineEquation ID="IEq18"><EquationSource Format="TEX">\(H/\varphi - T\)</EquationSource></InlineEquation>and <InlineEquation ID="IEq19"><EquationSource Format="TEX">\(\varphi\)</EquationSource></InlineEquation> implies that this finding should be regarded as a starting point for future studies rather than as proof of a biological mechanism. Within these limitations, golden-ratio-based TDT measures provide a quantitative complement, not a replacement, to traditional TDT indices for cognitive impairment assessment and require confirmation in independent multi-centre samples before clinical adoption.</p>

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Quantifying golden-ratio deviations in the tree drawing test to identify patients with Alzheimer’s disease

  • Michelangelo Stanzani Maserati,
  • Fabiana Zama

摘要

The golden ratio (\(\varphi \approx 1.618\)) exhibits unique autosimilarity properties that appear throughout biological systems, including human physiology and neural organization. The Tree Drawing Test (TDT), a simple cognitive assessment tool that mainly implies visuospatial, praxic and executive functions, may capture \(\varphi\)-based organizational principles that become disrupted in neurodegenerative conditions. This study examined the relationship between golden ratio proportions and cognitive impairment in tree drawings through quantitative analysis of a large cohort of cognitively impaired patients. We evaluated 613 Alzheimer’s disease (AD) patients, 328 mild cognitive impairment (MCI) patients, and 438 healthy controls who completed the TDT. Five novel golden ratio-based deviation indices were developed to quantify proportional relationships between trunk and crown dimensions; among these, the trunk-based index \(H/\varphi - T\)showed the most consistent group separation (Distance-to-Diameter Ratio \(=0{.}546\); Fisher Ratio \(=0{.}561\)), with all three pairwise diagnostic comparisons reaching \(p<0{.}0001\) (Mann–Whitney U, Bonferroni-corrected) in the full sample and across sex and education strata. Within a multinomial logistic regression framework with stratified 5-fold cross-validation, \(H/\varphi - T\)retained independent discriminative value after adjustment for age, education, and the established Space Occupation (SO) index, reaching a macro-averaged AUC of 0.834 (AD vs. rest: 0.855, 95% CI \([0{.}835,\,0{.}873]\); CNTRL vs. rest: 0.911, 95% CI \([0{.}894,\,0{.}927]\); MCI vs. rest: 0.736); the Likelihood Ratio Test confirmed that \(H/\varphi - T\)contributes information not captured by SO, age, and education combined (\(\Lambda =121{.}91\), \(p<0{.}0001\)), and convergent results under two independent matched-subgroup strategies indicated that age and education differences do not explain this signal. Pre-specified operational cut-offs derived from the cohort yielded clinically interpretable sensitivity/specificity trade-offs, with AUC \(= 0.911\) [0.894, 0.927] for healthy-control identification using the full multivariate model. As a secondary descriptive observation, group means of \(H/\varphi - T\)approximated the Fibonacci values F(5), F(7), F(9); a permutation-based null model (B \(=10{,}000\), \(\hat{p}<0{.}0001\)) and a Fibonacci-vs-Lucas specificity comparison (100% vs. 0% confidence-interval containment) indicated that this alignment is unlikely to arise by chance and is specific to \(\varphi\)-convergent sequences, although the algebraic link between \(H/\varphi - T\)and \(\varphi\) implies that this finding should be regarded as a starting point for future studies rather than as proof of a biological mechanism. Within these limitations, golden-ratio-based TDT measures provide a quantitative complement, not a replacement, to traditional TDT indices for cognitive impairment assessment and require confirmation in independent multi-centre samples before clinical adoption.