Scholarlink

Background <p>Anti-Yo paraneoplastic cerebellar degeneration (PCD) is a rare autoimmune disorder linked to ovarian and breast cancers. Neurological symptoms often precede cancer diagnosis, yet conventional imaging techniques may fail to detect early cerebellar changes. This study quantitatively assessed cerebellar atrophy and network alterations in anti-Yo PCD patients compared to healthy controls and patients with spinocerebellar ataxia type 1 (SCA1).</p> Methods <p>We analyzed structural MRI data from 11 antiYo PCD patients, 17 healthy controls, and 17 SCA1 patients. Cerebellar lobular segmentation and cortical thickness measurements were conducted. Structural covariance networks were built using inter-lobular Pearson correlation coefficients (threshold |<i>r</i>| &gt; 0.5), with graph theory metrics assessing connectivity. Univariate and age-adjusted multivariate analyses evaluated group differences, and machine learning assessed the discriminative power of regional morphometric measures.</p> Results <p>AntiYo PCD patients showed pronounced anterior cortical thinning, while SCA1 atrophy was milder and more posterior. Two PCD subtypes emerged: one with severe atrophy, another with nearnormal thickness. Network analysis revealed increased node strength and clustering coefficients, but reduced betweenness centrality in PCD, suggesting altered network hierarchy and widespread clustering that may reflect pathological reorganization. In cross-validated analysis, regional cerebellar features distinguished PCD, SCA1, and controls with promising AUC values.</p> Conclusions <p>Anti-Yo PCD is characterized by anterior cerebellar vulnerability and network reorganization distinct from SCA1. These morphometric and connectivity markers are candidate imaging biomarkers for early diagnosis and subgroup stratification in paraneoplastic cerebellar degeneration.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Spatial analysis of paraneoplastic cerebellar degeneration in ovarian cancer with anti-Yo syndrome and SCA1

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月27日

查看全文
  • Tamara Künzle,
  • Lucas Rincon de la Rosa,
  • Clément Vialatte de Pémille,
  • Alice Leprince-Laurenge,
  • Alberto Picca,
  • Giulia Coarelli,
  • Delphine Leclercq,
  • Alexandra Dürr,
  • Dimitri Psimaras,
  • Agusti Alentorn

摘要

Background

Anti-Yo paraneoplastic cerebellar degeneration (PCD) is a rare autoimmune disorder linked to ovarian and breast cancers. Neurological symptoms often precede cancer diagnosis, yet conventional imaging techniques may fail to detect early cerebellar changes. This study quantitatively assessed cerebellar atrophy and network alterations in anti-Yo PCD patients compared to healthy controls and patients with spinocerebellar ataxia type 1 (SCA1).

Methods

We analyzed structural MRI data from 11 antiYo PCD patients, 17 healthy controls, and 17 SCA1 patients. Cerebellar lobular segmentation and cortical thickness measurements were conducted. Structural covariance networks were built using inter-lobular Pearson correlation coefficients (threshold |r| > 0.5), with graph theory metrics assessing connectivity. Univariate and age-adjusted multivariate analyses evaluated group differences, and machine learning assessed the discriminative power of regional morphometric measures.

Results

AntiYo PCD patients showed pronounced anterior cortical thinning, while SCA1 atrophy was milder and more posterior. Two PCD subtypes emerged: one with severe atrophy, another with nearnormal thickness. Network analysis revealed increased node strength and clustering coefficients, but reduced betweenness centrality in PCD, suggesting altered network hierarchy and widespread clustering that may reflect pathological reorganization. In cross-validated analysis, regional cerebellar features distinguished PCD, SCA1, and controls with promising AUC values.

Conclusions

Anti-Yo PCD is characterized by anterior cerebellar vulnerability and network reorganization distinct from SCA1. These morphometric and connectivity markers are candidate imaging biomarkers for early diagnosis and subgroup stratification in paraneoplastic cerebellar degeneration.