This paper introduces DysArinVox, a new pathological speech corpus in Chinese. It included 173 participants from 27 healthy individuals and 146 voice disorders, whose various types and severities of vocal impairments as diagnosed by speech pathology experts via auditory perceptual evaluations and laryngoscopic imagery. DysArinVox is designed to provide a high-quality Chinese resource for AI-driven diagnostics and prognostics. To ensure the efficiency of corpus collection, we meticulously crafted recording scripts represent Mandarin phonetically, ensuring comprehensive syllable representation with minimal lexical complexity. Additionally, incorporating laryngoscopic images of patients into the dataset offers extra visual information, facilitating the development of advanced diagnostic frameworks. To our knowledge, this database represents the most comprehensive corpus of Chinese pathological speech to date.