RESUMEN
INTRODUCTION: To characterize venture capital (VC) investments in urology in the past decade that represent promising innovations in early-stage companies. MATERIALS AND METHODS: A retrospective analysis of deals made between VC investors and urologic companies from January 1, 2011, through June 28, 2021, was conducted by using a financial database (PitchBook Platform, PitchBook Data Inc). Data on urologic company and investor names; company information and funding categories (surgical device, therapeutic device, drug discovery/pharmaceutical, and health care technology companies); and deal sizes (in US dollars) and dates were abstracted and aggregated. Descriptive and linear regression analyses were conducted. RESULTS: Urology-related VC funding fluctuated from 2011 through mid-2021, but no substantial change was observed in funding over time. In total, 191 distinct deals were made involving urologic companies, totaling $1.1 billion. The four largest funding categories together accounted for $848 million and comprised therapeutic devices ($373 million), surgical devices ($187 million), drug discovery/pharmaceuticals ($185 million), and health care technology ($102 million). At least $450 million (41% of total investments) was invested in companies developing minimally invasive surgical devices. CONCLUSIONS: Urologic VC investments did not increase in the past decade and were allocated more toward devices than pharmaceuticals or health care technology. Given relative patterns within urology, VC investments may shift toward health care technology and away from pharmaceuticals but remain stable for devices. Further investments in promising technologies may help urologists more effectively manage urologic disease while optimizing outcomes.
Asunto(s)
Urología , Humanos , Estudios Retrospectivos , Inversiones en Salud , Financiación del Capital , Preparaciones FarmacéuticasRESUMEN
OBJECTIVES: The objectives of this exploratory study were to investigate the feasibility of multidimensional diffusion magnetic resonance imaging (MddMRI) in assessing diffusion heterogeneity at both a macroscopic and microscopic level in prostate cancer (PCa). MATERIALS AND METHODS: Informed consent was obtained from 46 subjects who underwent 3.0-T prostate multiparametric MRI, complemented with a prototype spin echo-based MddMRI sequence in this institutional review board-approved study. Prostate cancer tumors and comparative normal tissue from each patient were contoured on both apparent diffusion coefficient and MddMRI-derived mean diffusivity (MD) maps (from which microscopic diffusion heterogeneity [MKi] and microscopic diffusion anisotropy were derived) using 3D Slicer. The discriminative ability of MddMRI-derived parameters to differentiate PCa from normal tissue was determined using the Friedman test. To determine if tumor diffusion heterogeneity is similar on macroscopic and microscopic scales, the linear association between SD of MD and mean MKi was estimated using robust regression (bisquare weighting). Hypothesis testing was 2 tailed; P values less than 0.05 were considered statistically significant. RESULTS: All MddMRI-derived parameters could distinguish tumor from normal tissue in the fixed-effects analysis (P < 0.0001). Tumor MKi was higher (P < 0.05) compared with normal tissue (median, 0.40; interquartile range, 0.29-0.52 vs 0.20-0.18; 0.25), as was tumor microscopic diffusion anisotropy (0.55; 0.36-0.81 vs 0.20-0.15; 0.28). The MKi could not be predicted (no significant association) by SD of MD. There was a significant correlation between tumor volume and SD of MD (R2 = 0.50, slope = 0.008 µm2/ms per millimeter, P < 0.001) but not between tumor volume and MKi. CONCLUSIONS: This explorative study demonstrates that MddMRI provides novel information on MKi and microscopic anisotropy, which differ from measures at the macroscopic level. MddMRI has the potential to characterize tumor tissue heterogeneity at different spatial scales.