Automated cardiac sarcomere analysis from second harmonic generation images.
Automatic quantification of cardiac muscle properties in tissue sections might provide important information related to different types of diseases. Second harmonic generation (SHG) imaging provides a stain-free microscopy approach to image cardiac fibers that, combined with our methodology of the automated measurement of the ultrastructure of muscle fibers, computes a reliable set of quantitative image features (sarcomere length, A-band length, thick-thin interaction length, and fiber orientation). We evaluated the performance of our methodology in computer-generated muscle fibers modeling some artifacts that are present during the image acquisition. Then, we also evaluated it by comparing it to manual measurements in SHG images from cardiac tissue of fetal and adult rabbits. The results showed a good performance of our methodology at high signal-to-noise ratio of 20 dB. We conclude that our automated measurements enable reliable characterization of cardiac fiber tissues to systematically study cardiac tissue in a wide range of conditions.
University of Barcelona, BCNatal-Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Déu), IDIBAPS, and Centre for Biomedical Research on Rare Diseases (CIBER-ER), Barcelona 08028, SpainbUniversitat Pompeu.
Patricia
P
Garcia-Canadilla
University of Barcelona, BCNatal-Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Déu), IDIBAPS, and Centre for Biomedical Research on Rare Diseases (CIBER-ER), Barcelona 08028, Spain.
Anna
A
Gonzalez-Tendero
University of Barcelona, BCNatal-Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Déu), IDIBAPS, and Centre for Biomedical Research on Rare Diseases (CIBER-ER), Barcelona 08028, Spain.
Igor
I
Iruretagoyena
University of Barcelona, BCNatal-Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Déu), IDIBAPS, and Centre for Biomedical Research on Rare Diseases (CIBER-ER), Barcelona 08028, Spain.
Fatima
F
Crispi
University of Barcelona, BCNatal-Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Déu), IDIBAPS, and Centre for Biomedical Research on Rare Diseases (CIBER-ER), Barcelona 08028, Spain.
Iratxe
I
Torre
University of Barcelona, BCNatal-Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Déu), IDIBAPS, and Centre for Biomedical Research on Rare Diseases (CIBER-ER), Barcelona 08028, Spain.
Ivan
I
Amat-Roldan
Universitat Pompeu Fabra, PhySense, DTIC, Barcelona 08018, SpaincICREA, Barcelona 08010, Spain.
Bart H
BH
Bijnens
University of Barcelona, BCNatal-Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Déu), IDIBAPS, and Centre for Biomedical Research on Rare Diseases (CIBER-ER), Barcelona 08028, Spain.
Eduard
E
Gratacos
D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008853:Microscopy / Q000379:methods*; D009206:Myocardium / Q000166:cytology; D061088:Photoacoustic Techniques / Q000379:methods*; D011817:Rabbits; D012518:Sarcomeres / Q000737:chemistry*; D059629:Signal-To-Noise Ratio