This study aimed to investigate the feasibility of integrating image features computed from both spatial and frequency domain to better describe the tumor heterogeneity for precise prediction of tumor response to postsurgical chemotherapy in patients with advanced-stage ovarian cancer. A computer-aided scheme was applied to first compute 133 features from five categories namely, shape and density, fast Fourier transform, discrete cosine transform (DCT), wavelet, and gray level difference method. An optimal feature cluster was then determined by the scheme using the particle swarm optimization algorithm aiming to achieve an enhanced discrimination power that was unattainable with the single features. The scheme was tested using a balanced dataset (responders and non-responders defined using 6 month PFS) retrospectively collected from 120 ovarian cancer patients. By evaluating the performance of the individual features among the five categories, the DCT features achieved the highest predicting accuracy than the features in other groups. By comparison, a quantitative image marker generated from the optimal feature cluster yielded the area under ROC curve (AUC) of 0.86, while the top performing single feature only had an AUC of 0.74. Furthermore, it was observed that the features computed from the frequency domain were as important as those computed from the spatial domain. In conclusion, this study demonstrates the potential of our proposed new quantitative image marker fused with the features computed from both spatial and frequency domain for a reliable prediction of tumor response to postsurgical chemotherapy.

Objective: The invisibility of domestic oocyte nucleus in bright field currently forces operators to blindly aspirate nucleus out in oocyte enucleation, usually causing large cytoplasm losses and poor developmental competences of cloned embryos. Although fluorescent labeling of nucleus allows for nucleus localization, the involved photobleaching problems and barriers to the execution of enucleation process limit its online-application in oocyte enucleation. This paper reports a novel label-free oocyte enucleation method for precise removal of the nucleus with less cytoplasm loss. Methods: The relative positions between the injection pipette and nucleus for complete removal of nucleus with less cytoplasm loss were determined through a finite element modeling of nucleus aspiration. To position injection pipette to the above positions relative to nucleus, the appropriate oocyte orientation and trajectory of injection pipette inside oocyte were derived according to the offline-calibrated 3-D distribution of nucleus and the simulated dynamic drift of nucleus that occurs as injection pipette is maneuvered inside oocyte. Finally, a robotic label-free precise enucleation procedure was established. Results: The experimental results on more than 1000 porcine oocytes proved that this system is capable of reducing cytoplasm loss by 60% at the same level of enucleation success rate and almost doubling the cleavage rate of clone embryos in comparison to blind aspiration method. Conclusions: The results prove that our method significantly improves the developmental competence of cloned embryos in comparison to manual enucleation method. Significance: Our method is expected to improve the extremely low success rate of animal cloning in the future.

The formation of the gigaseal, a giga Omega-scale seal between the micropipette electrode and cell surface, is the keystone to measure the extremely weak electric signals of cell ion channels in patch clamp technique. To determine a point on the cell surface facilitating gigaseal formation, 3-D cell morphology information is required. However, the current 3-D cell morphology measurement methods relying on special devices or easily causing clogging issues of the micropipette electrode due to contact on cells are usually not applicable in the traditional patch clamp system. Addressing this, a noninvasive 3-D cell morphology measurement method was developed in this article for robotic patch clamp with a higher success rate of gigaseal formation. First, the measured bath impedance of the micropipette electrode was modeled and then utilized to measure the cell surface height noninvasively. Using the measured cell surface heights at key positions, the 3-D cell morphology was fitted to determine a contact position on the cell surface to facilitate gigaseal formation. Finally, a robotic whole-patch clamp process was conducted at the determined contact position. Experimental results demonstrated that 100% and 90% success rates of noninvasive 3-D cell morphology measurements were achieved on the cultured human embryonic kindey (HEK)-293 cells and pyramidal neurons in mouse brain slices, respectively, with an average measurement error of cell surface height less than $0.15~\mu \text{m}$ . At the determined contact position, significant improvements in success rates of gigaseal formation and whole-cell patch clamp operation were achieved in comparison to the results at the positions recommended in related work. Our research may spike inspiration to improve the success rates of gigaseal formation and patch clamp operation based on 3-D cell morphologies.