The Streaming Web-Based Exercise at Home Study for Breast and Prostate Cancer Survivors: A Feasibility Study Protocol.

BACKGROUND: Despite the known benefits of physical activity in cancer survivors, adherence to exercise guidelines remains low. Known barriers to adhering to guidelines include a lack of time and an unwillingness to return to treatment facilities. Virtual exercise programming could assist in mitigating these barriers. This protocol presents a single arm pilot study exploring the feasibility of personalized Zoom-delivered exercise training for breast and prostate cancer survivors. A secondary objective is to determine the preliminary efficacy of participation on body composition, estimated VO2max, hand grip, one repetition maximum leg press, resting heart rate, resting blood pressure, exercise self-efficacy, and intentions to remain active. METHODS: Breast (n = 10) and prostate (n = 10) cancer survivors will participate in a 24-week feasibility study, including (1) 12 weeks of one-on-one virtual personal training with an exercise physiologist (EP) via Zoom, and (2) individual exercise for a 12-week follow-up period using recordings of Zoom sessions for guidance. Physical assessments and surveys will be implemented at baseline, 12 weeks, and at the end of the study (24 weeks from baseline). CONCLUSIONS: While virtual exercise programming became popularized during the pandemic, evidence is still required to understand whether it can successfully address barriers and promote participation.

3D image-guided robotic needle positioning system for small animal interventions.

PURPOSE: This paper presents the design of a micro-CT guided small animal robotic needle positioning system. In order to simplify the robotic design and maintain a small targeting error, a novel implementation of the remote center of motion is used in the system. The system has been developed with the objective of achieving a mean targeting error of <200 µm while maintaining a high degree of user friendliness. METHODS: The robot is compact enough to operate within a 25 cm diameter micro-CT bore. Small animals can be imaged and an intervention performed without the need to transport the animal from one workspace to another. Not requiring transport of the animal reduces opportunities for targets to shift from their localized position in the image and simplifies the workflow of interventions. An improved method of needle calibration is presented that better characterizes the calibration using the position of the needle tip in photographs rather than the needle axis. A calibration fixture was also introduced, which dramatically reduces the time requirements of calibration while maintaining calibration accuracy. Two registration modes have been developed to correspond the robot coordinate system with the coordinate system of the micro-CT scanner. The two registration modes offer a balance between the time required to complete a registration and the overall registration accuracy. The development of slow high accuracy and fast low accuracy registration modes provides users with a degree of flexibility in selecting a registration mode best suited for their application. RESULTS: The target registration error (TRE) of the higher accuracy primary registration was TRE(primary) = 31 ± 12 µm. The error in the lower accuracy combined registration was TRE(combined) = 139 ± 63 µm. Both registration modes are therefore suitable for small-animal needle interventions. The targeting accuracy of the robotic system was characterized using targeting experiments in tissue-mimicking gelatin phantoms. The results of the targeting experiments were combined with the known calibration and needle deflection errors to provide a more meaningful measure of the needle positioning accuracy of the system. The combined targeting errors of the system were 149 ± 41 µm and 218 ± 38 µm using the primary and combined registrations, respectively. Finally, pilot in vivo experiments were successfully completed to demonstrate the performance of the system in a biomedical application. CONCLUSIONS: The device was able to achieve the desired performance with an error of <200 µm and improved repeatability when compared to other designs. The device expands the capabilities of image-guided interventions for preclinical biomedical applications.

Traceable micro-CT scaling accuracy phantom for applications requiring exact measurement of distances or volumes.

PURPOSE: Volumetric x-ray microcomputed tomography (CT) can be employed in a variety of quantitative research applications such as image-guided interventions or characterization of medical devices. To ensure the highest geometric fidelity of images for these applications, a phantom and image processing algorithm have been developed to calibrate the scaling accuracy of micro-CT scanners to a traceable standard and provide corrections to image voxel sizing. METHODS: The calibration phantom contains six borosilicate beads whose separations have been measured to a traceable standard. An image processing algorithm compares the known separations of the beads to their separations in micro-CT images. A least-squares solution is used to determine linear scaling correction factors along each of the three scanner axes to minimize errors in the bead separations within the images by correcting the image voxel size. The correction factors were applied to images of a similar phantom with beads at different positions to evaluate the ability of the correction factors to reduce errors at points independent of the fiducial locations in the calibration phantom. The calibration phantom was used to evaluate the scaling accuracy of five different micro-CT scanners representing four different scanner models. RESULTS: In two of the five scanners evaluated, the correction factors significantly reduced the mean error in bead separations in the images from 0.17% to 0.05% and from 0.37% to 0.07% of the actual bead separations, respectively. Scanners yielding similar voxel sizes possessed comparable geometric errors after correction using the phantom. CONCLUSIONS: Although the magnitude of the corrections is small, such corrections can be important for demanding micro-CT applications. Even if no voxel size correction is required, the phantom provides an easily implemented method to verify the geometric fidelity of micro-CT scanners to a traceable standard of measurement.

Real-time field measurements of stable isotopes in water and CO2 by Fourier transform infrared spectrometry.

Continuous records of isotope behaviour in the environment are invaluable to understanding mass and energy fluxes. Although techniques such as isotope ratio mass spectrometry provide high precision data, they are not well suited to the analysis of a large number of samples and are currently restricted to use in the laboratory. Fourier transform infrared spectrometers are relatively cheap and sufficiently portable and robust to be taken into the field to collect continuous records of gas-phase isotope behaviour. Several examples of the application of this technique will be presented. One data set provides half-hourly determinations of vertical profiles of D/H in water vapour above agricultural fields over a 3-week period; the same infrared spectra can also be used to determine 13C/12C in CO2. The technique has also been applied to the study of CO2 in ambient air and in a limestone cave system. Some of the features and complications associated with the method will also be considered.

Face detection using spectral histograms and SVMs.

We present a face detection method using spectral histograms and support vector machines (SVMs). Each image window is represented by its spectral histogram, which is a feature vector consisting of histograms of filtered images. Using statistical sampling, we show systematically the representation groups face images together; in comparison, commonly used representations often do not exhibit this necessary and desirable property. By using an SVM trained on a set of 4500 face and 8000 nonface images, we obtain a robust classifying function for face and non-face patterns. With an effective illumination-correction algorithm, our system reliably discriminates face and nonface patterns in images under different kinds of conditions. Our method on two commonly used data sets give the best performance among recent face-detection ones. We attribute the high performance to the desirable properties of the spectral histogram representation and good generalization of SVMs. Several further improvements in computation time and in performance are discussed.