A new method for assessing lung tumor motion in radiotherapy using dynamic chest radiography

Dynamic chest radiography (DCR) is a recent advanced modality to acquire dynamic and functional images. We developed a new method using DCR and the free analysis software, Kinovea, to assess lung tumor motion. This study aimed to demonstrate the usefulness of our method. Phantom and clinical studies were performed. In the phantom study, dynamic images of a moving lead sphere were acquired using DCR, and the motion of the phantom was tracked using Kinovea in a DCR video. The amplitude of phantom motion was measured and compared with a predetermined baseline amplitude. In a clinical study, DCR and respiratory‐gated four‐dimensional computed tomography (4D‐CT) were performed on 15 patients who underwent stereotactic body radiation therapy for lung tumors. The amplitudes of tumor motion in DCR and 4D‐CT were measured in the superior‐inferior (SI), left‐right (LR), and anterior‐posterior (AP) directions, and the square root of the sum of squares (SRSS) of the amplitude was calculated in all directions. Spearman's rank correlation and the Wilcoxon signed‐rank test were performed to determine the correlations of the amplitudes of tumor motion obtained using DCR and 4D‐CT. In the phantom study, the absolute mean error between the measured and predetermined amplitudes was 0.60 mm (range: 0.061.53 mm). In the clinical study, the amplitudes of tumor motion obtained using DCR correlated significantly with those of 4D‐CT in the SI and LR directions, as did the SRSS values. The median amplitudes for DCR were significantly higher than those for 4D‐CT in all (SI, LR, and AP) directions, as were the SRSS values. Our proposed method based on DCR and Kinovea is useful for assessing lung tumor motion, visually and quantitatively. Therefore, DCR has potential as a new modality for evaluating lung tumor motion in radiotherapy.

Smart Web-Based Platform to Support Physical Rehabilitation

The enhancement of ubiquitous and pervasive computing brings new perspectives in medical rehabilitation. In that sense, the present study proposes a smart, web-based platform to promote the reeducation of patients after hip replacement surgery. This project focuses on two fundamental aspects in the development of a suitable tele-rehabilitation application, which are: (i) being based on an affordable technology, and (ii) providing the patients with a real-time assessment of the correctness of their movements. A probabilistic approach based on the development and training of ten Hidden Markov Models (HMMs) is used to discriminate in real time the main faults in the execution of the therapeutic exercises. Two experiments are designed to evaluate the precision of the algorithm for classifying movements performed in the laboratory and clinical settings, respectively. A comparative analysis of the data shows that the models are as reliable as the physiotherapists to discriminate and identify the motion errors. The results are discussed in terms of the required setup for a successful application in the field and further implementations to improve the accuracy and usability of the system.

Gamifying Motion Control Assessments Using Leap Motion Controller

In rehabilitation, exergames and serious games are widely usedin order to motivate patients in the therapeutic procedure. Patients are asked to modify their incorrect motor patterns or reinforce the proper ones through activity rather than exercise. Interactive applications as such, can have a huge impact on a patient's motivation making repetitive physical exercises into pleasant experiences, thus maximizing the gains of therapy. In this paper we present the design and implementation of a serious game platform based on virtual 3D game environment and leap motion controller for interaction. For each session, achieved goals and response to stimuli is recorded and analyzed. Preliminary analysis results from evaluating the game with healthy subjects are encouraging.

A comparison of peripheral imaging technologies for bone and muscle quantification: a technical review of image acquisition

The choice of an appropriate imaging technique to quantify bone, muscle, or muscle adiposity needs to be guided by a thorough understanding of its competitive advantages over other modalities balanced by its limitations. This review details the technical machinery and methods behind peripheral quantitative computed tomography (pQCT), high-resolution (HR)-pQCT, and magnetic resonance imaging (MRI) that drive successful depiction of bone and muscle morphometry, densitometry, and structure. It discusses a number of image acquisition settings, the challenges associated with using one versus another, and compares the risk-benefits across the different modalities. Issues related to all modalities including partial volume artifact, beam hardening, calibration, and motion assessment are also detailed. The review further provides data and images to illustrate differences between methods to better guide the reader in selecting an imaging method strategically. Overall, investigators should be cautious of the impact of imaging parameters on image signal or contrast-to-noise-ratios, and the need to report these settings in future publications. The effect of motion should be assessed on images and a decision made to exclude prior to segmentation. A more standardized approach to imaging bone and muscle on pQCT and MRI could enhance comparability across studies and could improve the quality of meta-analyses.