Estimation of Preclinical State Onset Age and Sojourn Time for Heavy Smokers in Lung Cancer.

Estimation of the three key parameters: onset age of the preclinical state, sojourn time and screening sensitivity is critical in cancer screening, since all other terms are functions of the three. A novel link function to connect sensitivity with time in the preclinical state and the likelihood method were used in this project; since sensitivity depends on how long one has entered the preclinical state relative to the total sojourn time. Simulations using Markov Chain Monte Carlo and maximum likelihood estimate were carried out to estimate the key parameters for male and female heavy smokers separately in the low-dose computed tomography group of the National Lung Screening Trial. Sensitivity for male and female heavy smokers were 0.883 and 0.915 respectively at the onset of the preclinical state, and increased to 0.972 and 0.981 at the end. The mean age to make the transition into the preclinical state was 70.94 or 71.15 for male and female heavy smokers respectively, and 90% of heavy smokers at risk for lung cancer would enter the preclinical state in age interval (55.7, 85.8) for males and (54.2, 87.7) for females, and the transition peaked around age 69 for both genders. The mean sojourn time in the preclinical state was 1.43 and 1.49 years, and the 99% credible intervals for the sojourn time were (0.21, 2.96) and (0.37, 2.69) years for male and female heavy smokers correspondingly. Based on the result, low-dose CT should be started at age 55 and ended before 85 for heavy smokers. This provided important information to policy makers.

Lung Nodule Malignancy Prediction From Longitudinal CT Scans With Siamese Convolutional Attention Networks.

Goal: We propose a convolutional attention-based network that allows for use of pre-trained 2-D convolutional feature extractors and is extendable to multi-time-point classification in a Siamese structure. Methods: Our proposed framework is evaluated for single- and multi-time-point classification to explore the value that temporal information, such as nodule growth, adds to malignancy prediction. Results: Our results show that the proposed method outperforms a comparable 3-D network with less than half the parameters on single-time-point classification and further achieves performance gains on multi-time-point classification. Conclusions: Attention-based, Siamese 2-D pre-trained CNNs lead to fast training times and are effective for malignancy prediction from single-time-point or multiple-time-point imaging data.

3-D Active Contour Segmentation Based on Sparse Linear Combination of Training Shapes (SCoTS).

SCoTS captures a sparse representation of shapes in an input image through a linear span of previously delineated shapes in a training repository. The model updates shape prior over level set iterations and captures variabilities in shapes by a sparse combination of the training data. The level set evolution is therefore driven by a data term as well as a term capturing valid prior shapes. During evolution, the shape prior influence is adjusted based on shape reconstruction, with the assigned weight determined from the degree of sparsity of the representation. For the problem of lung nodule segmentation in X-ray CT, SCoTS offers a unified framework, capable of segmenting nodules of all types. Experimental validations are demonstrated on 542 3-D lung nodule images from the LIDC-IDRI database. Despite its generality, SCoTS is competitive with domain specific state of the art methods for lung nodule segmentation.

Correlation of Computed Tomography Measured Presacral Thickness with Body Mass Index.

Sacral colpopexy is often chosen as a reliable approach that effectively resolves vaginal vault prolapse. Advancements in minimally invasive technology, robotic and laparoscopic surgery, have helped facilitate surgical dissection and operation when performing this procedure. An increased presacral thickness can potentially present a surgical challenge when operating in the presacral space. We hypothesize that there is a correlation between body mass index and presacral thickness. Computed Tomography (CT) images of 241 patients were reviewed in this retrospective study. The presacral thickness was measured by taking the cross sectional distance from the sacral promontory to the upper aspect of the iliac arteries. The corresponding demographic information of age, body mass index (BMI), and comorbidities were evaluated using univariate analysis, linear regression, and multiple regression analysis. The mean age was 56.6 years, and BMI was 27.6. The mean presacral thickness measurement based on the CT scan was 21.08 mm. Univariate linear regression models demonstrated a positive correlation between presacral thickness and BMI and a negative correlation with age. When adjusting for both age and BMI on multivariate analysis, a positive correlation with hypertension was found. The surgeon should be aware of this potential change in anatomy when operating in the presacral space.

Correlation of patient age with CT-measured aorta-sacral promontory distance.

INTRODUCTION AND HYPOTHESIS: Pelvic floor disorders are becoming more prevalent in the elderly population. Since more patients are seeking definitive management for their prolapse, the number of elderly patients undergoing sacral colpopexies will likely increase. During sacral colpopexies, the surgeon must carefully dissect in the presacral space and avoid vital structures. In elderly patients the aorta potentially elongates and the vertebral body height decreases. Consequently, there is a potential for anatomical change of distance from the bifurcation of the aorta to the sacral promontory. This study aimed to correlate the aorta-sacral promontory distance with age. METHODS: From 1 January 2013 to 31 January 2014 computed tomography (CT) images of 241 patients were reviewed in this retrospective study. Radiologists measured the aorta-sacral promontory distance on sagittal acquisition. The corresponding demographic information of age, body mass index, and comorbidities was evaluated using univariate analysis and univariate linear regression. RESULTS: The mean age was 56.6 years, and BMI was 27.6. The mean aorta-sacral promontory measurement based on the CT scan was 63.11 mm. Univariate analysis using a t test and ANOVA demonstrated an inverse correlation with age (p < 0.0001) and hypertension (p = 0.0034) and a positive correlation with BMI categories (p < 0.0017) Under univariate linear regression, the weight of the patient in kilograms demonstrated positive correlation (p = 0.0413). CONCLUSIONS: Based on CT measurements, the aorta-sacral promontory distance is decreased in elderly and hypertensive patients. Heavier patients have an increased aorta-sacral promontory distance. These potential anatomical variants should be considered before operating in the presacral space.

Human meniscus allografts' in vivo size and motion characteristics: magnetic resonance imaging assessment under weightbearing conditions.

BACKGROUND: Although many reports have described clinical outcome of meniscus transplants, their size and motion patterns are not well understood. This study assessed postoperative in vivo size and motion patterns of meniscus transplants under full weightbearing conditions. HYPOTHESIS: The human meniscus transplant has size and motion characteristics similar to the native menisci. STUDY DESIGN: Case series; Level of evidence, 4. METHODS: Eight meniscus transplants in 7 knees were studied 15 to 34 months postoperatively. The knees were scanned in an open magnetic resonance imaging 0.5-T superconducting magnet while standing. Single slice sagittal and coronal images were obtained at 0 degrees , 30 degrees , 60 degrees , and 90 degrees of flexion in the operative and contralateral knees. RESULTS: The mean height and width of the anterior and posterior horns of the transplants were similar to those of native menisci. The millimeters of coronal displacement of motion of the midbody were also similar between the transplants and the native menisci. The anterior horn of the native medial menisci moved a mean of 5 mm more (total anterior to posterior translation, P < .05) than did the transplants. The posterior horn of the native medial menisci, and both horns of the native lateral menisci, also tended to move more than the corresponding horns of the transplanted menisci, although this result could not be confirmed statistically, given the number of menisci studied. CONCLUSION: Meniscus transplants had similar size and midbody motion characteristics as the native menisci. The horns of the meniscus transplants tended to show decreased motion compared with the native menisci. The operative techniques and subsequent healing of the graft bone and peripheral attachments provided a stable meniscus construct.