STUDY OF THE EFFECTS OF TOTAL MODULATION TRANSFER FUNCTION CHANGES ON OBSERVER PERFORMANCE USING CLINICAL MAMMOGRAMS

The main goal of this study was to relate physical changes in image quality measured by Modulation Transfer Function (MTF) to diagnostic accuracy.^ One Hundred and Fifty Kodak Min-R screen/film combination conventional craniocaudal mammograms obtained with the Pfizer Microfocus Mammographic system were selected from the files of the Department of Radiology, at M.D. Anderson Hospital and Tumor Institute.^ The mammograms included 88 cases with a variety of benign diagnosis and 62 cases with a variety of malignant biopsy diagnosis. The average age of the patient population was 55 years old. 70 cases presented calcifications with 30 cases having calcifications smaller than 0.5mm. 46 cases presented irregular bordered masses larger than 1 cm. 30 cases presented smooth bordered masses with 20 larger than 1 cm.^ Four separated copies of the original images were made each having a different change in the MTF using a defocusing technique whereby copies of the original were obtained by light exposure through different thicknesses (spacing) of transparent film base.^ The mammograms were randomized, and evaluated by three experienced mammographers for the degree of visibility of various anatomical breast structures and pathological lesions (masses and calicifications), subjective image quality, and mammographic interpretation.^ 3,000 separate evaluations were anayzed by several statistical techniques including Receiver Operating Characteristic curve analysis, McNemar test for differences between proportions and the Landis et al. method of agreement weighted kappa for ordinal categorical data.^ Results from the statistical analysis show: (1) There were no statistical significant differences in the diagnostic accuracy of the observers when diagnosing from mammograms with the same MTF. (2) There were no statistically significant differences in diagnostic accuracy for each observer when diagnosing from mammograms with the different MTF's used in the study. (3) There statistical significant differences in detail visibility between the copies and the originals. Detail visibility was better in the originals. (4) Feature interpretations were not significantly different between the originals and the copies. (5) Perception of image quality did not affect image interpretation.^ Continuation and improvement of this research ca be accomplished by: using a case population more sensitive to MTF changes, i.e., asymptomatic women with minimum breast cancer, more observers (including less experienced radiologists and experienced technologists) must collaborate in the study, and using a minimum of 200 benign and 200 malignant cases.^

Temporal variations of dyspnea, fatigue, and lung function in chronic lung disease

Background. Research investigating symptom management in patients with chronic obstructive pulmonary disease (COPD) largely has been undertaken assuming the homeostatic construct, without regard to potential roles of circadian rhythms. Temporal relations among dyspnea, fatigue, peak expiratory flow rate (PEFR) and objective measures of activity/rest have not been reported in COPD. ^ Objectives. The specific aims of this study were to (1) explore the 24-hour patterns of dyspnea, fatigue, and PEFR in subjects with COPD; (2) examine the relations among dyspnea, fatigue, and PEFR in COPD; and (3) examine the relations among objective measures of activity/rest and dyspnea, fatigue, and PEFR in COPD. ^ Methods. The repeated-measures design involved 10 subjects with COPD who self-assessed dyspnea and fatigue by 100 mm visual analog scales, and PEFR by peak flow meter in their home 5 times a day for 8 days. Activity/rest was measured by wrist actigraphy. Single and population mean cosinor analyses and correlations were computed for dyspnea, fatigue, and PEFR; correlations were done among these variables and activity/rest. ^ Results. Circadian rhythms were documented by single cosinor analysis in 40% of the subjects for dyspnea, 60% for fatigue, and 60% for PEFR. The population cosinor analysis of PEFR yielded a significant rhythm (p < .05). The 8-day 24-hour means of dyspnea and fatigue was moderately correlated (r = .48, p < .01). Dyspnea and PEFR, and fatigue and PEFR, were weakly correlated in a negative way (r = −.11, p < .05 and r = −.15, p < .01 respectively). Weak to moderate correlations (r = .12–.34, p < .05) were demonstrated between PEFR and mean activity level measured up to 4 hours before PEFR measurement. ^ Conclusions. The findings suggest that (1) the dyspnea and fatigue experienced by COPD patients are moderately related, (2) there is a weak to modest positive relation between PEFR and activity levels, and (3) temporal variation in lung function may not affect the dyspnea and fatigue experienced by patients with COPD. Further research, examining the relations among dyspnea, fatigue, PEFR, and activity/rest is needed. Replication of this study is suggested with a larger sample size. ^

Improving the accuracy of radiation pneumonitis dose response models

The prognosis for lung cancer patients remains poor. Five year survival rates have been reported to be 15%. Studies have shown that dose escalation to the tumor can lead to better local control and subsequently better overall survival. However, dose to lung tumor is limited by normal tissue toxicity. The most prevalent thoracic toxicity is radiation pneumonitis. In order to determine a safe dose that can be delivered to the healthy lung, researchers have turned to mathematical models predicting the rate of radiation pneumonitis. However, these models rely on simple metrics based on the dose-volume histogram and are not yet accurate enough to be used for dose escalation trials. The purpose of this work was to improve the fit of predictive risk models for radiation pneumonitis and to show the dosimetric benefit of using the models to guide patient treatment planning. The study was divided into 3 specific aims. The first two specifics aims were focused on improving the fit of the predictive model. In Specific Aim 1 we incorporated information about the spatial location of the lung dose distribution into a predictive model. In Specific Aim 2 we incorporated ventilation-based functional information into a predictive pneumonitis model. In the third specific aim a proof of principle virtual simulation was performed where a model-determined limit was used to scale the prescription dose. The data showed that for our patient cohort, the fit of the model to the data was not improved by incorporating spatial information. Although we were not able to achieve a significant improvement in model fit using pre-treatment ventilation, we show some promising results indicating that ventilation imaging can provide useful information about lung function in lung cancer patients. The virtual simulation trial demonstrated that using a personalized lung dose limit derived from a predictive model will result in a different prescription than what was achieved with the clinically used plan; thus demonstrating the utility of a normal tissue toxicity model in personalizing the prescription dose.