We determined contrast thresholds for lesion detection as a function of lesion size in both mammograms and filtered noise backgrounds with the same average power spectrum, P(f)=B/f3. Experiments were done using hybrid images with digital images of tumors added to digitized normal backgrounds, displayed on a monochrome monitor. Four tumors were extracted from digitized specimen radiographs. The lesion sizes were varied by digital rescaling to cover the range from 0.5 to 16 mm. Amplitudes were varied to determine the value required for 92% correct detection in two-alternative forced-choice (2AFC) and 90% for search experiments. Three observers participated, two physicists and a radiologist. The 2AFC mammographic results demonstrated a novel contrast-detail (CD) diagram with threshold amplitudes that increased steadily (with slope of 0.3) with increasing size for lesions larger than 1 mm. The slopes for prewhitening model observers were about 0.4. Human efficiency relative to these models was as high as 90%. The CD diagram slopes for the 2AFC experiments with filtered noise were 0.44 for humans and 0.5 for models. Human efficiency relative to the ideal observer was about 40%. The difference in efficiencies for the two types of backgrounds indicates that breast structure cannot be considered to be pure random noise for 2AFC experiments. Instead, 2AFC human detection with mammographic backgrounds is limited by a combination of noise and deterministic masking effects. The search experiments also gave thresholds that increased with lesion size. However, there was no difference in human results for mammographic and filtered noise backgrounds, suggesting that breast structure can be considered to be pure random noise for this task. Our conclusion is that, in spite of the fact that mammographic backgrounds have nonstationary statistics, models based on statistical decision theory can still be applied successfully to estimate human performance.

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The American Association for Thoracic Surgery provides specific guidelines for lung cancer screening in North America.

Modern imaging methods like computed tomography (CT) generate 3-D volumes of image data. How do radiologists search through such images? Are certain strategies more efficient? Although there is a large literature devoted to understanding search in 2-D, relatively little is known about search in volumetric space. In recent years, with the ever-increasing popularity of volumetric medical imaging, this question has taken on increased importance as we try to understand, and ultimately reduce, errors in diagnostic radiology. In the current study, we asked 24 radiologists to search chest CTs for lung nodules that could indicate lung cancer. To search, radiologists scrolled up and down through a "stack" of 2-D chest CT "slices." At each moment, we tracked eye movements in the 2-D image plane and coregistered eye position with the current slice. We used these data to create a 3-D representation of the eye movements through the image volume. Radiologists tended to follow one of two dominant search strategies: "drilling" and "scanning." Drillers restrict eye movements to a small region of the lung while quickly scrolling through depth. Scanners move more slowly through depth and search an entire level of the lung before moving on to the next level in depth. Driller performance was superior to the scanners on a variety of metrics, including lung nodule detection rate, percentage of the lung covered, and the percentage of search errors where a nodule was never fixated.

There is a need to work toward a mutual understanding and consensus between pathologists, clinicians, and researchers with the use of the term BAC versus adenocarcinoma. Future studies should make some attempt to quantitate these components and/or other features such as size of scar, size of invasive component, or pattern of invasion. Hopefully, this work will allow definition of a category of adenocarcinoma, mixed subtype with predominant BAC/minimal invasion and a favorable prognosis.

Diagnostic accuracy for radiologists is above that expected by chance when they are exposed to a chest radiograph for only one-fifth of a second, a period too brief for more than a single voluntary eye movement. How do radiologists glean information from a first glance at an image? It is thought that this expert impression of the gestalt of an image is related to the everyday, immediate visual understanding of the gist of a scene. Several high-speed mechanisms guide our search of complex images. Guidance by basic features (such as color) requires no learning, whereas guidance by complex scene properties is learned. It is probable that both hardwired guidance by basic features and learned guidance by scene structure become part of radiologists' expertise. Search in scenes may be best explained by a two-pathway model: Object recognition is performed via a selective pathway in which candidate targets must be individually selected for recognition. A second, nonselective pathway extracts information from global or statistical information without selecting specific objects. An appreciation of the role of nonselective processing may be particularly useful for understanding what separates novice from expert radiologists and could help establish new methods of physician training based on medical image perception.

The majority of researchers investigating hyperpolarized gas MRI as a candidate functional lung imaging modality have used 3 He as their imaging agent of choice rather than 129 Xe. This preference has been predominantly due to, 3 He providing stronger signals due to higher levels of polarization and higher gyromagnetic ratio, as well as its being easily available to more researchers due to availability of polarizers (USA) or ease of gas transport (Europe). Most researchers agree, however, that hyperpolarized 129 Xe will ultimately emerge as the imaging agent of choice due to its unlimited supply in nature and its falling cost. Our recent polarizer technology delivers vast improvements in hyperpolarized 129 Xe output. Using this polarizer, we have demonstrated the unique property of xenon to measure alveolar surface area noninvasively. In this article, we describe our human protocols and their safety, and our results for the measurement of the partial pressure of pulmonary oxygen (pO 2 ) by observation of 129 Xe signal decay. We note that the measurement of pO 2 by observation of 129 Xe signal decay is more complex than that for 3 He because of an additional signal loss mechanism due to interphase diffusion of 129 Xe from alveolar gas spaces to septal tissue. This results in measurements of an equivalent pO 2 that accounts for both traditional T 1 decay from pO 2 and that from interphase diffusion. We also provide an update on new technological advancements that form the foundation for an improved compact design polarizer as well as improvements that provide another order-of-magnitude scale-up in xenon polarizer output.

Pulmonary hemorrhage after TTLB is common but rarely requires intervention. An enlarged mPAD at CT may not be a risk factor for higher-grade hemorrhage.