Blind spots at oncological CT: lessons learned from PET/CT

Esses, Steven J.; Yeframov, Nikolay; Bernstine, Hanna; Sella, Tamar; Fraifeld, Shifra; Kruskal, Jonathan B.; Groshar, David

doi:10.1102/1470-7330.2012.0030

Cited by 8 publications

(9 citation statements)

References 37 publications

(46 reference statements)

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“…Other studies have reported similar results, with frequently missed lesions on radiologic examinations being pulmonary embolism, venous thrombosis, unexpected gastrointestinal tumors, and bone and soft tissue lesions such as metastasis (2,3,9).…”

Section: Jksronlineorgsupporting

confidence: 62%

“…Occasionally, as in cases of neck or abdominal computed tomography (CT) scans, additional specific sites (i.e., a part of the chest) may inevitably be included and also need to be interpreted correctly. Incidental but potentially important findings outside the area of interest may be present but missed in any radiologic studies (2)(3)(4)(5)(6). We have occasionally found chest lesions that were not reported on neck CT interpretations when follow-up neck or chest CT studies were performed and compared with a previous neck CT study.…”

Section: Introductionmentioning

confidence: 98%

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Characteristics of Chest Lesions Missed on Neck CT Interpretations

Park

Beck

Jang

et al. 2016

J Korean Soc Radiol

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Purpose: The purpose of this study was to identify the characteristics of chest lesions that are missed in interpretations of neck computed tomography (CT) scans. Materials and Methods: A total of 240 consecutive neck CT scans were retrospectively analyzed to determine whether chest lesions were included or not. All missed chest lesions, which had not been described on neck CT reports, were recorded, and classified according to their clinical significance (insignificant, indeterminate, or significant) and awareness (known or unknown) at the time of CT interpretation, and their radiologic patterns were analyzed. Results: Eighty seven (36.3%) of 240 neck CT scans had 105 chest lesions, and 88 of these were not described on the neck CT reports. Thirty seven clinically known or insignificant lesions were excluded, resulting in a miss rate for chest lesions of 35.2% (37/105), with six of these (5.7%) being potentially significant. The most common location of missed chest lesions was the lung (56/88, 63.6%), and 45 (80.4%) of these missed lung lesions were visualized only with lung window settings. Conclusion: Chest lesions were common and frequently missed on neck CT interpretations. When reviewing neck CT scans, a special attention should be given to lung lesions by using lung window settings.

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Section: Jksronlineorgsupporting

confidence: 62%

Section: Introductionmentioning

confidence: 98%

Characteristics of Chest Lesions Missed on Neck CT Interpretations

Park

Beck

Jang

et al. 2016

J Korean Soc Radiol

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“…18 F-FDG is the most widely used radiolabeled agent (or tracer) which is actively taken up and accumulated in cancer cells [4]. Since 18 F-FDG PET/CT can detect cancer cells at cellular and molecular levels, it is regarded as the most sensitive and specified method among current imaging modalities [14][15][16].…”

Section: Pet Specialists and 18 F-fdg Pet/ctmentioning

confidence: 99%

Interactive Communication Between PET Specialists and Oncologists

Che

Zhang

Dong

et al. 2016

Perspectives on Nuclear Medicine for Molecular Diagnosis and Integrated Therapy

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With an increasing number of positron emission tomography (PET) facilities while a growing shortage of PET specialists in mainland China, interactive communication between PET specialists and oncologists plays a crucial role in individualized management of cancer patients and survivors. It is essential that PET specialists should be well informed by oncologists of their patients' history, current problem, treatments, and particularly, the follow-up information. Vice versa, oncologists should be advised by PET specialists on their thorough interrogation, detailed observations, as well as potential false-positive or false-negative findings-some of which might be ignored in their reports. Improving communication and coordination between PET specialists and oncologists has been linked not only to greater understanding and cooperation but also better patient management. In addition, this interactive communication is an essential element of good collaboration for multicenter clinical trials, for instance, how to make PET as an imaging biomarker to evaluate efficacy more rapidly and to increase the probability of success in a clinical trial and how to move non-FDG radiopharmaceutical forward, etc. Here, our review focuses on the conceptual framework, key features, current problems, and future perspectives on this topic.

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“…These rates are based on the values found in the literature. [30][31][32][33][34] Treatment. Different types of treatment (surgery, radiotherapy, and drug therapy) can be specified in the model, as well as decision rules that govern the choice of treatment for a specific patient.…”

Section: Disease Modelmentioning

confidence: 99%

The Melanoma MAICare Framework: A Microsimulation Model for the Assessment of Individualized Cancer Care

et al. 2016

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Recently, new but expensive treatments have become available for metastatic melanoma. These improve survival, but in view of the limited funds available, cost-effectiveness needs to be evaluated. Most cancer cost-effectiveness models are based on the observed clinical events such as recurrence- free and overall survival. Times at which events are recorded depend not only on the effectiveness of treatment but also on the timing of examinations and the types of tests performed. Our objective was to construct a microsimulation model framework that describes the melanoma disease process using a description of underlying tumor growth as well as its interaction with diagnostics, treatments, and surveillance. The framework should allow for exploration of the impact of simultaneously altering curative treatment approaches in different phases of the disease as well as altering diagnostics. The developed framework consists of two components, namely, the disease model and the clinical management module. The disease model consists of a tumor level, describing growth and metastasis of the tumor, and a patient level, describing clinically observed states, such as recurrence and death. The clinical management module consists of the care patients receive. This module interacts with the disease process, influencing the rate of transition between tumor growth states at the tumor level and the rate of detecting a recurrence at the patient level. We describe the framework as the required input and the model output. Furthermore, we illustrate model calibration using registry data and data from the literature.

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Blind spots at oncological CT: lessons learned from PET/CT

Cited by 8 publications

References 37 publications

Characteristics of Chest Lesions Missed on Neck CT Interpretations

Characteristics of Chest Lesions Missed on Neck CT Interpretations

Interactive Communication Between PET Specialists and Oncologists

The Melanoma MAICare Framework: A Microsimulation Model for the Assessment of Individualized Cancer Care

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