Features of non-small cell lung carcinomas overlooked at digital chest radiography
ABSTRACT To examine the imaging features of non-small cell lung carcinomas (NSCLC) overlooked at digital chest radiography (dCXR), and compare general and thoracic radiologists' performance for lung carcinoma detection at dCXR.
Frontal and lateral dCXR from 30 consecutive patients with lung carcinoma overlooked during initial interpretation and 30 normal controls were independently retrospectively reviewed by two blinded thoracic radiologists and, in a separate review, three blinded general radiologists. The location, size, histopathology, borders, presence of superimposed structures, and lesion opacity were recorded. Interobserver agreement was calculated, and the detection performance between thoracic and general radiologists was compared.
The average patient age was 67.9 years (range 47-82 years). The average size of carcinomas missed by the thoracic radiologists was 18.1mm (range 10-32 mm). Lesion margins were circumscribed in 29% (2/7), and 71% (5/7) of missed lesions were obscured by anatomical superimposition. Seventy-one percent (5/7) of missed lesions were solid nodules on computed tomography (CT) images. Forty-three percent of lesions were located in the upper lobes and 63% were adenocarcinomas. Compared with general radiologists, the seven NSCLC missed by the thoracic radiologists tended to be smaller (p=0.063), had significantly lower CT density measurements (-92.4+/-87.5 HU versus -70+/-87.2 HU, p=0.050), and more commonly had an ill-defined margin (p=0.026). The clinical stage of the overlooked lesions did not differ between the two groups (p=0.480).
The lesion size, location, conspicuity, and histopathology impact the likelihood of lung carcinoma detection at dCXR in a fashion similar to that of conventional film-screen techniques.
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ABSTRACT: Chest radiography, computed tomography (CT), positron emission tomography (PET), and PET-CT are powerful imaging tools used worldwide for the diagnosis and treatment strategy of NSCLC. Furthermore, we present examples of CT imaging using an exciting new anticancer drug, Lipoplatin, a liposomal nanoparticle formulation of cisplatin. The ability of Lipoplatin™ to target primary tumors and metastases, using the permeability of the vasculature and the growing tumor for its preferential extravasation, and to cause a greater damage to tumor tissue as compared to normal tissue has been demonstrated in animal and human studies. It was demonstrated that Lipoplatin™ can target and kill tumor endothelial cells and, thus, it has the properties of a chemotherapeutic and of an antiangiogenesis drug, combined together. CT scans from patients participating in a multicenter Phase III clinical study demonstrate appraisal of response to Lipoplatin plus paclitaxel as first line treatment in NSCLC. Our results and literature review suggest that key factors for effective chemotherapy treatment and response of NSCLC relate to histological type and early diagnosis. We further suggest that liposomes endowed with tumor targeting properties can be used as carriers of radioactive material in cancer imaging.Cancer Therapy 01/2008; 6:629-646.
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ABSTRACT: To assess whether short-term feedback helps readers to increase their performance using computer-aided detection (CAD) for nodule detection in chest radiography. The 140 CXRs (56 with a solitary CT-proven nodules and 84 negative controls) were divided into four subsets of 35; each were read in a different order by six readers. Lesion presence, location and diagnostic confidence were scored without and with CAD (IQQA-Chest, EDDA Technology) as second reader. Readers received individual feedback after each subset. Sensitivity, specificity and area under the receiver-operating characteristics curve (AUC) were calculated for readings with and without CAD with respect to change over time and impact of CAD. CAD stand-alone sensitivity was 59 % with 1.9 false-positives per image. Mean AUC slightly increased over time with and without CAD (0.78 vs. 0.84 with and 0.76 vs. 0.82 without CAD) but differences did not reach significance. The sensitivity increased (65 % vs. 70 % and 66 % vs. 70 %) and specificity decreased over time (79 % vs. 74 % and 80 % vs. 77 %) but no significant impact of CAD was found. Short-term feedback does not increase the ability of readers to differentiate true- from false-positive candidate lesions and to use CAD more effectively. • Computer-aided detection (CAD) is increasingly used as an adjunct for many radiological techniques. • Short-term feedback does not improve reader performance with CAD in chest radiography. • Differentiation between true- and false-positive CAD for low conspicious possible lesions proves difficult. • CAD can potentially increase reader performance for nodule detection in chest radiography.European Radiology 03/2012; 22(8):1659-64. DOI:10.1007/s00330-012-2412-7 · 4.34 Impact Factor