Tumorous tissue characterization using integrated 18F-FDG PET/dual-energy CT in lung cancer: Combining iodine enhancement and glycolytic activity.

Positron emission tomography/computed tomography (PET/CT) with 18F-fluorodeoxyglucose (18F-FDG) has become the method of choice for tumor staging in lung cancer patients with improved diagnostic accuracy for the evaluation of lymph node involvement and distant metastasis. Due to its spectral capabilities, dual-energy CT (DECT) employs a material decomposition algorithm enabling precise quantification of iodine concentrations in distinct tissues. This technique enhances the characterization of tumor blood supply and has demonstrated promising results for the assessment of therapy response in patients with lung cancer. Several studies have demonstrated that DECT provides additional value to the PET-based evaluation of glycolytic activity, especially for the evaluation of therapy response and follow-up of patients with lung cancer. The combination of PET and DECT in a single scanner system enables the simultaneous assessment of glycolytic activity and iodine enhancement, offering further insight to the characterization of tumorous tissues. Recently a new approach of a novel integrated PET/DECT was investigated in a pilot study on patients with non-small cell lung cancer (NSCLC). The study showed a moderate correlation between PET-based standard uptake values (SUV) and DECT-based iodine densities in the evaluation of lung tumorous tissue but with limited assessment of lymph nodes. The following review on tumorous tissue characterization using PET and DECT imaging describes the strengths and limitations of this novel technique.

Non-contrast and portal venous phase computed tomography in breast cancer hepatic metastases: comparison of tumor measurements and impact on response assessment.

BACKGROUND: For many common malignancies, including breast cancer, evaluation for metastatic disease using multiphase computed tomography (CT) has fallen out of favor and been replaced by studies performed only in the portal venous phase. However, differences in tumor vascularity could produce differences in appearance on post-contrast imaging. PURPOSE: To assess non-contrast phase and portal venous phase computed tomography in detection and measurement of hepatic metastases from breast carcinoma. MATERIALS AND METHODS: A total of 75 CT scans from 52 breast cancer patients were independently assessed by three body imagers for lesion presence, number and size. Readers randomly assessed portal venous phase or combined phase images at one session with cross-over reads performed four to six weeks later. RESULTS: In the 58% of cases where index lesions measured larger on combined phase, the mean difference in lesion size was 5.7 mm. In this group, combined phase reads demonstrated an 8.4 mm increase in sum of largest diameters, and a mean percentage sum of largest diameters increase of 19% compared to portal venous phase-only reads. CONCLUSION: Addition of non-contrast phase images results in increased index lesion size in most patients with hepatic metastases from breast cancer. If only the portal venous phase is utilized, there is potential for incorrectly diagnosing disease progression on follow-up due to underestimation of lesion size.

Benefits of Integrated RIS/PACS/Reporting Due to Automatic Population of Templated Reports.

With integration of the Radiological Information Systems (RIS), Picture Archiving and Communication systems (PACS), and reporting systems, patient identifiers and examination information can automatically map into examination reports. There are many potential benefits of report automation to radiologists including improvements in efficiency, accuracy, and fatigue. In this article we describe a 2 part study, with the first part being an anonymous survey of radiologists concerning report automation. A total of 13 staff radiologists and 9 radiology residents at a single institution completed an anonymous survey. Respondents were asked if automatic population of examination description, comparison examination data, indications, computed tomography dose, technique, and copy to physician data saved time, decreased fatigue, and increased accuracy. Respondents were asked if a "copy findings" function saved time. The second objective part of the study was a mock examination experiment to assess time savings of report automation and to assess error rates. Of all, 9 radiologists were asked to dictate fields for 8 mock examinations. Subjects were timed and reporting errors monitored. Estimated daily time savings and error rates were calculated assuming a mix of 80 studies. A total of 95% surveyed responded that report automation saved time; 91% that report automation improved accuracy of dictations; 82% that report automation decreased fatigue. Furthermore, 83% of copy finding function users reported time savings. Average time to dictate these prepopulated fields was 51 seconds per study. Average error rate per report was 0.86, with an average of 0.26 errors remaining uncorrected upon report completion. Estimated average time per day saved per radiologist from report automation was 68 minutes. Estimated average corrected errors was 48 per day. Estimated average uncorrected or missed errors was 21 per day. These estimated benefits from report automation result from tight integration of RIS, PACS, and reporting systems.

A noise-optimized virtual monoenergetic reconstruction algorithm improves the diagnostic accuracy of late hepatic arterial phase dual-energy CT for the detection of hypervascular liver lesions.

OBJECTIVES: To assess the image quality and diagnostic accuracy of a noise-optimized virtual monoenergetic imaging (VMI+) algorithm compared with standard virtual monoenergetic imaging (VMI) and linearly-blended (M_0.6) reconstructions for the detection of hypervascular liver lesions in dual-energy CT (DECT). METHODS: Thirty patients who underwent clinical liver MRI were prospectively enrolled. Within 60 days of MRI, arterial phase DECT images were acquired on a third-generation dual-source CT and reconstructed with M_0.6, VMI and VMI+ algorithms from 40 to 100 keV in 5-keV intervals. Liver parenchyma and lesion contrast-to-noise-ratios (CNR) were calculated. Two radiologists assessed image quality. Lesion sensitivity, specificity and area under the receiver operating characteristic curves (AUCs) were calculated for the three algorithms with MRI as the reference standard. RESULTS: VMI+ datasets from 40 to 60 keV provided the highest liver parenchyma and lesion CNR (p ≤0.021); 50 keV VMI+ provided the highest subjective image quality (4.40±0.54), significantly higher compared to VMI and M_0.6 (all p <0.001), and the best diagnostic accuracy in < 1-cm diameter lesions (AUC=0.833 vs. 0.777 and 0.749, respectively; p ≤0.003). CONCLUSIONS: 50-keV VMI+ provides superior image quality and diagnostic accuracy for the detection of hypervascular liver lesions with a diameter < 1cm compared to VMI or M_0.6 reconstructions. KEY POINTS: • Low-keV VMI+ are characterized by higher contrast resulting from maximum iodine attenuation. • VMI+ provides superior image quality compared with VMI or M_0.6. • 50-keV_VMI+ provides higher accuracy for the detection of hypervascular liver lesions < 1cm.

Differentiating biliary cystadenomas from benign hepatic cysts: Preliminary analysis of new predictive imaging features.

OBJECTIVE: To identify performance of imaging features in differentiating hepatic cysts from biliary cystadenomas of the liver. METHODS: 25 pathologically confirmed hepatic cystic lesions (hepatic cysts or biliary cystadenomas) were evaluated retrospectively and predetermined imaging features assessed for performance in differentiation. RESULTS: Any septation which arose from a cyst wall without external indentation had a very high association with biliary cystadenoma, while the presence of a thick septation had only a moderate association. CONCLUSIONS: The relationship between septations and the wall of the cystic lesion performed better than previously reported features including thick septations.