Postinjection transmission scanning in myocardial 18F-FDG PET studies using both filtered backprojection and iterative reconstruction.

The aim of the present study was to evaluate the effect of postinjection transmission scanning (Post-Tx) on both the qualitative interpretation and the quantitative analysis of cardiac (18)F-FDG PET images. Furthermore, the accuracy of 2 different methods to correct for emission contamination was studied. An additional aim of this study was to compare images reconstructed with both standard filtered backprojection (FBP) and an iterative reconstruction algorithm (ordered-subset maximization expectation [OSEM]). METHODS: Sixteen patients underwent dynamic (18)F-FDG imaging. Both before injection of (18)F-FDG and after completing the emission scan, a 10-min transmission scan was performed (Pre-Tx and Post-Tx, respectively). Images were reconstructed using both FBP and OSEM. The emission study reconstructed with Pre-Tx was considered to be the gold standard. Emission studies were also reconstructed with Post-Tx, with and without correction for emission contamination. Correction for emission contamination was performed with either transmission image segmentation (TIS) or by estimating the emission bias from the last emission frame (dwell profile [DP] method). All images were then compared by calculating ratios of (18)F-FDG activity between corresponding myocardial segments in each patient. Furthermore, qualitative grading of (18)F-FDG uptake was compared between the studies. RESULTS: The mean ratio of (18)F-FDG activity between segments from FBP-Post and FBP-Pre was 0.78 +/- 0.08. When TIS and DP were used, the mean ratios were 0.80 +/- 0.07 and 0.94 +/- 0.06, respectively. The use of OSEM resulted in, on average, 2% lower values for (18)F-FDG activity as compared with FBP. The mean normalized (18)F-FDG uptake was higher in FBP-Post, especially in segments with decreased (18)F-FDG activity. Only in the case of DP were no significant differences observed as compared with FBP-Pre. In general, qualitative analysis of the images showed that the agreement between the reconstruction methods was comparable with the reproducibility of FBP-Pre. CONCLUSION: Post-Tx for attenuation correction in cardiac (18)F-FDG PET scans resulted in substantial underestimation of (18)F-FDG activity. More accurate results were obtained with correction for emission contamination using DP. Differences in visual assessment of (18)F-FDG images were small. Finally, iterative reconstruction could be used as an alternative to FBP in static (18)F-FDG imaging of the heart.     

腹部CT:迭代统计重建法与滤波反投影重建技术的比较

目的比较在不同X线管电流时间(50～200mAs)条件下通过迭代重建法(ASIR)与滤波反投影重建技术(FBP)获得腹部CT影像质量及病变显示能力。材料与方法征得22     

Local detection of prostate cancer by positron emission tomography with 2-fluorodeoxyglucose: comparison of filtered back projection and iterative reconstruction with segmented attenuation correction.

BACKGROUND: To compare filtered back projection (FBP) and iterative reconstruction with segmented attenuation correction (IRSAC) in the local imaging of prostate cancer by positron emission tomography with 2-fluorodeoxyglucose (FDG-PET). METHODS: We retrospectively identified 13 patients with primary (n=7) or recurrent (n=6) prostate cancer who had increased uptake in the prostate on FDG-PET performed without urinary catheterization, contemporaneous biopsy confirming the presence of active tumor in the prostate, and correlative cross-sectional imaging by MRI (n=8) or CT (n=5). FDG-PET images were reconstructed by FBP and IRSAC. Two independent nuclear medicine physicians separately rated FBP and IRSAC images for visualization of prostatic activity on a 4-point scale. Results were compared using biopsy and cross-sectional imaging findings as the standard of reference. RESULTS: IRSAC images were significantly better that FBP in terms of visualization of prostatic activity in 12 of 13 patients, and were equivalent in 1 patient (p<0.001, Wilcoxon signed ranks test). In particular, 2 foci of tumor activity in 2 different patients seen on IRSAC images were not visible on FBP images. In 11 patients who had a gross tumor mass evident on cross-sectional imaging, there was good agreement between PET and cross-sectional anatomic imaging with respect to tumor localization. CONCLUSIONS: In selected patients, cancer can be imaged within the prostate using FDG-PET, and IRSAC is superior to FBP in image reconstruction for local tumor visualization.     

Quantitative analysis of emphysema and airway measurements according to iterative reconstruction algorithms: comparison of filtered back projection,adaptive statistical iterative reconstruction and model-based iterative reconstruction

Objectives

To evaluate filtered back projection (FBP) and two iterative reconstruction (IR) algorithms and their effects on the quantitative analysis of lung parenchyma and airway measurements on computed tomography (CT) images.

Methods

Low-dose chest CT obtained in 281 adult patients were reconstructed using three algorithms: FBP, adaptive statistical IR (ASIR) and model-based IR (MBIR). Measurements of each dataset were compared: total lung volume, emphysema index (EI), airway measurements of the lumen and wall area as well as average wall thickness. Accuracy of airway measurements of each algorithm was also evaluated using an airway phantom.

Results

EI using a threshold of ?950 HU was significantly different among the three algorithms in decreasing order of FBP (2.30 %), ASIR (1.49 %) and MBIR (1.20 %) (P?<?0.01). Wall thickness was also significantly different among the three algorithms with FBP (2.09 mm) demonstrating thicker walls than ASIR (2.00 mm) and MBIR (1.88 mm) (P?<?0.01). Airway phantom analysis revealed that MBIR showed the most accurate value for airway measurements.

Conclusion

The three algorithms presented different EIs and wall thicknesses, decreasing in the order of FBP, ASIR and MBIR. Thus, care should be taken in selecting the appropriate IR algorithm on quantitative analysis of the lung.

Key Points

? Computed tomography is increasingly used to provide objective measurements of intra-thoracic structures. ? Iterative reconstruction algorithms can affect quantitative measurements of lung and airways. ? Care should be taken in selecting reconstruction algorithms in longitudinal analysis. ? Model-based iterative reconstruction seems to provide the most accurate airway measurements.     

Comparison of adaptive statistical iterative and filtered back projection reconstruction techniques in brain CT

Purpose

To compare image quality and visualization of normal structures and lesions in brain computed tomography (CT) with adaptive statistical iterative reconstruction (ASIR) and filtered back projection (FBP) reconstruction techniques in different X-ray tube current–time products.

Materials and methods

In this IRB-approved prospective study, forty patients (nineteen men, twenty-one women; mean age 69.5 ± 11.2 years) received brain scan at different tube current–time products (300 and 200 mAs) in 64-section multi-detector CT (GE, Discovery CT750 HD). Images were reconstructed with FBP and four levels of ASIR-FBP blending. Two radiologists (please note that our hospital is renowned for its geriatric medicine department, and these two radiologists are more experienced in chronic cerebral vascular disease than in neoplastic disease, so this research did not contain cerebral tumors but as a discussion) assessed all the reconstructed images for visibility of normal structures, lesion conspicuity, image contrast and diagnostic confidence in a blinded and randomized manner. Volume CT dose index (CTDI_vol) and dose-length product (DLP) were recorded. All the data were analyzed by using SPSS 13.0 statistical analysis software.

Results

There was no statistically significant difference between the image qualities at 200 mAs with 50% ASIR blending technique and 300 mAs with FBP technique (p > .05). While between the image qualities at 200 mAs with FBP and 300 mAs with FBP technique a statistically significant difference (p < .05) was found.

Conclusion

ASIR provided same image quality and diagnostic ability in brain imaging with greater than 30% dose reduction compared with FBP reconstruction technique.     

18F-FLT PET for visualization of laryngeal cancer: comparison with 18F-FDG PET.

The feasibility of (18)F-3'-fluoro-3'-deoxy-L-thymidine PET (FLT PET) for detecting laryngeal cancer was investigated and compared with (18)F-FDG PET. METHODS: Eleven patients diagnosed with or strongly suspected of having recurrent laryngeal cancer and 10 patients with histologically proven primary laryngeal cancer underwent attenuation-corrected (18)F-FLT PET imaging 60 min after injection of a median of 213 MBq (range, 175-400 MBq) (18)F-FLT and attenuation-corrected (18)F-FDG PET imaging 90 min after injection of a median of 340 MBq (range, 165-650 MBq) (18)F-FDG. All patients were staged by endoscopy and CT according to the Union Internationale Contre la Cancer TNM staging system. All patients underwent biopsy of the laryngeal area after imaging. Lesions seen on (18)F-FDG PET and (18)F-FLT PET were compared with histopathologic results. Mean SUVs, maximum SUVs, and tumor-to-nontumor (TNT) ratios were calculated for (18)F-FLT and (18)F-FDG. Wilcoxon nonparametric testing was used for comparison of (18)F-FDG with (18)F-FLT uptake. The Spearman correlation coefficient was used to correlate mean SUVs, maximum SUVs, and TNT ratios of (18)F-FDG PET and (18)F-FLT PET. Two-tailed P values < 0.05 were considered significant. RESULTS: (18)F-FDG PET and (18)F-FLT PET detected laryngeal cancer correctly in 15 of 17 patients. One lesion judged as positive on (18)F-FDG PET turned out to be normal tissue. Of 2 lesions judged as positive on (18)F-FLT PET, 1 turned out to be inflammation and the other to be normal tissue. Maximum SUVs were 3.3 (range, 1.9-8.5) for (18)F-FDG and 1.6 (range, 1.0-5.7) for (18)F-FLT (P < 0.001). Mean SUVs were 2.7 (range, 1.5-6.5) for (18)F-FDG and 1.2 (range, 0.8-3.8) for (18)F-FLT (P < 0.001). TNT was 1.9 (range, 1.3-4.7) for (18)F-FDG and 1.5 (range, 1.1-3.5) for (18)F-FLT (P < 0.05). CONCLUSION: The numbers of laryngeal cancers detected with (18)F-FLT PET and (18)F-FDG PET were equal. In laryngeal cancer, the uptake of (18)F-FDG is higher than that of (18)F-FLT.     

Quantitative comparison of analytic and iterative reconstruction methods in 2- and 3-dimensional dynamic cardiac 18F-FDG PET.

The aim of this work was to compare the quantitative accuracy of iteratively reconstructed cardiac (18)F-FDG PET with that of filtered backprojection for both 2-dimensional (2D) and 3-dimensional (3D) acquisitions and to establish an optimal procedure for imaging myocardial viability with (18)F-FDG PET. METHODS: Eight patients underwent dynamic cardiac (18)F-FDG PET using an interleaved 2D/3D scan protocol, enabling comparison of 2D and 3D acquisitions within the same patient and study. A 10-min transmission scan was followed by a 10-min, 25-frame dynamic 3D scan and then by a series of 10 alternating 5-min 3D and 2D scans. Images were reconstructed with filtered backprojection (FBP) or attenuation-weighted ordered-subsets expectation maximization (OSEM), combined with Fourier rebinning (FORE) for 3D acquisitions, applying all usual corrections. Regions of interest (ROIs) were drawn in the myocardium, left ventricle, and ascending aorta, with the last 2 being used to define image-derived input functions (IDIFs). Patlak graphical analysis was used to compare net (18)F-FDG uptake in the myocardium, calculated from either 2D or 3D data, after reconstruction with FBP or OSEM. Either IDIFs or arterial sampling was used as the input function. The same analysis was performed on parametric images. RESULTS: A good correlation (r(2) > 0.99) was found between net (18)F-FDG uptake values for a myocardium ROI determined using each acquisition and reconstruction method and blood-sampling input functions. A similar result was found for parametric images. The ascending aorta was the best choice for IDIF definition. CONCLUSION: Good correlation and no bias of net (18)F-FDG uptake in relation to that based on FBP images, combined with less image noise, make 3D acquisition with FORE plus attenuation-weighted OSEM reconstruction the preferred choice for cardiac (18)F-FDG PET studies.     

Superior objective and subjective image quality of deep learning reconstruction for low-dose abdominal CT imaging in comparison with model-based iterative reconstruction and filtered back projection

Objective:This study aimed to conduct objective and subjective comparisons of image quality among abdominal computed tomography (CT) reconstructions with deep learning reconstruction (DLR) algorithms, model-based iterative reconstruction (MBIR), and filtered back projection (FBP).Methods:Datasets from consecutive patients who underwent low-dose liver CT were retrospectively identified. Images were reconstructed using DLR, MBIR, and FBP. Mean image noise and contrast-to-noise ratio (CNR) were calculated, and noise, artifacts, sharpness, and overall image quality were subjectively assessed. Dunnett’s test was used for statistical comparisons.Results:Ninety patients (67 ± 12.7 years; 63 males; mean body mass index [BMI], 25.5 kg/m²) were included. The mean noise in the abdominal aorta and hepatic parenchyma of DLR was lower than that in FBP and MBIR (p < .001). For FBP and MBIR, image noise was significantly higher for obese patients than for those with normal BMI. The CNR for the abdominal aorta and hepatic parenchyma was higher for DLR than for FBP and MBIR (p < .001). MBIR images were subjectively rated as superior to FBP images in terms of noise, artifacts, sharpness, and overall quality (p < .001). DLR images were rated as superior to MBIR images in terms of noise (p < .001) and overall quality (p = .03).Conclusions:Based on objective and subjective comparisons, the image quality of DLR was found to be superior to that of MBIR and FBP on low-dose abdominal CT. DLR was the only method for which image noise was not higher for obese patients than for those with a normal BMI.Advances in knowledge:This study provides previously unavailable information on the properties of DLR systems and their clinical utility.     

Image quality of ct angiography using model-based iterative reconstruction in infants with congenital heart disease: Comparison with filtered back projection and hybrid iterative reconstruction

PurposeTo compare the image quality, rate of coronary artery visualization and diagnostic accuracy of 256-slice multi-detector computed tomography angiography (CTA) with prospective electrocardiographic (ECG) triggering at a tube voltage of 80 kVp between 3 reconstruction algorithms (filtered back projection (FBP), hybrid iterative reconstruction (iDose⁴) and iterative model reconstruction (IMR)) in infants with congenital heart disease (CHD).MethodsFifty-one infants with CHD who underwent cardiac CTA in our institution between December 2014 and March 2015 were included. The effective radiation doses were calculated. Imaging data were reconstructed using the FBP, iDose⁴ and IMR algorithms. Parameters of objective image quality (noise, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR)); subjective image quality (overall image quality, image noise and margin sharpness); coronary artery visibility; and diagnostic accuracy for the three algorithms were measured and compared.ResultsThe mean effective radiation dose was 0.61 ± 0.32 mSv. Compared to FBP and iDose⁴, IMR yielded significantly lower noise (P < 0.01), higher SNR and CNR values (P < 0.01), and a greater subjective image quality score (P < 0.01). The total number of coronary segments visualized was significantly higher for both iDose⁴ and IMR than for FBP (P = 0.002 and P = 0.025, respectively), but there was no significant difference in this parameter between iDose⁴ and IMR (P = 0.397). There was no significant difference in the diagnostic accuracy between the FBP, iDose⁴ and IMR algorithms (χ² = 0.343, P = 0.842).ConclusionsFor infants with CHD undergoing cardiac CTA, the IMR reconstruction algorithm provided significantly increased objective and subjective image quality compared with the FBP and iDose⁴ algorithms. However, IMR did not improve the diagnostic accuracy or coronary artery visualization compared with iDose⁴.     

18F-FDG PET in evaluation of adrenal lesions in patients with lung cancer.

The purpose of this study was to assess the role of PET with (18)F-FDG in differentiating benign from metastatic adrenal masses detected on CT or MRI scans of patients with lung cancer. METHODS: This retrospective study analyzed (18)F-FDG PET scans of patients with lung cancer who were found to have an adrenal mass on CT or MRI scans. One hundred thirteen adrenal masses (75 unilateral and 19 bilateral; size range, 0.8-4.7 cm) were evaluated in 94 patients. PET findings were interpreted as positive if the (18)F-FDG uptake of the adrenal mass was greater than or equal to that of the liver. PET findings were interpreted as negative if the (18)F-FDG uptake of the adrenal mass was less than that of the liver. All studies were reviewed independently by 3 nuclear medicine physicians, and the results were then correlated with clinical follow-up or biopsy results when available. RESULTS: PET findings were positive in 71 adrenal masses. Sixty-seven of these were eventually considered to be metastatic adrenal disease. In the remaining 4, no changes in lesion size were noted on follow-up examinations. PET findings were negative in 42 adrenal masses, of which 37 eventually proved to be benign. Among the 5 adrenal masses that were false-negative, one was a large necrotic metastasis; 1 was a 2.4-cm lesion with central hemorrhaging, and the remaining 3 were lesions of less than 11 mm. The sensitivity, specificity, and accuracy for detecting metastatic disease were 93%, 90%, and 92%, respectively. CONCLUSION: (18)F-FDG PET is an accurate, noninvasive technique for differentiating benign from metastatic adrenal lesions detected on CT or MRI in patients with lung cancer. In addition, PET has the advantage of assessing the primary cancer sites and detecting other metastases.     

Direct comparison of (18)F-FDG PET and PET/CT in patients with colorectal carcinoma.

The purpose of this study was to compare (18)F-FDG PET and PET/CT in a population of patients with colorectal cancer. METHODS: PET and PET/CT images from 45 patients (17 women, 28 men; mean age +/- SD, 60.8 +/- 11.1 y) with known colorectal cancer referred for PET from June to November 2001 were retrospectively reviewed. Images were acquired with a PET/CT scanner, and (68)Ge attenuation correction was applied. PET images and fused (68)Ge attenuation-corrected PET and CT images were independently and separately interpreted by a moderately experienced reader unaware of the clinical information. Certainty of lesion characterization was scored on a 5-point scale (0 = definitely benign, 1 = probably benign, 2 = equivocal, 3 = probably malignant, 4 = definitely malignant). Lesion location was scored on a 3-point scale (0 = uncertain, 1 = probable, 2 = definite). The presence or absence of tumor was subsequently assessed using all available clinical, pathologic, and follow-up information. Analysis was provided for lesions detected by both PET and PET/CT. RESULTS: The frequency of equivocal and probable lesion characterization was reduced by 50% (50 to 25) with PET/CT, in comparison with PET. The frequency of definite lesion characterization was increased by 30% (84 to 109) with PET/CT. The number of definite locations was increased by 25% (92 to 115) with PET/CT. Overall correct staging increased from 78% to 89% with PET/CT on a patient-by-patient analysis. CONCLUSION: PET/CT imaging increases the accuracy and certainty of locating lesions in colorectal cancer. More definitely normal and definitely abnormal lesions (and fewer probable and equivocal lesions) were identified with PET/CT than with PET alone. Staging and restaging accuracy improved from 78% to 89%.     

(18)F-FDG PET versus (18)F-FDG PET/CT for adrenal gland lesion characterization: a comparison of diagnostic efficacy in lung cancer patients.

OBJECTIVE: The aim of this study was to assess the diagnostic efficacy of integrated PET/CT using fluorodeoxyglucose (FDG) for the differentiation of benign and metastatic adrenal gland lesions in patients with lung cancer and to compare the diagnostic efficacy with the use of PET alone. MATERIALS AND METHODS: Sixty-one adrenal lesions (size range, 5-104 mm; mean size, 16 mm) were evaluated retrospectively in 42 lung cancer patients. Both PET images alone and integrated PET/CT images were assessed, respectively, at two-month intervals. PET findings were interpreted as positive if the FDG uptake of adrenal lesions was greater than or equal to that of the liver, and the PET/CT findings were interpreted as positive if an adrenal lesion show attenuation > 10 HU and showed increased FDG uptake. Final diagnoses of adrenal gland lesions were made at clinical follow-up (n = 52) or by a biopsy (n = 9) when available. The diagnostic accuracies of PET and PET/CT for the characterization of adrenal lesions were compared using the McNemar test. RESULTS: Thirty-five (57%) of the 61 adrenal lesions were metastatic and the remaining 26 lesions were benign. For the depiction of adrenal gland metastasis, the sensitivity, specificity, and accuracy of PET were 74%, 73%, and 74%, respectively, whereas those of integrated PET/CT were 80%, 89%, and 84%, respectively (p values; 0.5, 0.125, and 0.031, respectively). CONCLUSION: The use of integrated PET/CT is more accurate than the use of PET alone for differentiating benign and metastatic adrenal gland lesions in lung cancer patients.     

Imaging of gynecologic tumors: comparison of (11)C-choline PET with (18)F-FDG PET.

This study was designed to compare the value of PET using (11)C-choline with that of PET using (18)F-FDG for the diagnosis of gynecologic tumors. METHODS: We examined 21 patients, including 18 patients with untreated primary tumors and 3 patients with suspected recurrence of ovarian cancer. (11)C-choline PET and (18)F-FDG PET were performed within 2 wk of each other on each patient. The patients fasted for at least 5 h before the PET examinations, and PET was performed 5 min ((11)C-choline) and 60 min ((18)F-FDG) after injection of each tracer. PET images were corrected for the transmission data, and the reconstructed images were visually analyzed. Then, the standardized uptake value (SUV) was calculated for quantitative assessment of tumor uptake. PET results were compared with surgical histology or >6 mo of clinical observations. RESULTS: Of 18 untreated patients, (11)C-choline PET correctly detected primary tumors in 16 patients, whereas (18)F-FDG PET detected them in 14 patients. In 1 patient with small uterine cervical cancer and 1 diabetic patient with uterine corpus cancer, only (11)C-choline PET was true-positive. Both tracers were false-negative for atypical hyperplasia of the endometrium in 1 patient and were false-positive for pelvic inflammatory disease in 1 patient. For the diagnosis of recurrent ovarian cancer (n = 3), (11)C-choline PET and (18)F-FDG PET were true-positive in 1 patient, whereas neither tracer could detect cystic recurrent tumor and microscopic peritoneal disease in the other 2 patients. In the 15 patients with true-positive results for both tracers, tumor SUVs were significantly higher for (18)F-FDG than for (11)C-choline (9.14 +/- 3.78 vs. 4.61 +/- 1.61, P < 0.0001). In 2 patients with uterine cervical cancer, parailiac lymph node metastases were clearly visible on (18)F-FDG PET but were obscured by physiologic bowel uptake on (11)C-choline PET. CONCLUSION: The use of (11)C-choline PET is feasible for imaging of gynecologic tumors. Unlike (18)F-FDG PET, interpretation of the primary tumor on (11)C-choline PET is not hampered by urinary radioactivity; however, variable background activity in the intestine may interfere with the interpretation.     

Comparison between human and model observer performance in low-contrast detection tasks in CT images: application to images reconstructed with filtered back projection and iterative algorithms

Objective:

To compare low-contrast detectability (LCDet) performance between a model [non–pre-whitening matched filter with an eye filter (NPWE)] and human observers in CT images reconstructed with filtered back projection (FBP) and iterative [adaptive iterative dose reduction three-dimensional (AIDR 3D; Toshiba Medical Systems, Zoetermeer, Netherlands)] algorithms.

Methods:

Images of the Catphan® phantom (Phantom Laboratories, New York, NY) were acquired with Aquilion ONE™ 320-detector row CT (Toshiba Medical Systems, Tokyo, Japan) at five tube current levels (20–500 mA range) and reconstructed with FBP and AIDR 3D. Samples containing either low-contrast objects (diameters, 2–15 mm) or background were extracted and analysed by the NPWE model and four human observers in a two-alternative forced choice detection task study. Proportion correct (PC) values were obtained for each analysed object and used to compare human and model observer performances. An efficiency factor (η) was calculated to normalize NPWE to human results.

Results:

Human and NPWE model PC values (normalized by the efficiency, η = 0.44) were highly correlated for the whole dose range. The Pearson''s product-moment correlation coefficients (95% confidence interval) between human and NPWE were 0.984 (0.972–0.991) for AIDR 3D and 0.984 (0.971–0.991) for FBP, respectively. Bland–Altman plots based on PC results showed excellent agreement between human and NPWE [mean absolute difference 0.5 ± 0.4%; range of differences (−4.7%, 5.6%)].

Conclusion:

The NPWE model observer can predict human performance in LCDet tasks in phantom CT images reconstructed with FBP and AIDR 3D algorithms at different dose levels.

Advances in knowledge:

Quantitative assessment of LCDet in CT can accurately be performed using software based on a model observer.CT has become one of the most used techniques in radiology departments. Its progressive introduction in healthcare services and the increasing number of CT scans performed worldwide per year has raised the concern about the related radiation dose.^1,2 Several improvements have been incorporated in the scanners to obtain images at the lowest achievable dose without losing relevant diagnostic information. Among them, iterative reconstruction techniques are promising. Several studies have shown that, with these algorithms, the image noise can be decreased and that higher contrast-to-noise ratios (CNRs) can be obtained compared with traditional filtered back projection (FBP) and thus a significant dose reduction can be achieved.^3–6A wide variability in dose and image quality has been found between different CT scanners to perform similar diagnostic tasks.⁷ To assess image quality, low-contrast detectability (LCDet) is determined as the smallest object visible for certain contrast value at a given dose level. LCDet can be subjectively assessed by several observers scoring the visibility of objects on CT phantom images. These studies are time consuming and expensive owing to the large required number of observers and observations.⁸ The range of available protocols and custom parameters for each application adds complexity to optimization too.⁹ Furthermore, the results might be biased if the observers know beforehand the location of the objects in the phantom. Tests of statistical significance are controversial to obtain average results based on human observer studies, as a great inter- and intra-observer variability may appear.^10,11 Computer model observers, intended to predict the performance of human observers in image analysis, can be an alternative to objectively assess image quality. They can be a useful tool when investigating the influence of acquisition and reconstruction parameters on image quality or the effect of object size, shape and contrast in detection tasks.^12–15In a previous work, an objective statistical method using a specific model observer [non–pre-whitening matched filter with an eye filter (NPWE)] was presented to investigate the influence of different CT acquisition parameters on LCDet.¹⁶The main goal of this work is to compare the model observer LCDet performance in CT images acquired at different dose levels with human observers. Images reconstructed with two algorithms (FBP and iterative) were used in this study. Two-alternative forced choice (2-AFC) experiments, in which the observers scored samples containing signals or background (Bg) extracted from the images, were carried out. The results were presented at the Medical Imaging Perception Society XV Conference held in Washington DC during 14–16 August 2013, which is focused on observer performance analysis and diagnostic quality of imaging technique improvements.     

Detection of distant metastases in esophageal cancer with (18)F-FDG PET.

Standard staging of esophageal and gastroesophageal junction (GEJ) tumors substantially lacks accuracy. The aim of this study was to investigate whether the addition of PET with (18)F-FDG is a valuable gain in the initial staging. METHODS: Between January 1996 and January 2002, (18)F-FDG PET was performed in 74 patients. Conventional staging included CT in all patients and well-performed endoscopic ultrasonography (EUS) in 52 patients. They were compared with (18)F-FDG PET with pathology and follow-up of suspicious lesions as the gold standard. RESULTS: PET identified 70 primary tumors (sensitivity, 95%). Sensitivity to identify locoregional metastases was highest for EUS (69%) but was not different for CT and PET (44% and 55%, respectively). PET was able to identify distant nodal disease in 71% (17/24 patients) compared with 29% (7/24 patients) after combined CT/EUS alone (P = 0.021). Sensitivity to detect distant nodal and systemic (M1) disease increased with PET (78% vs. 37%; P = 0.012). PET upstaged 15 patients (15/74; 20%) correctly as M1 disease, missed by CT/EUS, and correctly downstaged 4 patients (5%) from M1 to M0 disease. However, false upstaging and downstaging was encountered in 5 (7%) and 3 (4%) patients, respectively. CONCLUSION: PET improves the currently applied staging of esophageal and GEJ tumors, particularly by ameliorating the detection of M1 disease.     

Imaging infection and inflammation in children with (18)F-FDG PET and (18)F-FDG PET/CT

The goal of this article is to delineate indications for (18)F-FDG PET/CT pertaining to inflammation in the pediatric population, with emphasis on those that have been described in the literature. The limitations of (18)F-FDG PET/CT in this type of evaluation are also described, and the importance of using as low a dose as feasible is discussed. After reading this article, the reader should be able to list several clinical situations in which (18)F-FDG PET/CT may be appropriate, describe some limitations of (18)F-FDG PET/CT, and explain why dose is particularly important in the pediatric population.     

Comparison of 18F-FLT PET and 18F-FDG PET in esophageal cancer.

18F-FDG PET has gained acceptance for staging of esophageal cancer. However, FDG is not tumor specific and false-positive results may occur by accumulation of FDG in benign tissue. The tracer 18F-fluoro-3'-deoxy-3'-L-fluorothymidine (18F-FLT) might not have these drawbacks. The aim of this study was to investigate the feasibility of 18F-FLT PET for the detection and staging of esophageal cancer and to compare 18F-FLT PET with 18F-FDG PET. Furthermore, the correlation between 18F-FLT and 18F-FDG uptake and proliferation of the tumor was investigated. METHODS: Ten patients with biopsy-proven cancer of the esophagus or gastroesophageal junction were staged with CT, endoscopic ultrasonography, and ultrasound of the neck. In addition, all patients underwent a whole-body 18F-FLT PET and 18F-FDG PET. Standardized uptake values were compared with proliferation expressed by Ki-67 positivity. RESULTS: 18F-FDG PET was able to detect all esophageal cancers, whereas 18F-FLT PET visualized the tumor in 8 of 10 patients. Both 18F-FDG PET and 18F-FLT PET detected lymph node metastases in 2 of 8 patients. 18F-FDG PET detected 1 cervical lymph node that was missed on 18F-FLT PET, whereas 18F-FDG PET showed uptake in benign lesions in 2 patients. The uptake of 18F-FDG (median standardized uptake value [SUV(mean)], 6.0) was significantly higher than 18F-FLT (median SUV(mean), 3.4). Neither 18F-FDG maximum SUV (SUV(max)) nor 18F-FLT SUV(max) correlated with Ki-67 expression in the linear regression analysis. CONCLUSION: In this study, uptake of 18F-FDG in esophageal cancer is significantly higher compared with 18F-FLT uptake. 18F-FLT scans show more false-negative findings and fewer false-positive findings than do 18F-FDG scans. Uptake of 18F-FDG or 18F-FLT did not correlate with proliferation.     

Artificial intelligence machine learning-based coronary CT fractional flow reserve (CT-FFRML): Impact of iterative and filtered back projection reconstruction techniques

BackgroundThe influence of computed tomography (CT) reconstruction algorithms on the performance of machine-learning-based CT-derived fractional flow reserve (CT-FFR_ML) has not been investigated. CT-FFR_ML values and processing time of two reconstruction algorithms were compared using an on-site workstation.MethodsCT-FFR_ML was computed on 40 coronary CT angiography (CCTA) datasets that were reconstructed with both iterative reconstruction in image space (IRIS) and filtered back-projection (FBP) algorithms. CT-FFR_ML was computed on a per-vessel and per-segment basis as well as distal to lesions with ≥50% stenosis on CCTA. Processing times were recorded. Significant flow-limiting stenosis was defined as invasive FFR and CT-FFR_ML values ≤ 0.80. Pearson's correlation, Wilcoxon, and McNemar statistical testing were used for data analysis.ResultsPer-vessel analysis of IRIS and FBP reconstructions demonstrated significantly different CT-FFR_ML values (p ≤ 0.05). Correlation of CT-FFR_ML values between algorithms was high for the left main (r = 0.74), left anterior descending (r = 0.76), and right coronary (r = 0.70) arteries. Proximal and middle segments showed a high correlation of CT-FFR_ML values (r = 0.73 and r = 0.67, p ≤ 0.001, respectively), despite having significantly different averages (p ≤ 0.05). No difference in diagnostic accuracy was observed (both 81.8%, p = 1.000). Of the 40 patients, 10 had invasive FFR results. Per-lesion correlation with invasive FFR values was moderate for IRIS (r = 0.53, p = 0.117) and FBP (r = 0.49, p = 0.142). Processing time was significantly shorter using IRIS (15.9 vs. 19.8 min, p ≤ 0.05).ConclusionCT reconstruction algorithms influence CT-FFR_ML analysis, potentially affecting patient management. Additionally, iterative reconstruction improves CT-FFR_ML post-processing speed.