Pulmonary nodules: sensitivity of maximum intensity projection versus that of volume rendering of 3D multidetector CT data

ACR Appropriateness Criteria® Pulmonary Arteriovenous Malformation (PAVM): 2023 Update

Pulmonary arteriovenous malformations (PAVMs) occur in 30% to 50% of patients with hereditary hemorrhagic telangiectasia. Clinical presentations vary from asymptomatic disease to complications resulting from the right to left shunting of blood through the PAVM such as paradoxical stroke, brain abscesses, hypoxemia, and cardiac failure. Radiology plays an important role both in the diagnosis and treatment of PAVM. Based on different clinical scenarios, the appropriate imaging study has been reviewed and is presented in this document. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

Speeding pelvic fracture fixation: CT scan with simultaneous 3-D pelvic reconstruction in the emergency department

INTRODUCTION

Contrast-enhanced computed tomography (CT) scans are usually needed in the emergency department (ED) to evaluate intra-abdominal injuries associated with pelvic fractures. Three-dimensional (3-D) images for pelvis reconstruction are also needed for planning surgical fixation after admission. This study investigates the advantages integrating a one-stage computed tomography (CT) scan with these two diagnostic modalities simultaneously to reduce the time to surgery and improve the outcomes of pelvic fracture fixation.

METHODS

A retrospective cohort study (2018-2021) of patients with pelvic fractures was performed. Patients were categorized into the one-stage CT group or the two-stage CT group, and propensity score matching was used to address biases. The outcome measures included time to surgical fixation, time to CT scan for 3-D pelvis reconstruction, and overall length of hospital stay.

RESULTS

Four hundred forty-four pelvic fracture patients who underwent definite surgical fixation were identified. Of those, 320 underwent a one-stage CT scan, while the remaining 124 underwent a two-stage CT scan. After well-balanced matching, those in the one-stage CT group had a significantly shorter time to surgical fixation than those in the two-stage CT group (4.6 vs. 6.8 days, p < 0.001). Even among critically ill patients necessitating intensive care unit (ICU) admission, the one-stage CT scan group had a shorter time to definitive surgical fixation (5.5 vs. 7.2 days, p = 0.002) and a shorter hospital stay (19.0 vs. 32.7 days, p = 0.006).

CONCLUSION

A one-stage contrast-enhanced CT scan combined with simultaneous 3-D pelvis reconstruction is promising for expediting surgical fixation in pelvic fracture patients. This innovative strategy may improve patient outcomes by facilitating timely surgical interventions and minimizing delays associated with additional CT scans.

Incorporation of CAD (computer-aided detection) with thin-slice lung CT in routine 18F-FDG PET/CT imaging read-out protocol for detection of lung nodules

OBJECTIVE

To evaluate the detection rate and performance of 18F-FDG PET alone (PET), the combination of PET and low-dose thick-slice CT (PET/lCT), PET and diagnostic thin-slice CT (PET/dCT), and additional computer-aided detection (PET/dCT/CAD) for lung nodules (LN)/metastases in tumor patients. Along with this, assessment of inter-reader agreement and time requirement for different techniques were evaluated as well.

METHODS

In 100 tumor patients (56 male, 44 female; age range: 22-93 years, mean age: 60 years) 18F-FDG PET images, low-dose CT with shallow breathing (5 mm slice thickness), and diagnostic thin-slice CT (1 mm slice thickness) in full inspiration were retrospectively evaluated by three readers with variable experience (junior, mid-level, and senior) for the presence of lung nodules/metastases and additionally analyzed with CAD. Time taken for each analysis and number of the nodules detected were assessed. Sensitivity, specificity, positive and negative predictive value, accuracy, and Receiver operating characteristic (ROC) analysis of each technique was calculated. Histopathology and/or imaging follow-up served as reference standard for the diagnosis of metastases.

RESULTS

Three readers, on an average, detected 40 LN in 17 patients with PET only, 121 LN in 37 patients using ICT, 283 LN in 60 patients with dCT, and 282 LN in 53 patients with CAD. On average, CAD detected 49 extra LN, missed by the three readers without CAD, whereas CAD overall missed 53 LN. There was very good inter-reader agreement regarding the diagnosis of metastases for all four techniques (kappa: 0.84-0.93). The average time required for the evaluation of LN in PET, lCT, dCT, and CAD was 25, 31, 60, and 40 s, respectively; the assistance of CAD lead to average 33% reduction in time requirement for evaluation of lung nodules compared to dCT. The time-saving effect was highest in the less experienced reader. Regarding the diagnosis of metastases, sensitivity and specificity combined of all readers were 47.8%/96.2% for PET, 80.0%/81.9% for PET/lCT, 100%/56.7% for PET/dCT, and 95.6%/64.3% for PET/CAD. No significant difference was observed regarding the ROC AUC (area under the curve) between the imaging methods.

CONCLUSION

Implementation of CAD for the detection of lung nodules/metastases in routine 18F-FDG PET/CT read-out is feasible. The combination of diagnostic thin-slice CT and CAD significantly increases the detection rate of lung nodules in tumor patients compared to the standard PET/CT read-out. PET combined with low-dose CT showed the best balance between sensitivity and specificity regarding the diagnosis of metastases per patient. CAD reduces the time required for lung nodule/metastasis detection, especially for less experienced readers.

Artificial Intelligence Assisted Computational Tomographic Detection of Lung Nodules for Prognostic Cancer Examination: A Large-Scale Clinical Trial

Low-dose computed tomography (LDCT) has emerged as a standard method for detecting early-stage lung cancer. However, the tedious computer tomography (CT) slide reading, patient-by-patient check, and lack of standard criteria to determine the vague but possible nodule leads to variable outcomes of CT slide interpretation. To determine the artificial intelligence (AI)-assisted CT examination, AI algorithm-assisted CT screening was embedded in the hospital picture archiving and communication system, and a 200 person-scaled clinical trial was conducted at two medical centers. With AI algorithm-assisted CT screening, the sensitivity of detecting nodules sized 4−5 mm, 6~10 mm, 11~20 mm, and >20 mm increased by 41%, 11.2%, 10.3%, and 18.7%, respectively. Remarkably, the overall sensitivity of detecting varied nodules increased by 20.7% from 67.7% to 88.4%. Furthermore, the sensitivity increased by 18.5% from 72.5% to 91% for detecting ground glass nodules (GGN), which is challenging for radiologists and physicians. The free-response operating characteristic (FROC) AI score was ≥0.4, and the AI algorithm standalone CT screening sensitivity reached >95% with an area under the localization receiver operating characteristic curve (LROC-AUC) of >0.88. Our study demonstrates that AI algorithm-embedded CT screening significantly ameliorates tedious LDCT practices for doctors.

Deep Learning Applications in Computed Tomography Images for Pulmonary Nodule Detection and Diagnosis: A Review

Lung cancer has one of the highest mortality rates of all cancers and poses a severe threat to people’s health. Therefore, diagnosing lung nodules at an early stage is crucial to improving patient survival rates. Numerous computer-aided diagnosis (CAD) systems have been developed to detect and classify such nodules in their early stages. Currently, CAD systems for pulmonary nodules comprise data acquisition, pre-processing, lung segmentation, nodule detection, false-positive reduction, segmentation, and classification. A number of review articles have considered various components of such systems, but this review focuses on segmentation and classification parts. Specifically, categorizing segmentation parts based on lung nodule type and network architectures, i.e., general neural network and multiview convolution neural network (CNN) architecture. Moreover, this work organizes related literature for classification of parts based on nodule or non-nodule and benign or malignant. The essential CT lung datasets and evaluation metrics used in the detection and diagnosis of lung nodules have been systematically summarized as well. Thus, this review provides a baseline understanding of the topic for interested readers.

Comparison of Maximum Intensity Projection and Volume Rendering in Detecting Pulmonary Nodules on Multidetector Computed Tomography

Introduction Lung cancer is the most common cancer overall, and the foremost cause of cancer-related mortality. Almost all lung cancers evolve from pulmonary nodules. As multidetector CT (MDCT) scanners are now widely available, there is an increased rate of detection of pulmonary nodules. It is of utmost importance to evaluate pulmonary nodules to rule out the possibility of neoplastic diseases. With advancements in technology, there are various manual and automatic analytic software providing a wide range of post-processing techniques. Maximum intensity projection (MIP) and volume rendering (VR) techniques have been analyzed previously regarding pulmonary nodules but there is a scarcity of data in terms of low-density nodules. This study aims to delineate the comparison and supremacy of both techniques in terms of low-density nodules. Methodology The current prospective study was conducted from June 2019 to June 2020 in the Radiology Department at Dr. Ziauddin Hospital, Karachi. Chest CT scans were performed on 16 slice MDCT (Alexion 16 Multi-slice, Toshiba Medical System Corporation, Houston, TX). A consultant radiologist of six years experience and a postgraduate trainee of three years experience analyzed each patient on a workstation (Vitrea 6.2.0, Vital Images, Minnetonka, MN). SPSS 23.0 (SPSS Inc., Chicago, IL) was incorporated for data analysis. Data were expressed in the median and interquartile range (IQR). Data collected for this study were analyzed using analyzing the median difference in nodule count using Wilcoxon's signed-rank test. A p-value of <0.05 was considered significant. Results After informed consent, 236 patients were recruited for the study. MIP outperformed VR in terms of nodule detection and low-density nodules at each evaluated slab thicknesses (p<0.001). A 10-mm MIP was superior to all other techniques in terms of detection of pulmonary nodules and low-density nodules (p<0.001). MIP was also considered an easier technique as there was excellent inter-rater reliability and agreement. Conclusion This study is robust evidence regarding the supremacy of MIP. MIP outperformed VR on every slab thicknesses. The 10-mm MIP technique was superior to all others evaluated and was recorded to be an easier analyzing technique.

Lung Cancer Screening, Version 3.2018, NCCN Clinical Practice Guidelines in Oncology

Lung cancer is the leading cause of cancer-related mortality in the United States and worldwide. Early detection of lung cancer is an important opportunity for decreasing mortality. Data support using low-dose computed tomography (LDCT) of the chest to screen select patients who are at high risk for lung cancer. Lung screening is covered under the Affordable Care Act for individuals with high-risk factors. The Centers for Medicare & Medicaid Services (CMS) covers annual screening LDCT for appropriate Medicare beneficiaries at high risk for lung cancer if they also receive counseling and participate in shared decision-making before screening. The complete version of the NCCN Guidelines for Lung Cancer Screening provides recommendations for initial and subsequent LDCT screening and provides more detail about LDCT screening. This manuscript focuses on identifying patients at high risk for lung cancer who are candidates for LDCT of the chest and on evaluating initial screening findings.

Lung Surveillance Strategy for High-Grade Soft Tissue Sarcomas: Chest X-Ray or CT Scan?

BACKGROUND

Given the propensity for lung metastases, National Comprehensive Cancer Network guidelines recommend lung surveillance with either chest x-ray (CXR) or CT in high-grade soft tissue sarcoma. Considering survival, diagnostic sensitivity, and cost, the optimal modality is unknown.

METHODS

The US Sarcoma Collaborative database (2000 to 2016) was reviewed for patients who underwent resection of a primary high-grade soft tissue sarcoma. Primary end point was overall survival (OS). Cost analysis was performed.

RESULTS

Among 909 patients, 83% had truncal/extremity and 17% had retroperitoneal tumors. Recurrence occurred in 48%, of which 54% were lung metastases. Lung surveillance was performed with CT in 80% and CXR in 20%. Both groups were clinically similar, although CT patients had more retroperitoneal tumors and recurrences. Regardless of modality, 85% to 90% of lung metastases were detected within the first 2 years with a similar re-intervention rate. When considering age, tumor size, location, margin status, and receipt of radiation, lung metastasis was independently associated with worse OS (hazard ratio 4.26; p < 0.01) and imaging modality was not (hazard ratio 1.01; p = 0.97). Chest x-ray patients did not have an inferior 5-year OS rate compared with CT (71% vs 60%; p < 0.01). When analyzing patients in whom no lung metastases were detected, both cohorts had a similar 5-year OS rate (73% vs 74%; p = 0.42), suggesting CXR was not missing clinically relevant lung nodules. When adhering to a guideline-specified protocol for 2018 projected 4,406 cases, surveillance with CXR for 5 years results in savings of $5 million to $8 million/year to the US healthcare system.

CONCLUSIONS

In this large multicenter study, lung surveillance with CXR did not result in worse overall survival compared with CT. With considerable savings, a CXR-based protocol can optimize resource use for lung surveillance in high-grade soft tissue sarcoma; prospective trials are needed.

The configuration of DMD and the maximum intensity projection method for improving contrast in DMD-based confocal microscope

In this article, an operation strategy of digital micromirror device (DMD) and the maximum intensity projection (MIP) image processing method are proposed to improve the contrast of images in confocal microscopy. First, the configuration of DMD is demonstrated and the effect of scanning unit size on image performance is analyzed. Then, the image processing method MIP is applied. According to the MIP method, only the maximum intensity projection point of the same pixel is chosen from every image, and the maximum intensity projection point exactly corresponds to the positon where mirror is at "on" position during the scanning process in DMD-based confocal microscope system,. Thus, high contrast of images can be achieved by using MIP. Finally, experiments are conducted to verify imaging performance by changing the parameter of scanning unit size and applying a MIP image processing technique. The results show that DMD scanning unit size and MIP image processing techniques play important roles in improving image contrast. Smaller scanning unit size of DMD improves axial contrast but greatly decreases the signal to noise ratio, which thus leads to reduced image contrast. Larger scanning unit size produces a better signal to noise ratio, thus better image contrast. However, a large S will sacrifice the processing time. Therefore, DMD scanning unit size should be smaller on the premise that image contrast can be satisfied. RESEARCH HIGHLIGHTS: Effect of DMD scanning unit size setting on image contrast is analyzed and verified. The maximum intensity projection (MIP) is investigated to improve the image contrast. Experiments are conducted to verify the enhancement of the image contrast.

Evaluation of Thick-Slab Overlapping MIP Images of Contrast-Enhanced 3D T1-Weighted CUBE for Detection of Intracranial Metastases: A Pilot Study for Comparison of Lesion Detection, Interpretation Time, and Sensitivity with Nonoverlapping CUBE MIP, CUBE, and Inversion-Recovery-Prepared Fast-Spoiled Gradient Recalled Brain Volume

BACKGROUND AND PURPOSE

Early and accurate identification of cerebral metastases is important for prognostication and treatment planning although this process is often time consuming and labor intensive, especially with the hundreds of images associated with 3D volumetric imaging. This study aimed to evaluate the benefits of thick-slab overlapping MIPs constructed from contrast-enhanced T1-weighted CUBE (overlapping CUBE MIP) for the detection of brain metastases in comparison with traditional CUBE and inversion-recovery prepared fast-spoiled gradient recalled brain volume (IR-FSPGR-BRAVO) and nonoverlapping CUBE MIP.

MATERIALS AND METHODS

A retrospective review of 48 patients with cerebral metastases was performed at our institution from June 2016 to October 2017. Brain MRIs, which were acquired on multiple 3T scanners, included gadolinium-enhanced T1-weighted IR-FSPGR-BRAVO and CUBE, with subsequent generation of nonoverlapping CUBE MIP and overlapping CUBE MIP. Two blinded radiologists identified the total number and location of metastases on each image type. The Cohen κ was used to determine interrater agreement. Sensitivity, interpretation time, and lesion contrast-to-noise ratio were assessed.

RESULTS

Interrater agreement for identification of metastases was fair-to-moderate for all image types (κ = 0.222-0.598). The total number of metastases identified was not significantly different across the image types. Interpretation time for CUBE MIPs was significantly shorter than for CUBE and IR-FSPGR-BRAVO, saving at least 50 seconds per case on average (P < .001). The mean lesion contrast-to-noise ratio for both CUBE MIPs was higher than for IR-FSPGR-BRAVO. The mean contrast-to-noise ratio for small lesions (<4 mm) was lower for nonoverlapping CUBE MIP (1.55) than for overlapping CUBE MIP (2.35). For both readers, the sensitivity for lesion detection was high for all image types but highest for overlapping CUBE MIP and CUBE (0.93-0.97).

CONCLUSIONS

This study suggests that the use of overlapping CUBE MIP or nonoverlapping CUBE MIP for the detection of brain metastases can reduce interpretation time without sacrificing sensitivity, though the contrast-to-noise ratio of lesions is highest for overlapping CUBE MIP.

Lung cancer screening: nodule identification and characterization

The accurate identification and characterization of small pulmonary nodules at low-dose CT is an essential requirement for the implementation of effective lung cancer screening. Individual reader detection performance is influenced by nodule characteristics and technical CT parameters but can be improved by training, the application of CT techniques, and by computer-aided techniques. However, the evaluation of nodule detection in lung cancer screening trials differs from the assessment of individual readers as it incorporates multiple readers, their inter-observer variability, reporting thresholds, and reflects the program accuracy in identifying lung cancer. Understanding detection and interpretation errors in screening trials aids in the implementation of lung cancer screening in clinical practice. Indeed, as CT screening moves to ever lower radiation doses, radiologists must be cognisant of new technical challenges in nodule assessment. Screen detected lung cancers demonstrate distinct morphological features from incidentally or symptomatically detected lung cancers. Hence characterization of screen detected nodules requires an awareness of emerging concepts in early lung cancer appearances and their impact on radiological assessment and malignancy prediction models. Ultimately many nodules remain indeterminate, but further imaging evaluation can be appropriate with judicious utilization of contrast enhanced CT or MRI techniques or functional evaluation by PET-CT.

Interval lung cancer after a negative CT screening examination: CT findings and outcomes in National Lung Screening Trial participants

OBJECTIVES

This study retrospectively analyses the screening CT examinations and outcomes of the National Lung Screening Trial (NLST) participants who had interval lung cancer diagnosed within 1 year after a negative CT screen and before the next annual screen.

METHODS

The screening CTs of all 44 participants diagnosed with interval lung cancer (cases) were matched with negative CT screens of participants who did not develop lung cancer (controls). A majority consensus process was used to classify each CT screen as positive or negative according to the NLST criteria and to estimate the likelihood that any abnormalities detected retrospectively were due to lung cancer.

RESULTS

By retrospective review, 40/44 cases (91%) and 17/44 controls (39%) met the NLST criteria for a positive screen (P < 0.001). Cases had higher estimated likelihood of lung cancer (P < 0.001). Abnormalities included pulmonary nodules ≥4 mm (n = 16), mediastinal (n = 8) and hilar (n = 6) masses, and bronchial lesions (n = 6). Cancers were stage III or IV at diagnosis in 32/44 cases (73%); 37/44 patients (84%) died of lung cancer, compared to 225/649 (35%) for all screen-detected cancers (P < 0.0001).

CONCLUSION

Most cases met the NLST criteria for a positive screen. Awareness of missed abnormalities and interpretation errors may aid lung cancer identification in CT screening.

KEY POINTS

• Lung cancer within a year of a negative CT screen was rare. • Abnormalities likely due to lung cancer were identified retrospectively in most patients. • Awareness of error types may help identify lung cancer sooner.

Adaptive iterative dose reduction 3D (AIDR 3D) vs. filtered back projection: radiation dose reduction capabilities of wide volume and helical scanning techniques on area-detector CT in a chest phantom study

BACKGROUND

Computed tomography (CT) has important roles for lung cancer screening, and therefore radiation dose reduction by using iterative reconstruction technique and scanning methods receive widespread attention.

PURPOSE

To evaluate the effect of two reconstruction techniques (filtered back projection [FBP] and adaptive iterative dose reduction using three-dimensional processing [AIDR 3D]) and two acquisition techniques (wide-volume scan [WVS] and helical scan as 64-detector-row CT [64HS]) on the lung nodule identifications of using a chest phantom.

MATERIAL AND METHODS

A chest CT phantom including lung nodules was scanned using WVS and 64HS at nine different tube currents (TCs; range, 270-10 mA). All CT datasets were reconstructed with AIDR 3D and FBP. Standard deviation (SD) measurements by region of interest placement and qualitative nodule identifications were statistically compared. 64HS and WVS were evaluated separately, and FBP images acquired with 270 mA was defined as the standard reference.

RESULTS

SDs of all datasets with AIDR 3D showed no significant differences (P > 0.05) with standard reference. When comparing nodule identifications, area under the curve on WVS with AIDR 3D with TC <30 mA, on 64HS with AIDR 3D with TC <40 mA, and on reconstructions with FBP and each scan method with TC <60 mA was significantly lower than with standard reference (P < 0.05). With the same TC and reconstruction, SDs and nodule identifications of WVS were not significantly different from 64HS (P > 0.05).

CONCLUSION

In term of SD of lung parenchyma and nodule identification, AIDR 3D can achieve more radiation dose reduction than FBP and there is no significant different between WVS and 64HS.

Advanced imaging tools in pulmonary nodule detection and surveillance

Lung cancer is a leading cause of death worldwide. The National Lung Screening Trial has demonstrated that lung cancer screening can reduce lung cancer specific and all cause mortality. With approval of national coverage for lung cancer screening, it is expected that an increase in exams related to pulmonary nodule detection and surveillance will ensue. Advanced imaging technologies for nodule detection and surveillance will be more important than ever. While computed tomography (CT) remains the modality of choice, other emerging modalities such as magnetic resonance imaging provides viable alternatives to CT.

CT Imaging of Interstitial Lung Diseases

Until today, computed tomography (CT) is the most important and valuable radiological modality to detect, analyze, and diagnose diffuse interstitial lung diseases (DILD), based on the unsurpassed morphological detail provided by high-resolution CT technique.

In the past decade, there has been a shift from an isolated histopathological diagnosis to a multidisciplinary acquired diagnosis consensus that is nowadays regarded to provide the highest level of diagnostic accuracy in patients with diffuse interstitial lung diseases. The 2002 ATS/ERS statement on classification of idiopathic interstitial pneumonias assigned a central role to high-resolution CT (HRCT) in the diagnostic workup of idiopathic interstitial pneumonias (ATS/ERS consensus classification 2002). The more recent 2013 ERS/ATS statement reinforced that combined clinical data (presentation, exposures, smoking status, associated diseases, lung function, and laboratory findings) and radiological findings are essential for a multidisciplinary diagnosis (Travis et al., Am J Respir Crit Care Med 188(6):733–748, 2013).

The traditional HRCT consisted of discontinuous 1 mm high-resolution axial slices. The primary focus was on visual pattern analysis demanding for the highest possible spatial resolution. Because of the intrinsic high structural contrast of the lung, it has been possible to substantially reduce dose without losing diagnostic information. This development has been supported by new detection and reconstruction techniques. Not only detection of subtle disease and visual comparison of disease stage but also disease classification and quantification nowadays take advantage of continuous volumetric data acquisition provided by multidetector row (MD) CT technique. The following book chapter will focus on acquisition technique with special emphasis on dose and reconstruction, advantages, and new diagnostic options of volumetric MDCT technique for interstitial lung diseases. Based on evidence from the literature, certain diseases will be covered more specifically, but it has to be noted that for the pattern analysis of the various interstitial lung diseases, the plethora of other publications and books is recommended.

Lung nodule and cancer detection in computed tomography screening

Fundamental to the diagnosis of lung cancer in computed tomography (CT) scans is the detection and interpretation of lung nodules. As the capabilities of CT scanners have advanced, higher levels of spatial resolution reveal tinier lung abnormalities. Not all detected lung nodules should be reported; however, radiologists strive to detect all nodules that might have relevance to cancer diagnosis. Although medium to large lung nodules are detected consistently, interreader agreement and reader sensitivity for lung nodule detection diminish substantially as the nodule size falls below 8 to 10 mm. The difficulty in establishing an absolute reference standard presents a challenge to the reliability of studies performed to evaluate lung nodule detection. In the interest of improving detection performance, investigators are using eye tracking to analyze the effectiveness with which radiologists search CT scans relative to their ability to recognize nodules within their search path in order to determine whether strategies might exist to improve performance across readers. Beyond the viewing of transverse CT reconstructions, image processing techniques such as thin-slab maximum-intensity projections are used to substantially improve reader performance. Finally, the development of computer-aided detection has continued to evolve with the expectation that one day it will serve routinely as a tireless partner to the radiologist to enhance detection performance without significant prolongation of the interpretive process. This review provides an introduction to the current understanding of these varied issues as we enter the era of widespread lung cancer screening.

A comparison of axial versus coronal image viewing in computer-aided detection of lung nodules on CT

PURPOSE

To compare primarily viewing axial images (Axial mode) versus coronal reconstruction images (Coronal mode) in computer-aided detection (CAD) of lung nodules on multidetector computed tomography (CT) in terms of detection performance and reading time.

MATERIALS AND METHODS

Sixty CT data sets from two institutions were collected prospectively. Ten observers (6 radiologists, 4 pulmonologists) with varying degrees of experience interpreted the data sets using CAD as a second reader (performing nodule detection first without then with aid). The data sets were interpreted twice, once each for Axial and Coronal modes, in two sessions held 4 weeks apart. Jackknife free-response receiver-operating characteristic analysis was used to compare detection performances in the two modes.

RESULTS

Mean figure-of-merit values with and without aid were 0.717 and 0.684 in Axial mode and 0.702 and 0.671 in Coronal mode; use of CAD significantly increased the performance of observers in both modes (P < 0.01). Mean reading times for radiologists did not significantly differ between Axial (156 ± 74 s) and Coronal mode (164 ± 69 s; P = 0.08). Mean reading times for pulmonologists were significantly lower in Coronal (112 ± 53 s) than in Axial mode (130 ± 80 s; P < 0.01).

CONCLUSION

There was no statistically significant difference between Axial and Coronal modes for lung nodule detection with CAD.

Picture the future: emerging imaging modalities

The past century has witnessed accelerated development in imaging modalities. Better anatomical visualisation and improved data analysis have improved survival rates. Through emerging functional, molecular and structural imaging modalities, better anatomical visualisation has been extended to cellular and molecular detail, improving diagnosis and management of diseases. This article reviews the advances made in emerging imaging modalities as well as their potential applications in targeted therapy.

Evaluation and management of pulmonary nodules: state-of-the-art and future perspectives

INTRODUCTION

The imaging evaluation of pulmonary nodules, often incidentally detected on imaging examinations performed for other clinical reasons, is a frequently encountered clinical circumstance. With advances in imaging modalities, both the detection and characterization of pulmonary nodules continue to evolve and improve.

AREAS COVERED

This article will review the imaging modalities used to detect and diagnose benign and malignant pulmonary nodules, with a focus on computed tomography (CT), which continues to be the mainstay for evaluation. The authors discuss recent advances in the lung nodule management, and an algorithm for the management of indeterminate pulmonary nodules.

EXPERT OPINION

There are set of criteria that define a benign nodule, the most important of which are the lack of temporal change for 2 years or more, and certain benign imaging criteria, including specific patterns of calcification or the presence of fat. Although some indeterminate pulmonary nodules are immediately actionable, generally those approaching 1 cm or larger in diameter, at which size the diagnostic accuracy of tools such as positron emission tomography (PET)/CT, single photon emission CT (SPECT) and biopsy techniques are sufficient to warrant their use. The majority of indeterminate pulmonary nodules are under 1 cm, for which serial CT examinations through at least 2 years for solid nodules and 3 years for ground-glass nodules, are used to demonstrate either benign biologic behavior or otherwise. The management of incidental pulmonary nodules involves a multidisciplinary approach in which radiology plays a pivotal role. Newer imaging and postprocessing techniques have made this a more accurate technique eliminating ambiguity and unnecessary follow-up.

Comparison of chest dual-energy subtraction digital tomosynthesis and dual-energy subtraction radiography for detection of pulmonary nodules: initial evaluations in human clinical cases

RATIONALE AND OBJECTIVES

To compare initial evaluations of chest dual-energy subtraction digital tomosynthesis (DES-DT) and dual-energy subtraction radiography (DES-R) for detection of pulmonary nodules.

MATERIALS AND METHODS

DES-DT and DES-R systems with pulsed x-rays and rapid kV switching were used to evaluate pulmonary nodules (>4-6 mm, 2 nodules; >6-8 mm, 2 nodules; >8 mm, 32 nodules). Multidetector computed tomography was used as a reference. A filtered back-projection algorithm was used to reconstruct low-voltage (60 kVp), high-voltage (120 kVp), and soft-tissue or bone-subtracted tomograms of the desired layer thicknesses from the image data acquired during a single tomographic scan. DES-R images were processed from the low- and high-voltage images. To detect the pulmonary nodules, we used both systems to examine 36 patients with and 36 patients without pulmonary nodules. Two radiologists and three doctors of pulmonary medicine (average experience, 18 years) performed receiver operating characteristic (ROC) curve analysis to evaluate the results.

RESULTS

The ROC analysis results suggested that the detection ability was significantly better for DES-DT than for DES-R (P < .0001; 95% confidence interval: DES-DT, 0.94 [0.83-0.99]; DES-R, 0.76 [0.68-0.85]; sensitivity: DES-DT, 87.7 ± 2.9%; DES-R, 53.8 ± 3.5%; specificity: DES-DT, 78.3 ± 5.6%; DES-R, 78.4 ± 3.4%; accuracy: DES-DT, 83.1 ± 3.8%, DES-R, 66.1 ± 2.0%). When the nodules were no longer superimposed over the normal structures, their characteristics and distribution could be observed much more clearly.

CONCLUSION

Compared with DES-R, DES-DT provided greater sensitivity for detection of pulmonary nodules, particularly for the larger ones.

Detection of pulmonary nodules at paediatric CT: maximum intensity projections and axial source images are complementary

BACKGROUND

Maximum intensity projection (MIP) images might be useful in helping to differentiate small pulmonary nodules from adjacent vessels on thoracic multidetector CT (MDCT).

OBJECTIVE

The aim was to evaluate the benefits of axial MIP images over axial source images for the paediatric chest in an interobserver variability study.

MATERIALS AND METHODS

We included 46 children with extra-pulmonary solid organ malignancy who had undergone thoracic MDCT. Three radiologists independently read 2-mm axial and 10-mm MIP image datasets, recording the number of nodules, size and location, overall time taken and confidence.

RESULTS

There were 83 nodules (249 total reads among three readers) in 46 children (mean age 10.4 ± 4.98 years, range 0.3-15.9 years; 24 boys). Consensus read was used as the reference standard. Overall, three readers recorded significantly more nodules on MIP images (228 vs. 174; P < 0.05), improving sensitivity from 67% to 77.5% (P < 0.05) but with lower positive predictive value (96% vs. 85%, P < 0.005). MIP images took significantly less time to read (71.6 ± 43.7 s vs. 92.9 ± 48.7 s; P < 0.005) but did not improve confidence levels.

CONCLUSION

Using 10-mm axial MIP images for nodule detection in the paediatric chest enhances diagnostic performance, improving sensitivity and reducing reading time when compared with conventional axial thin-slice images. Axial MIP and axial source images are complementary in thoracic nodule detection.

Non-solid lung nodules on low-dose computed tomography: comparison of detection rate between 3 visualization techniques

Objective: To compare various visualization techniques for the detection of non-solid nodules in low-dose lung cancer screening computed tomography (CT) scans. Methods: An enriched sample of 216 male lung cancer screening subjects aged 60.4 ± 6.0 years was used. Two blinded independent readers searched for non-solid nodules on 5-mm multiplanar reconstructions, 1-mm slices and 7-mm maximum intensity projections (trial protocol). The reference standard was a consensus diagnosis of all non-solid nodules reported at least once. Results: Twenty-three individuals (10.6%) had in total 34 non-solid nodules. Interobserver agreement was good (Cohen kappa 0.89–0.95). For both observers, we found no differences between the 3 viewing techniques (P > 0.13). Conclusion: In low-dose lung cancer screening CT scans, we were unable to find a viewing technique superior to that used in the trial by experienced observers who focused on non-solid nodule detection.

Technical developments in postprocessing of paediatric airway imaging

CT postprocessing allows more scan information to be viewed at one time allowing an accurate diagnosis to be made more efficiently, and is particularly important in paediatric practice where invasive clinical diagnostic tools can be replaced or at least assisted by modern postprocessing techniques. Four visualization techniques in clinical use are described in this paper including the advantages and disadvantages of each: multiplanar reformation, maximum and minimum intensity projections, shaded surface display and volume rendering. Volume-rendered internal visualization in the form of virtual endoscopy is also discussed. In addition, the clinical usefulness in paediatric practice of demonstrating airway compression and its causes are discussed. Advanced postprocessing techniques that must still find their way from the biomedical research environment into clinical use are introduced with specific reference to computer-aided diagnosis.

A radial structure tensor and its use for shape-encoding medical visualization of tubular and nodular structures

The concept of curvature and shape-based rendering is beneficial for medical visualization of CT and MRI image volumes. Color-coding of local shape properties derived from the analysis of the local Hessian can implicitly highlight tubular structures such as vessels and airways, and guide the attention to potentially malignant nodular structures such as tumors, enlarged lymph nodes, or aneurysms. For some clinical applications, however, the evaluation of the Hessian matrix does not yield satisfactory renderings, in particular for hollow structures such as airways, and densely embedded low contrast structures such as lymph nodes. Therefore, as a complement to Hessian-based shape-encoding rendering, this paper introduces a combination of an efficient sparse radial gradient sampling scheme in conjunction with a novel representation, the radial structure tensor (RST). As an extension of the well-known general structure tensor, which has only positive definite eigenvalues, the radial structure tensor correlates position and direction of the gradient vectors in a local neighborhood, and thus yields positive and negative eigenvalues which can be used to discriminate between different shapes. As Hessian-based rendering, also RST-based rendering is ideally suited for GPU implementation. Feedback from clinicians indicates that shape-encoding rendering can be an effective image navigation tool to aid diagnostic workflow and quality assurance.

Flat-panel detector computed tomography imaging: observer performance in detecting pulmonary nodules in comparison with conventional chest radiography and multidetector computed tomography

PURPOSE

The aim of this study was to compare the detectability of lung nodules on images obtained with a flat-panel detector computed tomography (FPD-CT) system and by chest radiographs (CXRs) using receiver-operating characteristic (ROC) analysis.

MATERIALS AND METHODS

FPD-CT was conducted with the patients in the sitting position. For the CXR study, the patients stood erect. Our study population consisted of 26 individuals ranging in age from 50 to 83 years. The reference standard was based on the interpretations obtained by consensus of 2 radiologists on multidetector CT images for the presence or absence of nodules. Four other radiologists independently assessed and recorded the absence or presence of lung nodules and their location on FPD-CT and CXR images. ROC analysis was used to evaluate lung nodule detectability by both imaging modalities.

RESULTS

Two radiologists identified 34 nodules whose diameter was 5 to 42 mm (mean, 19.3 mm) in 23 of the 26 study participants on the multidetector CT images. Overall, analysis of variance for ROC analysis showed that FPD-CT was significantly better in detecting nodules than CXR (P=0.02). The estimated mean Az value was 0.9818±0.0083 with FPD-CT and 0.7610±0.0908 with CXR. The sensitivity for nodule detection on FPD-CT and CXR images was 79.4% and 33.8%, respectively.

CONCLUSION

The detectability of pulmonary nodules was better on images of FPD-CT than on CXRs.

Evaluating the growth of pulmonary nodular ground-glass opacity on CT: comparison of volume rendering and thin slice images

This study examined the value of volume rendering (VR) interpretation in assessing the growth of pulmonary nodular ground-glass opacity (nGGO). A total of 47 nGGOs (average size, 9.5 mm; range, 5.7-20.6 mm) were observed by CT scanning at different time under identical parameter settings. The growth of nGGO was analyzed by three radiologists by comparing the thin slice (TS) CT images of initial and repeat scans with side-by-side cine mode. One week later synchronized VR images of the two scans were compared by side-by-side cine mode to evaluate the nGGO growth. The nodule growth was rated on a 5-degree scale: notable growth, slight growth, dubious growth, stagnant growth, shrinkage. Growth standard was defined as: Density increase ≥ 30 HU and (or) diameter increase (by 20% in nodules ≥ 10 mm, 30% in nodules of 5-9 mm). Receiver operating characteristic (ROC) was performed. The results showed that 32 nGGOs met the growth criteria (29 nGGOs showed an increase in density; 1 nGGO showed an increase in diameter; 2 nGGOs showed an increase in both diameter and density). Area under ROC curve revealed that the performance with VR interpretation was better than that with TS interpretation (P<0.01, P<0.05 and P<0.05 for observers A, B and C respectively). Consistency between different observers was excellent with both VR interpretation (κ=0.89 for observers A&C, A&B, B&C) and TS interpretation (κ=0.71 for A&B, κ=0.68 for A&C, κ= 0.74 for B&C), but time spending was less with VR interpretation than with TS interpretation (P<0.0001, P<0.0001 and P<0.05 for observers A, B and C, respectively). It was concluded that VR is a useful technique for evaluating the growth of nGGO.

The diagnostic contribution of CT volumetric rendering techniques in routine practice

Computed tomography (CT) volumetric rendering techniques such as maximum intensity projection (MIP), minimum intensity projection (MinIP), shaded surface display (SSD), volume rendering (VR), and virtual endoscopy (VE) provide added diagnostic capabilities. The diagnostic value of such reconstruction techniques is well documented in literature. These techniques permit the exploration of fine anatomical detail that would be difficult to evaluate using axial reconstructions alone. Although these techniques are now widely available, many radiologists are either unfamiliar with them or do not fully utilize their potential in daily clinical practice. This paper is intended to provide an overview of the most common CT volumetric rendering techniques and their practical use in everyday diagnostics.

Comparing and combining algorithms for computer-aided detection of pulmonary nodules in computed tomography scans: The ANODE09 study

Numerous publications and commercial systems are available that deal with automatic detection of pulmonary nodules in thoracic computed tomography scans, but a comparative study where many systems are applied to the same data set has not yet been performed. This paper introduces ANODE09 ( http://anode09.isi.uu.nl), a database of 55 scans from a lung cancer screening program and a web-based framework for objective evaluation of nodule detection algorithms. Any team can upload results to facilitate benchmarking. The performance of six algorithms for which results are available are compared; five from academic groups and one commercially available system. A method to combine the output of multiple systems is proposed. Results show a substantial performance difference between algorithms, and demonstrate that combining the output of algorithms leads to marked performance improvements.

Observer accuracy in the detection of pulmonary nodules on CT: effect of cine frame rate

AIM

To assess the effect of cine frame rate on the accuracy of the detection of pulmonary nodules at computed tomography (CT).

MATERIALS AND METHODS

CT images of 15 consecutive patients with (n = 13) or without (n = 2) pulmonary metastases were identified. Initial assessment by two thoracic radiologists provided the "actual" or reference reading. Subsequently, 10 radiologists [board certified radiologists (n = 4) or radiology residents (n = 6)] used different fixed cine frame rates for nodule detection. Within-subjects analysis of variance (ANOVA) was used to evaluate the data.

RESULTS

Eighty-nine nodules were identified by the thoracic radiologists (median 8, range 0-29 per patient; median diameter 9 mm, range 4-40 mm). There was a non-statistically significant trend to reduced accuracy at higher frame rates (p=0.113) with no statistically significant difference between experienced observers and residents (p = 0.79).

CONCLUSION

The accuracy of pulmonary nodule detection at higher cine frame rates is reduced, unrelated to observer experience.

Incidentally detected small pulmonary nodules on CT

The widespread use of multidetector computed tomography for imaging of the chest has lead to a significant increase in the number of incidentally detected pulmonary nodules. The significance of these nodules is often uncertain and further investigations may be required. This article will review the spectrum of imaging appearances of small pulmonary nodules, and highlight the few features that allow confident characterization of a nodule as benign or malignant; current guidelines for the management of incidentally detected nodules will also be discussed.

Comparing three-dimensional volume-rendered CT images with fibreoptic tracheobronchoscopy in the evaluation of airway compression caused by tuberculous lymphadenopathy in children

BACKGROUND

Lymphobronchial tuberculosis (TB) causes airway compression in 38% of patients. The airway obstruction is conventionally assessed with fibreoptic tracheobronchoscopy (FTB). Multidetector-row spiral computed tomography (MDCT) with three-dimensional volume rendering (3-D VR) has significantly improved the imaging of the airways. No previous studies have assessed the accuracy of 3-D VR in determining the degree of airway compression in children due to TB lymphadenopathy.

OBJECTIVE

To compare 3-D VR CT to FTB for the assessment of airway compression due to TB lymphadenopathy in children.

MATERIALS AND METHODS

Included in the study were 26 children presenting with symptoms of airway compression caused by pulmonary TB. MDCT of the chest and FTB were performed in all patients. Retrospective 3-D VR reconstruction of the major airways was performed from the original CT raw data and used to evaluate the tracheobronchial tree for site and degree of airway compression and then compared to the FTB findings. FTB was used as the reference standard

RESULTS

By FTB 87 sites of airway compression were identified. Using the 3-D VR technique, 138 sites of airway compression were identified, of which 78 (90%) matched with the sites identified by FTB. The sensitivity and specificity of 3-D VR when compared with that of FTB was 92% and 85%, respectively. In four patients (15%), severe narrowing of the bronchus intermedius made FTB evaluation of the right middle and right lower lobe bronchi impossible. VR demonstrated significant distal obstruction in three of these four patients

CONCLUSION

3-D VR demonstrates a very good correlation with FTB in determining airway compression caused by TB lymphadenopathy in children. In combination with FTB, 3-D VR adds confidence to the bronchoscopy findings and complements FTB by adding additional information on the status of the airway distal to severe obstructions unreachable by FTB.

Efficacy of computer-aided detection system and thin-slab maximum intensity projection technique in the detection of pulmonary nodules in patients with resected metastases

OBJECTIVES

To evaluate the efficacy of the computer-aided detection (CAD) system and thin-slab maximum intensity projection (MIP) technique in the detection of pulmonary nodules at multidetector computed tomography (CT) in patients who underwent metastatectomy.

MATERIALS AND METHODS

This retrospective study was approved by the institutional review board and patients' informed consent was waived. Forty-nine consecutive patients who underwent pulmonary metastatectomy were enrolled. Four chest radiologists analyzed preoperative 1-mm section CT images and recorded the locus of each nodule candidate. Afterward, they reevaluated the images once using CAD software and once with thin-slab MIP given the results of 1-mm section CT alone. The reference standard for nodule presence was established by a consensus panel and pathologic records for malignant nodules.

RESULTS

A total of 514 nodules were identified by a consensus panel. Of 212 nodules surgically removed, 121 nodules were malignant. The sensitivity of each observer in detecting malignant nodules with thin-section CT scans alone was 91%, 88%, 87%, and 86% for observers A- to D, respectively. With CAD, sensitivity increased significantly to 95%, 95%, 94%, and 95% (P< 0.05 for observer B-D), and using MIP increased to 94%, 96%, 91%, and 92% (P < 0.05 for observer B-D), respectively. There were no significant differences in sensitivity between CAD and MIP for the detection of malignant nodules. The average number of false-positive findings per patient was 0.8 with thin-section CT alone, 1.1 with CAD, and 1.4 with MIP.

CONCLUSIONS

In candidates for metastatectomy, reading with the aid of either CAD or MIP significantly improved the detection of malignant nodules compared with using thin-section CT alone.

Effect of slab thickness on the CT detection of pulmonary nodules: use of sliding thin-slab maximum intensity projection and volume rendering

OBJECTIVE

The objective of this study was to evaluate the detection rates of pulmonary nodules on CT as a function of slab thickness using sliding thin-slab maximum intensity projection (MIP) and volume rendering (VR).

SUBJECTS AND METHODS

Eighty-eight oncology patients (33 women, 55 men; mean age, 59 years; age range, 18-81 years) who routinely underwent chest CT examinations were prospectively included. Two radiologists independently evaluated each CT examination for the presence of pulmonary nodules using MIP and VR, with each image reconstructed using three different slab thicknesses (5, 8, 11 mm). The standard of reference was the maximum number of detected nodules, which were classified by localization and size, judged to be true-positives by a consensus panel. Interreader agreement was assessed by kappa value on a nodule-by-nodule basis. Sensitivities for both reconstruction techniques and for the three slab thicknesses were calculated using the proportion procedure for survey data with the patient as the primary sample unit and were compared using the Wilcoxon's signed rank test with Bonferroni correction for both readers separately.

RESULTS

One thousand fifty-eight true-positive nodules were detected. Interreader agreement was fair to moderate. Sensitivity for pulmonary nodules was superior for 8-mm MIP (reader 1, 84%; reader 2, 81%) and was significantly better than the sensitivities of all other tested techniques for both readers (p < 0.001 each) independent of nodule localization and size (except for one reader's analysis of 8-mm MIP versus 11-mm MIP for nodules > 8 mm). A higher sensitivity was achieved using MIP than VR.

CONCLUSION

MIP with a slab thickness of 8 mm is superior in the detection of pulmonary nodules to all other tested techniques.

Multi slice computed tomography in the study of pulmonary metastases

PURPOSE

This study was undertaken to assess the performance of 16-slice computed tomography (MSCT) using Multi-Planar Reformatting (MPR), Maximum Intensity Projection (MIP) and Volume Rendering (VR) reconstructions to study pulmonary metastases.

MATERIALS AND METHODS

CT studies of 32 patients with pulmonary metastases were retrospectively reviewed. Images were assessed for the following parameters: number, size, location, distribution of the nodules and the presence of the "mass-vessel sign". These parameters were evaluated by two observers on axial-source images and on MPR, MIP and VR reconstructions. Sensitivity of each reconstruction and interobserver agreement were calculated.

RESULTS

Two-dimensional (2D) axial images and MIP and VR reconstructions exhibited 100% sensitivity for lesions >10 mm. For nodules 6-10 mm, sensitivity was 49%-55% for the 2D images, 90% for MIP and 80%-85% for VR reconstructions. For metastasis <or= 5 mm, sensitivity was 22% for 2D images, 87%-89% for MIP and 55%-58% for VR reconstructions. Coronal and sagittal MPR, MIP and VR did not improve the detection rate compared with the corresponding axial images. MIP and VR provided overlapping results in detecting the "mass-vessel sign".

CONCLUSIONS

MIP are the most sensitive reconstructions for detecting small pulmonary nodules.

Improved visualization of artificial pulmonary nodules with a new subvolume rendering technique

BACKGROUND

The detection of small nodules in pulmonary multidetector computed tomography (MDCT) data sets is challenging, and there is a need for visualization techniques that can improve reader sensitivity and efficiency. We have developed a subvolume rendering technique ("Softslice") with nonlinear, symmetrical modulation of the relative signal intensity along the viewing direction. Our hypothesis was that this technique might provide an advantageous visual differentiation between nodules and overlapping vessels in pulmonary MDCT subvolumes.

PURPOSE

To compare the Softslice subvolume rendering technique and maximum intensity projection (MIP) rendering for visualization of artificial pulmonary nodules in MDCT data sets.

MATERIAL AND METHODS

Virtual, artificial pulmonary nodules were created with custom-made software. The nodules had the same signal intensity as pulmonary vessels. Approximately 50 nodules with diameter 2-7 mm were inserted in the Digital Imaging and Communications in Medicine (DICOM) image files of pulmonary MDCT data sets obtained without intravenous contrast. Each data set contained approximately 300 slices with 1-mm slice spacing. Four types of subvolumes were rendered: MIP with 10- and 20-mm subvolume thickness, and Softslice with 20- and 30-mm subvolume thickness. Three radiologists performed readings with free scrolling using 1-, 4- or 8-mm increments between subvolume positions.

RESULTS

No significant differences in the number of detected nodules were found between the different renderings with free scrolling using 1- and 4-mm increments. When 8-mm increment was used, nodule detection with the 30-mm Softslice rendering was significantly superior to the other renderings (P = 0.012 vs. MIP 10 mm, P = 0.018 vs. MIP 20 mm, P = 0.021 vs. Softslice 20 mm). When the subvolume increments were changed from 4 mm to 8 mm, the most marked reduction in the number of detected nodules was seen for MIP subvolumes with 10-mm thickness (P = 0.018).

CONCLUSION

The Softslice rendering technique is promising for the detection of pulmonary nodules in MDCT data sets, and may allow more efficient reading than the standard MIP subvolume technique. With 10-mm MIP rendering, the detection rate for small pulmonary nodules substantially influenced by the incremental distance between subvolumes positions.

Influence of detector collimation and beam pitch for identification and image quality of ground-glass attenuation and nodules on 16- and 64-detector row CT systems: Experimental study using chest phantom

OBJECTIVE

The purpose of the present study was to determine the influence of detector collimation and beam pitch for identification and image quality of ground-glass attenuation (GGA) and nodules on 16- and 64-detector row CTs, by using a commercially available chest phantom.

MATERIALS AND METHODS

A chest CT phantom including simulated GGAs and nodules was scanned with different detector collimations, beam pitches and tube currents. The probability and image quality of each simulated abnormality was visually assessed with a five-point scoring system. ROC-analysis and ANOVA were then performed to compare the identification and image quality of either protocol with standard values.

RESULTS

Detection rates of low-dose CTs were significantly reduced when tube currents were set at 40mA or less by using detector collimation 16 and 64x0.5mm and 16 and 32mmx1.0mm for low pitch, and at 100mA or less by using detector collimation 16 and 64x0.5mm and 16 and 32mmx1.0mm for high pitch (p<0.05). Image qualities of low-dose CTs deteriorated significantly when tube current was set at 100mA or less by using detector collimation 16 and 64x0.5mm and 16 and 32x1.0mm for low pitch, and at 150mA or less by using detector collimation 16 and 64x0.5mm and 16 and 32x1.0mm for high pitch (p<0.05).

CONCLUSION

Detector collimation and beam pitch were important factors for the image quality and identification of GGA and nodules by 16- and 64-detector row CT.