Automated detection of pulmonary nodules on CT images: effect of section thickness and reconstruction interval--initial results

Institutional review board approval was obtained. Informed patient consent was not required. Study was compliant with HIPAA. Performance of an automated pulmonary nodule detection program was evaluated on multi-detector row CT images that were acquired once but reconstructed retrospectively at different section thicknesses and reconstruction intervals. From raw CT data in 10 patients with pulmonary nodules, three sets of CT images were reconstructed separately in each patient by selecting two section thickness and reconstruction combinations, respectively: thin group, 1 and 1 mm; overlap group, 5 and 1 mm; and thick group, 5 and 5 mm. Nodules 3 mm in diameter and larger were detected in each group (thin group, 126 nodules; overlap group, 121 nodules; and thick group, 114 nodules) by means of consensus of two radiologists. Findings were used as the reference standard for evaluation of the computer-aided detection (CAD) program. Sensitivity and number of false-positive findings per patient by CAD were: thin group, 95.2% (120 of 126 nodules) and 5.4 findings; overlap group, 94.2% (114 of 121 nodules) and 9.7 findings; and thick group, 88.6% (101 of 114 nodules) and 23.6 findings, indicating that nodule detection degraded with increase in section thickness but improved substantially with a small reconstruction interval.     

Automated volumetry of solid pulmonary nodules in a phantom: accuracy across different CT scanner technologies

OBJECTIVES: The accuracy of automated volumetry for pulmonary nodules in a phantom using different CT scanner technologies from single-slice spiral CT (SSCT) to 64-slice multidetector-row CT (MDCT) was compared. MATERIALS AND METHODS: A lung phantom with 5 different categories of pulmonary nodules was scanned using a single-slice spiral CT, a 4-slice MDCT, a 16-slice MDCT and a 64-slice MDCT. Each category comprised of 7-9 nodules each (total n = 40) with different known volumes. Standard dose and low dose protocols were performed using thin and thick collimation. Image data were reconstructed at the thinnest slice thickness. Data sets were analyzed with a dedicated volumetry software. Volumes of all nodules were calculated and compared. RESULTS: Mean absolute percentage error (APE) for all nodules was 8.65% (+/-7.29%) for the SSCT, 10.26% (+/-8.25%) for the 4-slice MDCT, 8.19% (+/-7.57%) for the 16-slice MDCT and 7.89% (+/-7.39%) for the 64-slice MDCT. There was statistically significant influence of the scanner type, protocol, anatomic location, and nodule volume on APE, but overall, APEs were comparable. CONCLUSION: Computer-aided volumetry showed accurate measurements in all tested scanner types. This finding has important implications for nodule assessment and follow-up.     

Computer-aided detection and automated CT volumetry of pulmonary nodules

With use of multislice computed tomography (MSCT), small pulmonary nodules are being detected in vast numbers, constituting the majority of all noncalcified lung nodules. Although the prevalence of lung cancers among such lesions in lung cancer screening populations is low, their isolation may contribute to increased patient survival. Computer-aided diagnosis (CAD) has emerged as a diverse set of diagnostic tools to handle the large number of images in MSCT datasets and most importantly, includes automated detection and volumetry of pulmonary nodules. Current CAD systems can significantly enhance experienced radiologists’ performance and outweigh human limitations in identifying small lesions and manually measuring their diameters, augment observer consistency in the interpretation of such examinations and may thus help to detect significantly higher rates of early malignomas and give more precise estimates on chemotherapy response than can radiologists alone. In this review, we give an overview of current CAD in lung nodule detection and volumetry and discuss their relative merits and limitations.     

Solitary pulmonary nodules: optimal slice thickness of high-resolution CT in differentiating malignant from benign

The purpose of this study was to determine an optimal slice thickness that was efficient in differentiating malignant from benign solitary pulmonary nodules (SPNs) on high-resolution computed tomography (HRCT) images. For a total of 92 SPNs, four radiologist indicated their confidence level for the malignant or benign SPN on the CT images presented in 1-, 3-, and 5-mm slice thickness. HRCT could be used to differentiate more accurately the malignant nodules from the benign ones using 1-mm-thick sections than 3- or 5-mm-thick sections.     

Clinical lymph node staging-Influence of slice thickness and reconstruction kernel on volumetry and RECIST measurements

Purpose

Therapy response evaluation in oncological patient care requires reproducible and accurate image evaluation. Today, common standard in measurement of tumour growth or shrinkage is one-dimensional RECIST 1.1. A proposed alternative method for therapy monitoring is computer aided volumetric analysis. In lung metastases volumetry proved high reliability and accuracy in experimental studies. High reliability and accuracy of volumetry in lung metastases has been proven. However, other metastatic lesions such as enlarged lymph nodes are far more challenging. The aim of this study was to investigate the reproducibility of semi-automated volumetric analysis of lymph node metastases as a function of both slice thickness and reconstruction kernel. In addition, manual long axis diameters (LAD) as well as short axis diameters (SAD) were compared to automated RECIST measurements.

Materials and methods

Multislice-CT of the chest, abdomen and pelvis of 15 patients with lymph node metastases of malignant melanoma were included. Raw data were reconstructed using different slice thicknesses (1–5 mm) and varying reconstruction kernels (B20f, B40f, B60f). Volume and RECIST measurements were performed for 85 lymph nodes between 10 and 60 mm using Oncology Prototype Software (Fraunhofer MEVIS, Siemens, Germany) and were compared to a defined reference volume and diameter by calculating absolute percentage errors (APE). Variability of the lymph node sizes was computed as relative measurement differences, precision of measurements was computed as relative measurement deviation.

Results

Mean absolute percentage error (APE) for volumetric analysis varied between 3.95% and 13.8% and increased significantly with slice thickness. Differences between reconstruction kernels were not significant, however, a trend towards middle soft tissue kernel could be observed.. Between automated and manual short axis diameter (SAD, RECIST 1.1) and long axis diameter (LAD, RECIST 1.0) no significant differences were found. The most unsatisfactory segmentation results occurred in higher slice thickness (3 and 5 mm) and sharp tissue kernel.

Conclusion

Volumetric analysis of lymph nodes works satisfying in a clinical setting. Thin slice reconstructions (≤3 mm) and a middle soft tissue reconstruction kernel are recommended. LAD and SAD did not show significant differences regarding APE. Automated RECIST measurement showed lower APE than manual measurement in trend.     

自动管电流调制技术结合迭代重建算法在低剂量CT肺动脉成像中的应用

目的 探讨自动管电流调制技术结合idose4迭代重建算法在低剂量CT肺动脉成像（CTPA）中的应用价值。方法 连续收集行CTPA的受检者80例,采用随机数字表法将其分为对照组和实验组,每组40例。两组管电压均采用80 kV。对照组固定管电流为180 mAs,采用滤波反投影法重建,获得A组图像;实验组采用自动管电流调制技术,分别采用滤波反投影法和idose4迭代重建算法重建,获得B组和C组图像。统计分析A、B和C 3组的图像质量主观评分、肺动脉平均CT值、图像噪声值、肺动脉的信噪比（SNR）和对比噪声比（CNR）。比较实验组和对照组的有效剂量（E）。结果 实验组、对照组的E分别为（1.2±0.2）和（1.9±0.3）mSv,实验组的ED较对照组明显降低了36.8%（t=-3.998,P<0.05）。3组图像质量主观评分均≥3,满足临床诊断要求,且差异无统计学意义（P>0.05）。3组SNR、CNR和噪声值组间比较,差异有统计学意义（F=10.4 11、7.630、13.021,P<0.05）;而肺动脉平均CT值差异无统计学意义（P>0.05）。结论 自动管电流调制技术结合idose4迭代重建算法在低剂量CTPA检查中,在获得良好图像质量的同时,可进一步降低辐射剂量。     

Renal cyst pseudoenhancement: influence of multidetector CT reconstruction algorithm and scanner type in phantom model

PURPOSE: To prospectively determine the dependence of renal cyst pseudoenhancement on multidetector computed tomographic (CT) scanner type and convolution kernel in a phantom model. MATERIALS AND METHODS: A customized anthropomorphic phantom was created to accept interchangeable 40-, 140-, and 240-HU renal inserts that contained stacked 0- and 50-HU cylindric cysts measuring 7, 10, and 15 mm in diameter. Each phantom and insert was scanned with five different multidetector CT scanners on five separate occasions by using 120 kVp, low and high tube current settings, 3.00-3.75-mm collimation, and standard and high-spatial-resolution kernels. A total of 2340 CT attenuation measurements were obtained by using standardized regions of interest. The effect of multidetector CT imaging regimen, tube current, cyst diameter, and renal attenuation on pseudoenhancement incidence was assessed by using generalized estimating equations based on a binary logistic regression model. Within this framework, a Bonferroni multiple comparison correction was used to assess pseudoenhancement frequency differences among imaging regimens. RESULTS: Pseudoenhancement occurred in both 0- and 50-HU cysts; was significantly correlated with multidetector CT imaging regimen (P<.0001), cyst diameter (P<.0001), and renal attenuation (P.3). When convolution kernels on specific scanners were compared, significant differences (P<.04) between kernels were identified with all five scanners in terms of observed pseudoenhancement incidence. Generational differences in equipment were noted, with pseudoenhancement incidence ranging from 1.7% to 8.3%, 1.7% to 16.7%, and 18.3% to 56.7% across relevant kernels for three scanners from one manufacturer. CONCLUSION: Pseudoenhancement is strongly dependent on multidetector CT convolution kernel. Varying this parameter may mitigate this phenomenon, which is independent of volume-averaging effects.     

螺旋CT薄层扫描并MPVR重建对孤立性肺结节的诊断价值

目的:探讨螺旋CT肺薄层扫描并多层面重建对孤立性肺结节的诊断价值。方法:对86例SPN患者进行螺旋CT规范化检查,并使用多层面重建(MPVR)技术重建观察。病灶结节直径选在0.8~3.0cm,病历均经临床手术或肺穿刺活检病理证实。其中恶性59例,均为原发性肺癌,包括腺癌25例、鳞癌17例、细支气管肺泡癌10例、小细胞未分化癌7例;良性病变27例,包括结核灶13例、炎性假瘤9例、错构瘤5例。结果:86例SPN的CT征象中,分叶征和棘突或毛刺征多出现于恶性结节,与病理和随访结果对比,螺旋CT薄层扫描并MPVR重建判断肺小结节良恶性的准确率、灵敏度、特异性、阳性预测值和阴性预测值分别为75.6%、76.3%、74.1%、86.5%、58.8%。结论:SCT肺薄层扫描并MPVR重建能显示更多的SPNCT征象,对SPN的良恶性诊断有较高的诊断价值。     

CT volumetry of artificial pulmonary nodules using an ex vivo lung phantom: Influence of exposure parameters and iterative reconstruction on reproducibility

Objectives

To evaluate the influence of exposure parameters and raw-data based iterative reconstruction (IR) on the measurement variability of computer-aided nodule volumetry on chest multidetector computed tomography (MDCT).

Materials and methods

N = 7 porcine lung explants were inflated in a dedicated ex vivo phantom and prepared with n = 162 artificial nodules. MDCT was performed eight consecutive times (combinations of 120 and 80 kV with 120, 60, 30 and 12 mA s), and reconstructed with filtered back projection (FBP) and IR. Nodule volume and diameter were measured semi-automatically with dedicated software. The absolute percentage measurement error (APE) was computed in relation to the 120 kV 120 mA s acquisition. Noise was recorded for each nodule in every dataset.

Results

Mean nodule volume and diameter were 0.32 ± 0.15 ml and 12.0 ± 2.6 mm, respectively. Although IR reduced noise by 24.9% on average compared to FBP (p < 0.007), APE with IR was equal to or slightly higher than with FBP. Mean APE for volume increased significantly below a volume computed tomography dose index (CTDI) of 1.0 mGy: for 120 kV 12 mA s APE was 3.8 ± 6.2% (FBP) vs. 4.0 ± 5.2% (IR) (p < 0.007); for 80 kV 12 mA s APE was 8.0 ± 13.0% vs. 9.3 ± 15.8% (n.s.), respectively. Correlating APE with image noise revealed that at identical noise APE was higher with IR than with FBP (p < 0.05).

Conclusions

Computer-aided volumetry is robust in a wide range of exposure settings, and reproducibility is reduced at a CTDI below 1.0 mGy only, but the error rate remains clinically irrelevant. Noise reduction by IR is not detrimental for measurement error in the setting of semi-automatic nodule volumetry on chest MDCT.     

Computer-assisted lung nodule volumetry from multi-detector row CT: influence of image reconstruction parameters

PURPOSE: To investigate differences in volumetric measurement of pulmonary nodules caused by changing the reconstruction parameters for multi-detector row CT. MATERIALS AND METHODS: Thirty-nine pulmonary nodules less than 2 cm in diameter were examined by multi-slice CT. All nodules were solid, and located in the peripheral part of the lungs. The resultant 48 parameters images were reconstructed by changing slice thickness (1.25, 2.5, 3.75, or 5 mm), field of view (FOV: 10, 20, or 30 cm), algorithm (high-spatial frequency algorithm or low-spatial frequency algorithm) and reconstruction interval (reconstruction with 50% overlapping of the reconstructed slices or non-overlapping reconstruction). Volumetric measurements were calculated using commercially available software. The differences between nodule volumes were analyzed by the Kruskal-Wallis test and the Wilcoxon Signed-Ranks test. RESULTS: The diameter of the nodules was 8.7+/-2.7 mm on average, ranging from 4.3 to 16.4mm. Pulmonary nodule volume did not change significantly with changes in slice thickness or FOV (p>0.05), but was significantly larger with the high-spatial frequency algorithm than the low-spatial frequency algorithm (p<0.05), except for one reconstruction parameter. The volumes determined by non-overlapping reconstruction were significantly larger than those of overlapping reconstruction (p<0.05), except for a 1.25 mm thickness with 10 cm FOV with the high-spatial frequency algorithm, and 5mm thickness. The maximum difference in measured volume was 16% on average between the 1.25 mm slice thickness/10 cm FOV/high-spatial frequency algorithm parameters and overlapping reconstruction. CONCLUSION: Volumetric measurements of pulmonary nodules differ with changes in the reconstruction parameters, with a tendency toward larger volumes in high-spatial frequency algorithm and non-overlapping reconstruction compared to the low-spatial frequency algorithm and overlapping reconstruction.     

Computer-assisted detection of pulmonary nodules: evaluation of diagnostic performance using an expert knowledge-based detection system with variable reconstruction slice thickness settings

The purpose of this study was to evaluate the performance of a computer-assisted diagnostic (CAD) tool using various reconstruction slice thicknesses (RST). Image data of 20 patients undergoing multislice CT for pulmonary metastasis were reconstructed at 4.0, 2.0 and 0.75 mm RST and assessed by two blinded radiologists (R1 and R2) and CAD. Data were compared against an independent reference standard. Nodule subgroups (diameter >10, 4–10, <4 mm) were assessed separately. Statistical methods were the ROC analysis and Mann-Whitney U test. CAD was outperformed by readers at 4.0 mm (Az = 0.18, 0.62 and 0.69 for CAD, R1 and R2, respectively; P<0.05), comparable at 2.0 mm (Az = 0.57, 0.70 and 0.69 for CAD, R1 and R2, respectively), and superior using 0.75 mm RST (Az = 0.80, 0.70 and 0.70 and sensitivity = 0.74, 0.53 and 0.53 for CAD, R1 and R2, respectively; P<0.05). Reader performances were significantly enhanced by CAD (Az = 0.93 and 0.95 for R1 + CAD and R2 + CAD, respectively, P<0.05). The CAD advantage was best for nodules <10 mm (detection rates = 93.3, 89.9, 47.9 and 47.9% for R1 + CAD, R2 + CAD, R1 and R2, respectively). CAD using 0.75 mm RST outperformed radiologists in nodules below 10 mm in diameter and should be used to replace a second radiologist. CAD is not recommended for 4.0 mm RST.     

Automated detection of lung nodules in CT images using shape-based genetic algorithm.

A shape-based genetic algorithm template-matching (GATM) method is proposed for the detection of nodules with spherical elements. A spherical-oriented convolution-based filtering scheme is used as a pre-processing step for enhancement. To define the fitness function for GATM, a 3D geometric shape feature is calculated at each voxel and then combined into a global nodule intensity distribution. Lung nodule phantom images are used as reference images for template matching. The proposed method has been validated on a clinical dataset of 70 thoracic CT scans (involving 16,800 CT slices) that contains 178 nodules as a gold standard. A total of 160 nodules were correctly detected by the proposed method and resulted in a detection rate of about 90%, with the number of false positives at approximately 14.6/scan (0.06/slice). The high-detection performance of the method suggested promising potential for clinical applications.     

Diagnosis of pulmonary emboli and image quality at CT pulmonary angiography: influence of imaging direction with multidetector CT

AIM: To determine whether there was a significant difference in the prevalence of emboli detected when patients underwent computed tomography pulmonary angiography (CTPA) in a craniocaudal direction versus a caudocranial direction. MATERIALS AND METHODS: This was a prospective study of 203 consecutive patients attending for CTPA for suspected pulmonary embolus. Imaging was performed on a multisection Siemens Volume Zoom CT machine, with bolus tracking centred on the main pulmonary artery after intravenous administration of contrast at 3 ml/s. Patients were examined in a single breath-hold, from the top of the aortic arch to the highest point of the diaphragm, in a randomly assigned cranio-caudal (group A), or caudo-cranial (group B) direction. Images were reviewed on a workstation in a cranio-caudal direction jointly by two radiologists unaware of the original imaging direction. The presence, number and position of arterial emboli were noted, and a subjective assessment of overall image quality and opacification of upper and lower lobe vessels (grade 1, 2, 3, or 4) was made. RESULTS: Emboli were detected in 46 patients. There was no significant difference in the prevalence of emboli detected in the two groups [group A craniocaudal direction n=22, group B caudocranial direction n=24 (p=0.76)]. Imaging direction did not significantly influence overall image quality (p=0.07), however, there was a significantly greater proportion of patients in group A with grade 1 opacification of the upper lobe arteries (p=0.02). CONCLUSION: Imaging direction does not significantly influence the diagnosis of pulmonary emboli but it does significantly improve the upper lobe pulmonary arterial enhancement with fewer non-diagnostic images, and on that basis we recommend that craniocaudal direction be used for CTPA studies.     

Appearances of mediastinal and pulmonary hilar lymph nodes on thin-section CT: comparison with 5 mm slice thickness CT

AIM: This study aimed to evaluate the efficacy of thin-section CT of the mediastinum in the assessment of thoracic lymph nodes in comparison with conventional CT. MATERIALS AND METHODS: A total of 193 CT examinations from 193 patients with suspected pulmonary disease were reconstructed into thin-section CT and conventional CT. The appearances of the lymph nodes were assessed and compared between thin-section CT and conventional CT. RESULTS: Intranodal fat was more often detected on thin-section CT than on conventional CT (P<.001). There were no statistically significant differences in the frequencies of inhomogeneous enhancement and bulging margin of the hilar lymph node. CONCLUSION: Thin-section CT can improve clinical N-staging of lung cancer due to classification of enlarged mediastinal lymph nodes as benign based on identification of intranodal fat.     

Quantification of coronary artery calcium using multidetector CT and a retrospective ECG-gating reconstruction algorithm.

OBJECTIVE: The purpose of our study was to evaluate the quality of and motion artifacts on multidetector CT scans and to compare the results with those of and on electron beam CT scans for the assessment of coronary calcium scores. MATERIALS AND METHODS: First, 20 volunteers were scanned using multidetector CT. We compared the signal-to-noise ratio in the heart, motion artifacts at the heart border, and the highest CT values in the regions of the coronary arteries using single-sector and multisector reconstruction algorithms. Next, 60 patients with coronary calcified deposits underwent both multidetector CT and electron beam CT. We compared coronary calcium scores determined with multidetector CT using the two algorithms (thresholds of 90 and 130 H) with those determined using electron beam CT. RESULTS: The signal-to-noise ratio was higher and motion artifacts were reduced when we used the multisector algorithm. The highest CT value in the region of the coronary arteries exceeded 90 H in one of 55 arteries on the multisector algorithm images and 17 of 55 arteries on single-sector algorithm images (chi-square test, p < 0.01). In coronary calcium scoring, correlation coefficients ranged from 0.920 to 0.992 (Pearson's product moment) and from 0.932 to 0.969 (Spearman's rank correlation coefficient). CONCLUSION: Multidetector CT with a retrospective ECG-gating algorithm (multisector reconstruction) produced cardiac images with fewer motion artifacts and showed a high correlation with coronary calcium scores determined using electron beam CT. Therefore, multidetector CT is a potential tool for coronary calcium scoring.     

Detection of pulmonary nodules by multislice computed tomography: improved detection rate with reduced slice thickness

The purpose of this study was to find out if the use of 1.25-mm collimated thin-slice technique helps to detect more small pulmonary lung nodules than the use of 5 mm. A total of 100 patient examinations that allowed a reconstruction of 1.25-mm slice thickness in addition to the standard of 5-mm slices were included in a prospective study. Acquisition technique included four rows of 1-mm slices. Two sets of contiguous images were reconstructed and compared with 1.25- and 5-mm slice thickness, respectively. Two radiologists performed a film-based analysis of the images. The size and the confidence of the seen nodules were reported. We did not perform a histological verification, according to the normal clinical procedure, although it would be optimal regarding research. Statistical analysis was performed by using longitudinal analysis described by Brunner and Langer [10]. In addition, sensitivity, specificity, negative predictive value and positive predictive value were calculated for each reader using the 1.25-mm sections as the gold standard. As an index for concordance the kappa value was used. A value of p<0.05 was regarded as significant. In 37 patients pulmonary nodules were detected. Twenty-four patients showed more than one nodule; among these, 7 patients had disseminated disease and were excluded from the study. Pulmonary nodules larger than 10 mm in size were equally well depicted with both modalities, whereas lesions smaller than 5 mm in size were significantly better depicted with 1.25 mm (p<0.05). Using 1.25 mm as the gold standard, sensitivity for 5-mm reconstruction interval was 88 and 86% for observers A and B, respectively. No false-positive results were reported for 5-mm sections. Interobserver agreement for nodule detection determined for 1.25-mm reconstruction intervals showed a k value of 0.753, indicating a good agreement, and 0.562 for 5-mm reconstruction intervals, indicating a moderate agreement. Brunner and Langer [10] analysis showed significant differences for slice thickness and no significant difference between the observers. Reduced slice thickness demonstrated an improvement of small nodule detection, confidence levels, and interobserver agreement. Application of thin-slice multidetector-row CT may raise the sensitivity for lung nodule detection, although the higher detection rate of smaller nodules has to be evaluated from a clinical perspective and remains problematic about how the detection of small nodules will effect patient outcome.