Dynamic computed tomography in solitary pulmonary nodules

OBJECTIVE: To evaluate the utility of dynamic computed tomography (CT) imaging in the management of solitary pulmonary nodules. METHODS: We examined solitary pulmonary nodules in 45 patients. The nodules included in the study were solid, homogenous, and spherical or oval-shaped in precontrast images. Nodules that had calcification or fat density were excluded from the study. We were not able to obtain clinical or pathological diagnosis of the nodules in 23 patients, and we excluded these patients from statistical analysis. Patients were examined with 2-mm collimation and 1-mm reconstruction interval. Computed tomography examinations were done before and after injection of contrast material. Computed tomography scans of the nodule were obtained in the first, second, third, fourth, and fifth minutes after contrast injection. RESULTS: The malignancy prevalence was 40%. The mean enhancement of malignant nodules were significantly higher than the benign ones. Also, the peak attenuation value obtained after the administration of contrast material was 82.44 +/- 19.56 HU in malignant lesions and 54 +/- 23.10 HU in benign ones, with statistical significance (P = 0.006). Using enhancement values greater than 15 HU as a threshold for malignancy, the calculated sensitivity, specificity, positive and negative predictive values, and accuracy of the dynamic CT examination were 100%, 69.2%, 69.2%, 100%, and 81%, respectively. CONCLUSION: Dynamic CT imaging demonstrates significantly greater enhancement in malignant nodules than in benign ones. Lung nodule enhancement of 15 HU or less strongly indicates benignity.     

Lung nodules: dual-kilovolt peak analysis with CT--multicenter study

PURPOSE: To test the following hypothesis: The greater the increase in the mean computed tomographic (CT) number of a radiologically indeterminate lung nodule from the CT number on a 140-kVp CT image to that on an 80-kVp CT image, the more likely the nodule is benign (ie, contains calcium). MATERIALS AND METHODS: Two hundred forty indeterminate lung nodules were prospectively studied at four institutions: Mayo Clinic Scottsdale, Ariz (n = 160); Mayo Clinic Rochester, Minn (n = 50); Shiga Health Insurance Hospital, Otsu, Japan (n = 25); and Duke University Medical Center, Durham, NC (n = 5). Of the 240 nodules, 157 met the entrance criteria for this study and had a diagnosis. All nodules included were solid, 5-40-mm diameter, relatively spherical, homogeneous, and without visible evidence of calcification or fat. Each nodule was evaluated by using 3-mm-collimation, nonenhanced CT scans with both 140- and 80-kVp x-ray beams. RESULTS: There were 86 (55%) benign and 71 (45%) malignant nodules. The median increase in the nodule mean CT number from the CT number on 140-kVp images to that on 80-kVp images was 2 HU for benign nodules and 3 HU for malignant nodules. This difference was not statistically significant. The area under the receiver operating characteristic curve was 0.505. CONCLUSION: Dual-kilovolt peak analysis with current CT technology does not appear to be helpful in the identification of benign lung nodules.     

Solitary pulmonary nodule: characterization with combined wash-in and washout features at dynamic multi-detector row CT

PURPOSE: To prospectively assess the accuracy of combined wash-in and washout characteristics at dynamic contrast material-enhanced multi-detector row computed tomography (CT) in distinguishing benign from malignant solitary pulmonary nodules. MATERIALS AND METHODS: Institutional review board approval and informed consent were obtained. The study included 107 patients (62 men, 45 women; mean age, 55 years; range, 22-81 years) with a solitary pulmonary nodule. After unenhanced CT (2.5-mm collimation) scans were obtained, dynamic CT was performed by using a helical technique (series of images obtained throughout the nodule, with 2.5-mm collimation, at 30, 60, 90, and 120 seconds and 4, 5, 9, 12, and 15 minutes) after intravenous injection of contrast medium (120 mL). Tissue diagnosis was made in 70 nodules, and follow-up images showed benignancy in the remaining 37 (no change in size, n = 32; decrease in size, n = 5). CT findings were analyzed in terms of wash-in and washout of contrast medium. Sensitivity, specificity, and accuracy for malignant nodules were calculated by considering both the wash-in and washout characteristics at dynamic CT. RESULTS: There were 49 malignant and 58 benign nodules. When diagnostic criteria for malignancy of both wash-in of 25 HU or greater and washout of 5-31 HU were applied, sensitivity, specificity, and accuracy for malignancy were 94% (46 of 49 nodules), 90% (52 of 58 nodules), and 92% (98 of 107 nodules), respectively. Of 58 benign nodules, 27 showed less than 25 HU wash-in, 14 showed persistent contrast enhancement without washout and with wash-in of 25 HU or greater, and 11 showed washout greater than 31 HU and wash-in of 25 HU or greater. CONCLUSION: Evaluation of solitary pulmonary nodules by analyzing combined wash-in and washout characteristics at dynamic contrast-enhanced multi-detector row CT showed 92% accuracy for distinguishing benign nodules from malignant nodules.     

Solitary pulmonary nodules: dynamic enhanced multi-detector row CT study and comparison with vascular endothelial growth factor and microvessel density

PURPOSE: To evaluate enhancement dynamics of solitary pulmonary nodules at multi-detector row computed tomography (CT) and to correlate results with extent of tumor angiogenesis in pathologic specimens. MATERIALS AND METHODS: One hundred thirty-one patients with solitary pulmonary nodules underwent unenhanced thin-section CT, followed by dynamic helical CT (throughout the nodule for 30 mm along the z-axis [13 images] and at 20-second intervals for 3 minutes [130 images total]) after intravenous injection of 120 mL of contrast medium. Diagnosis of malignancy or benignancy was assigned in 109 patients, and follow-up imaging suggested benignancy in the remaining 22. CT findings were analyzed for peak attenuation, net enhancement, and enhancement dynamics. In 54 patients with surgical diagnoses, Pearson correlation coefficient was used to correlate enhancement pattern with extent of microvessel density and vascular endothelial growth factor (VEGF) staining. RESULTS: With 30 HU or more of net enhancement as a cutoff value in differentiation of malignant and benign nodules, sensitivity for malignant nodules was 99% (69 of 70 malignant nodules), specificity was 54% (33 of 61 benign nodules), positive predictive value was 71% (69 of 97 malignant readings), negative predictive value was 97% (33 of 34 benign readings), and accuracy was 78% (102 of 131 nodules). Peak attenuation was correlated positively with extent of microvessel density (r = 0.369, P =.006) and VEGF staining (r = 0.277, P =.042). Malignant nodules showed significantly higher VEGF expression (P =.009) than that of benign nodules. CONCLUSION: Dynamic enhancement with multi-detector row CT shows high sensitivity and negative predictive values for diagnosis of malignant nodules but low specificity because of highly enhancing benign nodules. Extent of enhancement reflects underlying nodule angiogenesis.     

孤立肺结节的增强CT诊断新进展

孤立肺结节(SPN)的增强CT诊断是近年来研究热点之一,检查方法分为动态和多期增强扫描两类,以SPN的强化程度、结节-主动脉强化值比(S/A)、时间-密度曲线类型、灌注值、强化模式、肿瘤血管征等作为诊断依据。以强化值<15HU、S/A<6%为界值,可区分出良性结节;时间-密度曲线类型有助于恶性与炎性结节的鉴别;肿瘤血管征可作为特异性诊断指征;包膜样强化或内壁规则的周围强化高度提示结核的诊断。     

Pulmonary nodule characterization: a comparison of conventional with quantitative and visual semi-quantitative analyses using contrast enhancement maps

PURPOSE: To determine whether conventional nodule densitometry or analysis based on contrast enhancement maps of indeterminate lung nodules imaged with contrast-enhanced CT can distinguish benign from malignant lung nodules. MATERIALS AND METHOD: Thin section, contrast-enhanced CT (baseline, and post-contrast series acquired at 45, 90,180, and 360 s) was performed on 29 patients with indeterminate lung nodules (14 benign, 15 malignant). A thoracic radiologist identified the boundary of each nodule using semi-automated contouring to form a 3D region-of-interest (ROI) on each image series. The post-contrast series having the maximum mean enhancement was then volumetrically registered to the baseline series. The two series were subtracted volumetrically and the subtracted voxels were quantized into seven color-coded bins, forming a contrast enhancement map (CEM). Conventional nodule densitometry was performed to obtain the maximum difference in mean enhancement values for each nodule from a circular ROI. Three thoracic radiologists performed visual semi-quantitative analysis of each nodule, scoring each map for: (a) magnitude and (b) heterogeneity of enhancement throughout the entire volume of the nodule on a five-point scale. Receiver operator characteristic (ROC) analysis was conducted on these features to evaluate their diagnostic efficacy. Finally, 14 quantitative texture features were calculated for each map. A statistical analysis was performed to combine the 14 texture features to a single factor. ROC analysis of the derived aggregate factor was done as an indicator of malignancy. All features were analyzed for differences between benign and malignant nodules. RESULTS: Using 15 HU as a threshold, 93% (14/15) of malignant and 79% (11/14) of benign nodules demonstrated enhancement. The ROC curve when higher values of enhancement indicate malignancy was generated and area under the curve (AUC) was 0.76. The visually scored magnitude of enhancement was found to be less effective in distinguishing malignant from benign lesions, with an average AUC of 0.62. The visually scored pattern of enhancement was found to be more effective with an average AUC of 0.79. From the statistical analysis performed to combine the texture features to a single factor, the area under the ROC curve was 0.84. CONCLUSION: The present study suggests that visual semi-quantitative and quantitative characterization of contrast enhancement patterns may potentially enhance the discrimination between benign and malignant nodules. Further studies and correlation with pathologic material will be important to better understand the potential interplay between CT enhancement features, host stromal elements, and neovascularity that may contribute to these patterns.     

Solitary pulmonary nodule: CT evaluation of enhancement with iodinated contrast material--a preliminary report.

The authors hypothesized that the degree of contrast material enhancement of a pulmonary nodule, measured with computed tomography (CT), may indicate the likelihood of malignancy. Fifty-two patients with uncalcified solitary pulmonary nodules (diameter, 6-30 mm) were studied. Five single serial thin-section CT scans were obtained at 1-minute intervals after injection of 100 mL of nonionic contrast material. Twenty-two patients were excluded because the diagnosis was not clearly established: The observation period was less than 2 years, or the examination was technically inadequate. Malignant nodules were identified in 23 of the 30 remaining patients, and benign nodules were identified in seven. Within the first 2 minutes after the injection, all the malignant nodules had enhanced by 20 HU or greater (only one benign nodule had that degree of enhancement). The authors conclude that the degree of contrast material enhancement of pulmonary nodules as measured with CT may indicate the likelihood of malignancy.     

Accuracy of early and delayed FDG PET-CT and of contrast-enhanced CT in the evaluation of lung nodules: a preliminary study on 30 patients

Purpose

The aim of our prospective study was to compare the diagnostic accuracy of early, delayed and dual-time-point positron emission tomography (PET) acquisition with contrast enhanced computed tomography (CT) within a PET-CT examination in the evaluation of pulmonary solitary nodules (SPNs).

Materials and methods

Thirty patients were enrolled in the study. All the patients underwent a dual-time-point PET-CT examination. Whole-body PET images were acquired at 50 min after fluorine18-fluorodeoxyglucose (¹⁸F-FDG) administration (early), followed by a chest acquisition (delayed). Lung nodules with maximum standardised uptake value SUVmax ≥2.5 were considered malignant. SUVmax was calculated on early and delayed images; SUV increasing ≥10% (Δ SUVmax) was considered suggestive of malignancy. Absence of significant lung nodule enhancement (<15 Δ HU) at CT was considered strongly predictive of benignity. For the CT morphological assessment, the irregularity of the shape of each lesion was rated. PET-CT results were related to histological assays and clinical records. Diagnostic accuracy was assessed by area under the receiveroperarting characteristic (ROC) curves analysis.

Results

Early and delayed SUVmax of malignant nodules were significantly higher than those of benign disease. Early SUVmax sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were 77%, 91%, 79.5% and 66.7%; delayed SUVmax corresponding values were 77%, 66%, 74% and 66%; dual-time-point SUVmax values were 83%, 67%, 75% and 74%; ΔHU values were 94%, 34%, 67%, 96%; CT morphologic evaluation values were 61%, 46%, 60%, 47%. Area under the curve (AUC) for early SUVmax was 0.79, for delayed SUVmax 0.80, for dual-time-point SUVmax 0.85, for ΔHU 0.63 and for CT morphologic assessment 0.58.

Conclusions

In our small series of patients, early and delayed SUVmax showed comparable accuracies, whereas morphological and contrast enhanced CT evaluations showed the lowest accuracies. Dual-time-point SUVmax showed the largest AUC. However, dual-time-point SUVmax was most sensitive, whereas single-time-point SUVmax was most specific.     

Tissue characterization of solitary pulmonary nodule: comparative study between helical dynamic CT and integrated PET/CT.

Recent advances in the technology of helical multidetector CT allow precise evaluations of nodule hemodynamics. In addition, the efficacy of tissue characterization has improved, and now sensitivity and specificity of >90% are achieved. Moreover, the efficacy of PET for the tissue characterization of solitary pulmonary nodules (SPNs) has also become of importance. The purpose of this study was to compare the diagnostic accuracy of helical dynamic (HD) CT (HDCT) and integrated PET/CT for pulmonary nodule characterization. METHODS: One hundred nineteen patients with an SPN underwent both HDCT (unenhanced scans, followed by series of images at 30, 60, 90, 120 s and at 5 and 15 min after intravenous injection of contrast medium) and integrated PET/CT. On HDCT, a nodule was regarded as malignant with a net enhancement of > or =25 Hounsfield units (HU) and a washout of 5-31 HU. On integrated PET/CT, nodules were considered malignant with a > or =3.5 maximum standardized uptake value and an 18F-FDG uptake greater than that of mediastinal structures. The sensitivity, specificity, and accuracy of the 2 modalities for malignancy were compared using the McNemar test. RESULTS: There were 79 malignant and 40 benign nodules. The sensitivity, specificity, and accuracy for malignancy on HDCT were 81% (64/79 nodules), 93% (37/40), and 85% (101/119), respectively, whereas those on integrated PET/CT were 96% (76/79), 88% (35/40), and 93% (111/119), respectively (P = 0.008, 0.727, and 0.011, respectively). All malignant nodules were interpreted correctly on either HDCT or PET/CT. CONCLUSION: Integrated PET/CT is more sensitive and accurate than HDCT for the malignant nodule characterization; therefore, PET/CT may be performed as the first-line evaluation tool for SPN characterization. Because HDCT has high specificity and acceptable sensitivity and accuracy, it may be a reasonable alternative for nodule characterization when PET/CT is unavailable.     

Thin-section CT features of intrapulmonary lymph nodes

PURPOSE: The objective of this study was to evaluate CT findings of pathologically proven intrapulmonary lymph nodes (IPLNs) and discuss the utility of thin-section CT and contrast-enhanced CT. METHOD: CT findings of 18 nodules in 14 patients with pathologically proven IPLNs were reviewed. CT scanning of the whole lung was performed contiguously with slice thickness of 10 mm. In addition, a helical scan with slice thickness of 2 mm was performed in nine patients, focusing on the nodule. Contrast-enhanced helical CT was performed in four patients, and the utility of thin section CT and contrast-enhanced CT was investigated. RESULTS: One patient had three nodules, 2 patients had two nodules, and the remaining 11 patients had a solitary nodule. All nodules were located below the level of the carina and within 15 mm of the pleura. In one case, conventional CT revealed the nodule 20 mm away from the pleura; however, the nodule attached to the major fissure was clearly revealed on thin-section CT. The size of the nodules was < or =15 mm, and the shape was round (n = 8), oval (n = 9), or lobulated (n = 1) with sharp border. One nodule demonstrated a spiculated border due to a surrounding pulmonary fibrosis on conventional CT; however, thin-section CT showed precisely a sharp border. The lobulated shape of one case histopathologically reflected a hilus of lymph node. On contrast-enhanced helical CT, all four nodules were enhanced and the degree enhancement was 36-85 HU (median 66.6 HU). CONCLUSION: In current times, IPLNs are not uncommon lesions. We should consider IPLN in the differential diagnosis of solitary or multiple pulmonary nodules in the peripheral field and below the level of the carina. Thin-section CT showed precisely the border or relation between IPLNs and the surrounding structure. It was difficult to distinguish between IPLNs and malignant nodules from the degree of enhancement on contrast-enhanced CT. On thin-section and contrast-enhanced CT, the findings of IPLNs are not necessarily specific. Therefore, strict observation on CT is necessary; in certain cases that are increasing in size, video-assisted thoracic surgery should be considered because of their location.     

肺孤立结节CT增强动态扫描的研究(附36例)

目的：评估肺部孤立结节ＣＴ增强动态扫描特征。方法：３６例肺部孤立结节中恶性肿瘤（均为肺癌）２４例,炎症结节７例,结核球５例。以１００ｍｌ／ｍｉｎ速度静脉注射１．５ｍｌ／ｋｇ体重碘造影剂后行动态薄层扫描,层厚２ｍｍ,层间距２ｍｍ。测量增强前后各层次病灶ＣＴ值。结果：结核球无显著强化,炎症结节及恶性肿瘤均呈显著强化,结核球与炎症结节／恶性肿瘤增强值相比有显著性差异;所有炎症结节,２３例恶性肿瘤及１例结核球呈全部强化型,１例恶性肿瘤呈周边强化型,２例结核球呈环形强化,另外２例结核球无明显强化。结论：（１）结节增强值在２０ＨＵ以下提示结核球,２０～６０ＨＵ为恶性结节的一个指标,６０ＨＵ以上高度提示炎症结节。（２）环形强化提示结核球。     

Solitary pulmonary nodules: morphological and metabolic characterisation by FDG-PET-MDCT

PURPOSE: This study was done to analyse the additional morphological and functional information provided by the integration of [18F]-2-fluoro-2-deoxy-D-glucose positron emission tomography ([18F]-FDG-PET) with contrast-enhanced multidetector computed tomography (MDCT) in the characterisation of indeterminate solitary pulmonary nodules (SPNs). MATERIALS AND METHODS: Fifty-six SPNs, previously classified as indeterminate, were evaluated using a Discovery ST16 PET/CT system (GE Medical Systems) with nonionic iodinated contrast material and [18F]-FDG as a positron emitter. Images were evaluated on a dedicated workstation. Semiquantitative parameters of [18F]-FDG uptake and morphological, volumetric and densitometric parameters before and after contrast administration were analysed. Results were correlated with the histological and follow-up findings. RESULTS: Twenty-six SPNs were malignant and 30 were benign. Malignant lesions at both PET/CT and histology had a mean diameter of 1.8+/-1.2 cm, a volume doubling time (DT) of 222 days, a mean standardized uptake value (SUV) of 4.7 versus 1.08 in benign lesions and a mean postcontrast enhancement of 44.8 HU as opposed to 4.8 HU in benign nodules. Malignant lesions had a significantly shorter doubling time and significantly greater postcontrast enhancement compared with benign nodules. Based on the SUV and using a cut-off value of >2.5, PET/CT had a sensitivity of 76.9%, specificity of 100%, diagnostic accuracy of 89.2%, positive predictive value (PPV) of 100% and negative predictive value (NPV) of 83.3%. Based on doubling time (cut off<400 days), it had a sensitivity of 76.9%, specificity of 93.3%, accuracy of 85.7%, PPV of 90.9% and NPV of 82.3%. Based on postcontrast enhancement (cut off>15 HU), it had a sensitivity of 92.3%, specificity of 100%, accuracy of 96.4%, PPV of 100% and NPV of 93.7%. CONCLUSION: PET/CT allows accurate analysis of anatomical/morphological and metabolic/functional correlations of SPN, providing useful data for identifying and locating the disease, for differentiating between malignant and benign nodules and for establishing the aggressiveness and degree of vascularity of pulmonary lesions. Therefore, partly in view of the considerable reduction in time and cost of the single examinations, we believe that PET/CT will gain an increasingly dominant role in the diagnostic and therapeutic approach to lung cancer, especially in the preclinical phase.     

CT evaluation of solitary pulmonary nodules: value of 185-H reference phantom

The pulmonary nodule CT reference phantom is widely used in the evaluation of nodules 2 cm or less in diameter. It is used to detect benign patterns of calcification that are not visible on thin-section CT scans. Since 1986, the reference nodules have been manufactured with a nominal composition of 185 H. The multicenter study published in 1986 used nodules with a nominal composition of 264 H, 100 H more than the threshold value reported by Siegelman et al. in 1980. In the multicenter study, one of 37 nodules diagnosed as benign with the phantom proved to be malignant. The purpose of this study was to determine the misdiagnosis rate with the 185-H phantom and to ascertain whether the malignant tumors predicted to be benign actually contained calcification. We retrospectively reviewed 296 cases in which examinations had been performed with the 185-H nodules since 1986. Eighty-five nodules were diagnosed as benign by comparison to the reference phantom. These 85 contained no visible calcification on thin-section CT scans. Ten of the 85 cases were shown to be malignant tumors. Eight were diagnosed as having a high probability of benignity. Two were diagnosed as having a moderate probability of benignity. Calcium was present in the tissue of all six nodules available for review. Fifty-nine of the 85 nodules were still clinically indeterminate at the time of this review. Even if all of the clinically indeterminate nodules are benign, the misdiagnosis rate would be significantly higher than in most previous studies. Although analysis by using the reference phantom with 185-H nodules may indicate a high probability of benignity, close radiologic follow-up is necessary.     

Role of baseline nodule density and changes in density and nodule features in the discrimination between benign and malignant solid indeterminate pulmonary nodules

Purpose

To retrospectively evaluate whether baseline nodule density or changes in density or nodule features could be used to discriminate between benign and malignant solid indeterminate nodules.

Materials and methods

Solid indeterminate nodules between 50 and 500 mm³ (4.6–9.8 mm) were assessed at 3 and 12 months after baseline lung cancer screening (NELSON study). Nodules were classified based on morphology (spherical or non-spherical), shape (round, polygonal or irregular) and margin (smooth, lobulated, spiculated or irregular). The mean CT density of the nodule was automatically generated in Hounsfield units (HU) by the Lungcare^© software.

Results

From April 2004 to July 2006, 7310 participants underwent baseline screening. In 312 participants 372 solid purely intra-parenchymal nodules were found. Of them, 16 (4%) were malignant. Benign nodules were 82.8 mm³ (5.4 mm) and malignant nodules 274.5 mm³ (8.1 mm) (p = 0.000). Baseline CT density for benign nodules was 42.7 HU and for malignant nodules −2.2 HU (p = ns). The median change in density for benign nodules was −0.1 HU and for malignant nodules 12.8 HU (p < 0.05). Compared to benign nodules, malignant nodules were more often non-spherical, irregular, lobulated or spiculated at baseline, 3-month and 1-year follow-up (p < 0.0001). In the majority of the benign and malignant nodules there was no change in morphology, shape and margin during 1 year of follow-up (p = ns).

Conclusion

Baseline nodule density and changes in nodule features cannot be used to discriminate between benign and malignant solid indeterminate pulmonary nodules, but an increase in density is suggestive for malignancy and requires a shorter follow-up or a biopsy.     

Does contrast enhancement on CT suggest tumor response for chemotherapy in small cell carcinoma of the lung?

PURPOSE: The purpose of this article is to assess the correlation between contrast enhancement on CT and the tumor reduction ratio in small cell carcinoma of the lung after first-line chemotherapy. MATERIALS AND METHODS: Twenty-eight patients with small cell carcinoma of lung underwent preenhancement and postenhancement CT scans before and after first-line chemotherapy, followed by second-line chemotherapy in 7 patients who had relapsed. The authors retrospectively analyzed the correlation between the tumor reduction ratio and the CT numbers of contrast enhancement in each case by multiple regression analysis using SPSS. RESULTS: The mean tumor-reduction ratio was 58.2 +/- 43.2% after first-line chemotherapy, and the mean CT enhancement was 33.2 +/- 11.0 Hounsfield units (HU). The correlation coefficient between the tumor reduction ratio and the CT numbers of contrast enhancement was 0.57 (r = 0.32), and p value was < 0.002. After chemotherapy, more than 90% tumor reduction was seen in 11 patients. They revealed an average 41.9 +/- 7.6 HU tumor enhancement. Less than 50% tumor reduction was seen in 10 patients. They revealed an average 26.2 +/- 7.9 HU tumor enhancement. If these criteria of 30 HU contrast enhancement and 80% tumor reduction ratio were applied as a guide for chemotherapy response, the sensitivity, specificity, positive predictive value, and negative predictive value would be calculated as 85.7%, 84.6%, 85.7%, and 84.6%, respectively. CONCLUSION: In small cell carcinoma of the lung, it is statistically proven that the more enhanced tumor on CT, the better response to chemotherapy. Tumor enhancement of 30 HU is a suggestive guide for chemotherapy response in patients with small cell carcinoma.     

18F-FDG PET/CT对不同大小孤立性肺结节的诊断价值

目的 评价18F-脱氧葡萄糖(FDG) PET/CT对不同大小范围孤立性肺结节(SPN)良恶性鉴别诊断的价值.方法 从全国拥有PET/CT的10家医院筛选出已经获得病理学检查结果的SPN病例,收集诊断CT、PET/CT和病理检查结果以及标准摄取值(SUV)、结节大小等资料.诊断CT、PET/CT结果为肺癌、肺癌可能性大、肺癌可能者为阳性;结果为良性病变、良性可能性大、良性可能者为阴性;难以确定阳性和阴性者为不确定.采用SPSS 10.0软件对资料进行分析.结果 120个(120例)SPN中良性结节28个,恶性结节92个.直径或(长径+短径)/2≤1.0cm的结节17个,恶性病变9个;1.1～2.0cm 57个,恶性病变占75.44%;2.1～3.0cm 46个,恶性病变占86.96%.28个良性结节SUV最大值(SUVmax)的平均值为4.5±4.9, SUV平均值(SUVmean)的平均值为2.9±3.6;92个恶性结节SUVmax平均值为6.7±4.2, SUVmean平均值为4.9±3.6;良性结节的SUV显著低于恶性结节的SUV.无论良性还是恶性结节,随着结节的增大,SUV升高.诊断CT对结节良恶性鉴别的灵敏度为78.26%,特异性3/8,准确性72.22%; PET/CT灵敏度为94.51%,特异性64.00%,准确性87.93%.结论 18F-FDG PET/CT在SPN鉴别诊断中具有较高的灵敏度、特异性和准确性,优于诊断CT;结节大小是判断SPN良恶性的重要指标,直径或(长径+短径)/2＞2.0cm的结节,恶性可能性约为87%; SUV可以作为鉴别诊断的依据,但鉴于良性结节SUVmean的平均值为2.9±3.6,界值2.5仅供参考,尤其是对于≤1.0cm的结节.     

Computerized detection of lung nodules in thin-section CT images by use of selective enhancement filters and an automated rule-based classifier

RATIONALE AND OBJECTIVES: We have been developing a computer-aided diagnostic (CAD) scheme for lung nodule detection in order to assist radiologists in the detection of lung cancer in thin-section computed tomography (CT) images. MATERIALS AND METHODS: Our database consisted of 117 thin-section CT scans with 153 nodules, obtained from a lung cancer screening program at a Japanese university (85 scans, 91 nodules) and from clinical work at an American university (32 scans, 62 nodules). The database included nodules of different sizes (4-28 mm, mean 10.2 mm), shapes, and patterns (solid and ground-glass opacity (GGO)). Our CAD scheme consisted of modules for lung segmentation, selective nodule enhancement, initial nodule detection, feature extraction, and classification. The selective nodule enhancement filter was a key technique for significant enhancement of nodules and suppression of normal anatomic structures such as blood vessels, which are the main sources of false positives. Use of an automated rule-based classifier for reduction of false positives was another key technique; it resulted in a minimized overtraining effect and an improved classification performance. We used a case-based four-fold cross-validation testing method for evaluation of the performance levels of our computerized detection scheme. RESULTS: Our CAD scheme achieved an overall sensitivity of 86% (small: 76%, medium-sized: 94%, large: 95%; solid: 86%, mixed GGO: 89%, pure GGO: 81%) with 6.6 false positives per scan; an overall sensitivity of 81% (small: 69%, medium-sized: 91%, large: 91%; solid: 79%, mixed GGO: 88%, pure GGO: 81%) with 3.3 false positives per scan; and an overall sensitivity of 75% (small: 60%, medium-sized: 88%, large: 87%; solid: 70%, mixed GGO: 87%, pure GGO: 81%) with 1.6 false positives per scan. CONCLUSION: The experimental results indicate that our CAD scheme with its two key techniques can achieve a relatively high performance for nodules presenting large variations in size, shape, and pattern.     

Distinguishing benign from malignant pulmonary nodules with helical chest CT in children with malignant solid tumors

PURPOSE: To retrospectively assess whether computed tomographic (CT) findings can indicate the benign or malignant nature of pulmonary nodules in pediatric patients with malignant solid primary tumors. MATERIALS AND METHODS: With institutional review board approval, waived parental and patient consent, and HIPAA compliance, the authors determined the incidence of malignancy among 81 pulmonary nodules that were sampled at biopsy within 3 weeks after chest CT (January 1999 to September 2003) in 41 young patients with malignant solid tumors. Three radiologists independently and retrospectively reviewed these scans and the available previously obtained scans, classifying nodules as benign, malignant, or indeterminate on the basis of their number, unilateral versus bilateral distribution, size, margins (indistinct vs distinct), calcification, growth, and associated adenopathy. These classifications were compared with nodule histologic type, and interreviewer agreement was assessed. RESULTS: The median patient age was 14.8 years (mean, 13.7 years; range, 5-21 years). Twenty-four of the 41 patients (58%) had at least one biopsy-proved malignant nodule. Four (10%) patients had both benign and malignant nodules; 17 (42%) had only benign nodules. Reviewer 1 classified 65% (39 of 60) of nodules correctly; reviewer 2, 57% (37 of 65); and reviewer 3, 67% (43 of 64). Interreviewer agreement was slight to moderate (kappa /= .32). CONCLUSION: The frequency of benign nodules and the inconsistency of predictions based on CT features suggest the need for better predictors of pulmonary nodules being malignant or benign, so as to reduce unnecessary thoracotomy in pediatric patients with solid malignancy. .     

Ultra-low-dose MDCT of the chest: influence on automated lung nodule detection.

OBJECTIVE: To evaluate the relationship between CT dose and the performance of a computer-aided diagnosis (CAD) system, and to determine how best to minimize patient exposure to ionizing radiation while maintaining sufficient image quality for automated lung nodule detection, by the use of lung cancer screening CT. MATERIALS AND METHODS: Twenty-five asymptomatic volunteers participated in the study. Each volunteer underwent a low-dose CT scan without contrast enhancement (multidetector CT with 16 detector rows, 1.25 mm section thickness, 120 kVp, beam pitch 1.35, 0.6 second rotation time, with 1.25 mm thickness reconstruction at 1.25 mm intervals) using four different amperages 32, 16, 8, and 4 mAs. All series were analyzed using a commercially available CAD system for automatic lung nodule detection and the results were reviewed by a consensus reading by two radiologists. The McNemar test and Kappa analysis were used to compare differences in terms of the abilities to detect pulmonary nodules. RESULTS: A total of 78 non-calcified true nodules were visualized in the 25 study subjects. The sensitivities for nodule detection were as follows: 72% at 32 mAs, 64% at 16 mAs, 59% at 8 mAs, and 40% at 4 mAs. Although the overall nodule-detecting performance was best at 32 mAs, no significant difference in nodule detectability was observed between scans at 16 mAs or 8 mAs versus 32 mAs. However, scans performed at 4 mAs were significantly inferior to those performed at 32 mAs (p < 0.001). CONCLUSION: Reducing the radiation dose (i.e. reducing the amperage) lowers lung nodule detectability by CAD. However, relatively low dose scans were found to be acceptable and to cause no significant reduction in nodule detectability versus usual low-dose CT.     

Evaluation of Adrenal Masses in Lung Cancer Patients Using F-18 FDG PET/CT

Purpose

The aim of this study was to assess the diagnostic efficacy of PET/CT using various parameters for the characterization of adrenal nodules in lung cancer patients.

Methods

Sixty-one adrenal nodules in 51 lung cancer patients were evaluated. The final diagnosis was based on histology (n = 2) or imaging follow-up (n = 59, range of follow-up: 7–57 months, median 27 months). Each adrenal nodule was analyzed using four parameters of PET/CT: the maximum standardized uptake value (SUV_max), the adrenal nodule/liver ratio of the SUV (SUV ratio), Hounsfield units (HU) and size. The optimal cutoff of each parameter for the identification of metastatic nodule was determined by ROC analysis and then the diagnostic efficacy was compared among the parameters.

Results

Of the 61 adrenal nodules, 45 (73%) were considered metastasis. The optimal cutoff values of the parameters were SUV_max >2.7, SUV ratio >1.3, HU >18 and size >20 mm, respectively. The sensitivity, specificity and accuracy by SUV_max >2.7 were 88.9%, 87.5% and 88.5%, and those by SUV ratio >1.3 were 84.4%, 100% and 88.5%, respectively. The combination of SUV ratio >1.3 and HU >18 had sensitivity of 97.7%, specificity of 81.2% and accuracy of 93.4% to predict adrenal metastasis in patients with lung cancer.

Conclusion

SUV ratio from F-18 FDG PET/CT could identify the adrenal metastasis in lung cancer patients. The combination of SUV ratio and HU can improve the accuracy of differentiating benign and metastatic adrenal lesions in lung cancer patients.