Benign Solitary Pulmonary Nodules Research Articles

Plasma secretory phospholipase A2-IIa as a potential biomarker for lung cancer in patients with solitary pulmonary nodules

BackgroundFive-year survival for lung cancer has remained at 16% over last several decades largely due to the fact that over 50% of patients are diagnosed with locally-advanced or metastatic disease. Diagnosis at an earlier and potentially curable stage is crucial. Solitary pulmonary nodules (SPNs) are common, but the difficulty lies in the determination of which SPN is malignant. Currently, there is no convenient and reliable biomarker effective for early diagnosis. Secretory phospholipase A2-IIa (sPLA2-IIa) is secreted into the circulation by cancer cells and may allow for an early detection of lung cancer.MethodsPlasma samples from healthy donors, patients with only benign SPN, and patients with lung cancer were analyzed. Expression of sPLA2-IIa protein in lung cancer tissues was also determined.ResultsWe found that the levels of plasma sPLA2-IIa were significantly elevated in lung cancer patients. The receiver operating characteristic curve analysis, comparing lung cancer patients to patients with benign nodules, revealed an optimum cutoff value for plasma sPLA2-IIa of 2.4 ng/ml to predict an early stage cancer with 48% sensitivity and 86% specificity and up to 67% sensitivity for T2 stage lung cancer. Combined sPLA2-IIa, CEA, and Cyfra21.1 tests increased the sensitivity for lung cancer prediction. High level of plasma sPLA2-IIa was associated with a decreased overall cancer survival. sPLA2-IIa was overexpressed in almost all non-small cell lung cancer and in the majority of small cell lung cancer by immunohistochemistry analysis.ConclusionOur finding strongly suggests that plasma sPLA2-IIa is a potential lung biomarker to distinguish benign nodules from lung cancer and to aid lung cancer diagnosis in patients with SPNs.

Dual-energy CT in the evaluation of solitary pulmonary nodules by virtual non-enhanced images:initial experience

Objective To determine the accuracy and radiation dose of dual-energy computed tomography (CT) in evaluating solitary pulmonary nodules (SPNs) by virtual non-enhanced images.Methods Sixty-one patients with SPNs including 39 malignant and 18 benign nodules proved by pathology underwent DECT scans. The CT values of SPNs on enhanced weighted average and virtual non-enhanced images were compared by using Liver VNC processing unit in terms of their diagnostic accuracy for distinguishing malignant and benign nodules with a 20 HU threshold. Diagnostic accuracy was compared. In 28 patients of all patients, image noise and quality score of the non-enhanced and virtual non-enhanced images were compared, and radiation doses of each patient were recorded. The paired t test was used to analyze the noise difference between the plain scan and virtual non-enhanced scan. The Mann-Whitney U test was used to analyze statistically significant differences of the image quality score and radiation dose between the non-enhanced scan and virtual non-enhanced scan. Results The sensitivity, specificity and accuracy for distinguishing benign and malignant nodules by using the virtual non-enhanced image of were 89. 7％(35/39), 72.2％ (13/18), 84.2％ (48/57)respectively. The noise of common CT and virtual nonenhanced images were(8. 49 ± 1. 94) HU and( 10. 14 ± 2. 18 ) HU, and there were statistically difference (t＝9.45,P＜0. 01 ). The quality scores of common CT and virtual non-enhanced images were (4.71 ±0. 46 ) and ( 4.42 ± 0. 57 ), and there were no statistical difference ( U ＝ 290. 00, P ＞ 0. 05 ). The radiation doses of common CT and DECT were ( 3. 72 ± 0. 48 ) mSv and ( 3.78 ± 0. 45 ) mSv, and there were no statistical difference ( U ＝ 350. 50,P ＞ 0. 05 ). Conclusion DECT by using virtual non-enhanced images is useful tool to distinguish the benign and malignant SPN without additional radiation dose. Key words: Coin lesion pulmonary; Tomography, X-ray computed; Image processing,computed-assisted

Diagnosis of lung cancer in individuals with solitary pulmonary nodules by plasma microRNA biomarkers

BackgroundMaking a definitive preoperative diagnosis of solitary pulmonary nodules (SPNs) found by CT has been a clinical challenge. We previously demonstrated that microRNAs (miRNAs) could be used as biomarkers for lung cancer diagnosis. Here we investigate whether plasma microRNAs are useful in identifying lung cancer among individuals with CT-detected SPNs.MethodsBy using quantitative reverse transcriptase PCR analysis, we first determine plasma expressions of five miRNAs in a training set of 32 patients with malignant SPNs, 33 subjects with benign SPNs, and 29 healthy smokers to define a panel of miRNAs that has high diagnostic efficiency for lung cancer. We then validate the miRNA panel in a testing set of 76 patients with malignant SPNs and 80 patients with benign SPNs.ResultsIn the training set, miR-21 and miR-210 display higher plasma expression levels, whereas miR-486-5p has lower expression level in patients with malignant SPNs, as compared to subjects with benign SPNs and healthy controls (all P ≤ 0.001). A logistic regression model with the best prediction was built on the basis of miR-21, miR-210, and miR-486-5p. The three miRNAs used in combination produced the area under receiver operating characteristic curve at 0.86 in distinguishing lung tumors from benign SPNs with 75.00% sensitivity and 84.95% specificity. Validation of the miRNA panel in the testing set confirms their diagnostic value that yields significant improvement over any single one.ConclusionsThe plasma miRNAs provide potential circulating biomarkers for noninvasively diagnosing lung cancer among individuals with SPNs, and could be further evaluated in clinical trials.

Lung 99mTc-MIBI scintigraphy: impact on diagnosis of solitary pulmonary nodule

Most of today available non-invasive procedures cannot clearly determinate between benign and malignant solitary pulmonary nodules (SPN). The purpose of the study was to assess the possibility of using 99mTc labeled hexakis-2-methoxyisobutylisonitrile (99mTc-MIBI) to differentiate benign from malignant SPN. Sixty patients were included in the study if the CT scan showed indeterminate SPN. Prior to definitive diagnosis 99mTc-MIBI single photon emission computerized tomography (SPECT) was performed: early scan 10 minutes and delayed 60-120 minutes after the intravenous injection of 740 MBq 99mTc-MIBI using dual-headed Gamma camera. The results were considered positive if there was an increased accumulation of the radiopharmaceutical in the area of the lung corresponding to the location of the lesion. The mean nodule size ± SD measured on CT scan was 2.96 cm. Lung cancer was diagnosed in 30/60 patients (14 squamocellular, 10 adenocarcinoma, 3 large-cell and 3 microcellular lung carcinomas). Of the 30 patients with malignant lesions, 27 patients (90%) had positive 99mTc-MIBI scan results by qualitative assessment. Among benign lesions, 23/30 (76.7%) were negative on 99mTc-MIBI scan. The size and PH report of SPN is statistically significantly influencing on 99mTc-MIBI accumulation in the SPN (p<0.01). The sensitivity, specificity, accuracy, positive and negative predictive value were 90%, 76.6%, 79.4%, 88.5% and 83.3% respectively. 99mTc-MIBI SPECT is an inexpensive non-invasive diagnostic procedure which might be useful diagnostic modality in the evaluation of SPN. Easy availability and low cost makes 99mTc-MIBI SPECT an attractive method in evaluating SPN.

Impact of nonrigid motion correction technique on pixel‐wise pharmacokinetic analysis of free‐breathing pulmonary dynamic contrast‐enhanced MR imaging

To investigates the impact of nonrigid motion correction on pixel-wise pharmacokinetic analysis of free-breathing DCE-MRI in patients with solitary pulmonary nodules (SPNs). Misalignment of focal lesions due to respiratory motion in free-breathing dynamic contrast-enhanced MRI (DCE-MRI) precludes obtaining reliable time-intensity curves, which are crucial for pharmacokinetic analysis for tissue characterization. Single-slice 2D DCE-MRI was obtained in 15 patients. Misalignments of SPNs were corrected using nonrigid B-spline image registration. Pixel-wise pharmacokinetic parameters K(trans) , v(e) , and k(ep) were estimated from both original and motion-corrected DCE-MRI by fitting the two-compartment pharmacokinetic model to the time-intensity curve obtained in each pixel. The "goodness-of-fit" was tested with χ(2) -test in pixel-by-pixel basis to evaluate the reliability of the parameters. The percentages of reliable pixels within the SPNs were compared between the original and motion-corrected DCE-MRI. In addition, the parameters obtained from benign and malignant SPNs were compared. The percentage of reliable pixels in the motion-corrected DCE-MRI was significantly larger than the original DCE-MRI (P = 4 × 10(-7) ). Both K(trans) and k(ep) derived from the motion-corrected DCE-MRI showed significant differences between benign and malignant SPNs (P = 0.024, 0.015). The study demonstrated the impact of nonrigid motion correction technique on pixel-wise pharmacokinetic analysis of free-breathing DCE-MRI in SPNs.

First-pass perfusion imaging of solitary pulmonary nodules with 64-detector row CT: comparison of perfusion parameters of malignant and benign lesions

The purpose of this study was to determine the usefulness of first-pass whole nodule perfusion imaging in the differentiation of benign and malignant solitary pulmonary nodules (SPNs). 77 patients with non-calcified SPNs (46 malignant, 22 benign and 9 active inflammatory) underwent first-pass perfusion imaging with a 64-detector row CT scanner. Perfusion, peak enhancement intensity (PEI), time to peak (TTP) and blood volume (BV) were measured and statistically compared among different groups. Mean perfusion, PEI and BV for benign SPNs were significantly lower than those for malignant nodules (p<0.05) and active infections (p<0.05), but the differences were not statistically significant between malignant tumours and active infections (p>0.05). Receiver operating characteristic (ROC) curve analysis showed that SPNs with perfusion greater than 30.6 ml min(-1) ml(-1), PEI higher than 23.3 HU or BV larger than 12.2 ml per 100 g were more likely to be malignant. In conclusion, first-pass perfusion imaging with 64-detector row CT is a feasible way of assessing whole nodule perfusion and helpful in differentiating benign from malignant SPNs.

Risk stratification of solitary pulmonary nodules by means of PET using 18F-fluorodeoxyglucose and SUV quantification

(18)F-fluorodeoxyglucose (FDG) PET is the most accurate imaging modality in characterizing a solitary pulmonary nodule (SPN). Besides visual image interpretation, semiquantitative analysis using standardized uptake values (SUV) is performed to improve diagnostic accuracy. Mostly, an SUV threshold of 2.5 is applied to differentiate between benign and malignant lesions. In this study we analysed the use different SUV thresholds to predict the post-test probability of malignancy for the individual patient considering his pre-test probability. Furthermore, we investigated the prognostic value of SUV in SPN for survival. This retrospective study included 140 consecutive patients who underwent FDG PET for evaluation of SPN. Visual interpretation was performed by two readers. For semiquantitative analysis, maximum SUV (SUV(max)) was measured in all SPN. A final diagnosis was obtained by pathological examination or follow-up of more than 2 years. In a nomogram, positive and negative predictive values (PPV and NPV) were plotted against the hypothetical SUV threshold to determine the optimum SUV threshold. Survival was analysed using the Kaplan-Meier method and log-rank test. The prevalence of malignancy was 57%. The FDG uptake in malignant SPNs was higher than in benign SPNs (SUV 9.7 +/- 5.5 vs 2.6 +/- 2.5, p < 0.01). More than 90% of SPNs with an SUV below 2.0 were benign (sensitivity, specificity, NPV of 96, 55 and 92%). The highest diagnostic accuracy was achieved with an SUV of 4.0 (sensitivity, specificity and accuracy of 85%). Visual interpretation achieved corresponding values of 94, 70 and 84%, respectively. In lung cancer higher FDG uptake (SUV(max) >or= 9.5) was associated with shorter survival (median survival 20 months) and low FDG uptake with longer survival (>75 months). FDG PET allows assessment of the individual risk for malignancy in SPNs by considering tumoural SUV and pre-test probability. Higher FDG uptake in lung cancer as measured by SUV analysis is a prognostic factor. In patients with low FDG uptake in an SPN and increased risk during surgery omission of diagnostic thoracotomy may be warranted.

Charakterisierung und Management inzidentell diagnostizierter solitärer Lungenrundherde

How to deal with solitary pulmonary nodules (SPN) which are incidentally detected by computed tomography (CT) is an increasingly important task in the era of modern multislice CT. This paper reviews the morphological and functional characteristics and their value for discrimination between benign and malignant SPNs. In particular, the importance of nodule size, growth rate, margin morphology, density, calcifications or fatty components within the nodules, the significance of cavitations or aerobronchograms, enhancement patterns at dynamic contrast-enhanced CT and findings on positron emission tomography (PET) are discussed. The Bayesian analysis to calculate the probability of malignancy is presented. Finally, flow charts demonstrate the national and international recommendations for nodule management.

The Efficacy of Serum Carcinoembryonic Antigen (CEA), Cancer Antigen 125 (CA125), Carbohydrate Antigen 19-9 (CA19-9), Carbohydrate Antigen 15-3 (CA15-3), α-Fetoprotein (AFP) and Human Chorionic Gonadotropin (hCG) Levels in Determining the Malignancy of Solitary Pulmonary Nodules

We investigated the utility of the tumour markers carcinoembryonic antigen (CEA), cancer antigen 125 (CA125), carbohydrate antigen 19-9 (CA19-9), carbohydrate antigen 15-3 (CA15-3), alpha-fetoprotein (AFP) and human chorionic gonadotropin (hCG) for the differential diagnosis of benign and malignant solitary pulmonary nodules in 42 hospitalized patients. Routine medical history and physical examination of each patient was performed and each patient also had a chest X-ray and a thoracic computed tomography scan. The following diagnostic procedures were also undertaken: bronchoscopy, transthoracic needle aspiration biopsy, sputum cytology and culture, analysis of sputum acid-fast bacilli and thoracotomy. Measurement of serum levels of tumour antigens by Immulite 2000 radioimmunoassay found that three tumour markers, CEA, CA125 and CA15-3, could be used in the diagnosis of malignant solitary pulmonary nodules. More research is now required involving a larger group of patients.

Diagnostic performance of PET/CT in differentiation of malignant and benign non-solid solitary pulmonary nodules

To evaluate whether [F-18] fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) can distinguish benign from malignant solitary pulmonary nodules (SPNs) with non-solid components. [F-18] FDG-PET/CT scans were performed on 53 consecutive patients (30 men, 23 women; mean age 65 years) who had SPNs with non-solid components identified by CT screening for lung cancer. All patients underwent surgical resection, and all lesions were pathologically proved. Visual score, maximal, and mean standardized uptake value (SUV), and maximal and mean lesion-to-normal tissue count density ratio (LNR) were calculated in all lesions. In addition, clinical characteristics, laboratory test results, and CT findings were assessed. Benign SPNs with non-solid components had a higher uptake on [F-18] FDG-PET/CT. Visual score, maximal and mean SUV, and maximal and mean LNR were significantly higher in the benign when compared with the malignant SPNs (P < 0.001). When the cutoff of 1.5 was assigned for maximal SUV, the diagnostic performance of [F-18] FDG-PET/CT in predicting benign SPN revealed 100.0% sensitivity, 96.4% specificity, and 100.0% accuracy. [F-18] FDG-PET/CT is useful for the differential diagnosis of SPNs with non-solid components.

Standardized uptake value-based evaluations of solitary pulmonary nodules using F-18 fluorodeoxyglucose-PET/computed tomography

Combined positron emission tomography and computed tomography (PET/CT) might improve the accuracy of PET tracer quantification by providing the exact tumour contour from coregistered CT images. We compared various semiquantitative approaches for the characterization of solitary pulmonary nodules (SPNs) using F-18 fluorodeoxyglucose PET/CT. The final diagnosis of 49 SPNs (46 patients) was based on histopathology (n=33) or patient follow-up (n=16). The regions of interest (ROIs) were drawn around lesions based on the CT tumour contour and mirrored to the coregistered PET images. Quantification of F-18 fluorodeoxyglucose uptake was accomplished by calculating the standardized uptake value (SUV) using three different methods based on: activity from the maximum-valued pixel within the tumour (SUV-max); the mean ROI activity within the transaxial slice containing the maximum-valued pixel (SUV-mean); and the mean activity over the full tumour volume (SUV-vol). SUVs were corrected for partial volume effects and normalized by body surface area, lean body weight, and blood glucose. Recovery coefficients for partial-volume correction were derived from phantom studies. The ability of various SUVs to differentiate between benign and malignant SPNs was determined by calculating the area under the receiver operating characteristic (ROC) curves. Twenty-six SPNs were malignant and 23 were benign. The area under the ROC curve was 0.78 for SUV-mean, 0.83 for SUV-max, and 0.78 for SUV-vol. SUV-max and its normalizations yielded the highest area under the ROC curve (0.83-0.85); SUV-mean-partial volume corrected-lean body weight resulted in the lowest area under the ROC curve (0.76). At a specificity of 80%, SUV-max-body surface area provided the highest sensitivity (81%) and accuracy (80%) to detect malignant SPN. Using SUV-max with a cutoff of 2.4 at a specificity of 80% resulted in a sensitivity of 62% (accuracy 71%). Various normalizations applied to SUV-max provided the highest diagnostic accuracy for characterization of SPNs. Quantification methods using the exact tumour contour derived from CT in combined PET/CT imaging (ROI mean activity within a single transaxial slice and mean tumour volume activity) did not result in improved differentiation between benign and malignant SPN. Obtaining SUV-max might be sufficient in the clinical setting.

Quantitative Investigation of Solitary Pulmonary Nodules: Dynamic Contrast-Enhanced MRI and Histopathologic Analysis

The purposes of this study were to analyze the relation between enhancement patterns on dynamic enhanced MRI and histologic microvessel patterns of solitary pulmonary nodules (SPNs) and to address the topic of false-positive findings in differentiating SPNs with dynamic MRI. Sixty-eight patients with 68 pathologically proven SPNs (diameter <or= 30 mm) underwent dynamic 1.5-T MRI. On time-signal intensity curves generated after bolus injection of contrast material, steepest slope, peak height, and enhancement ratios of signal intensity at the first, second, and fourth minutes were calculated. The relation between dynamic MRI values and microvessel density was analyzed. The morphologic differences between malignant SPNs and active inflammatory SPNs also were analyzed. Threshold dynamic MRI values for differential diagnosis were determined. The dynamic MRI values of benign SPNs were significantly lower than those of the other SPNs (p < 0.01). The enhancement ratio at the fourth minute for active inflammatory SPNs was significantly higher than that of malignant SPNs (p < 0.01). A high correlation coefficient (r = 0.87, p < 0.001) was found between steepest slope and microvessel density. With steepest slope 1.5%/s or less, benign SPNs were clearly differentiated from other SPNs. With enhancement ratio at the fourth minute 65% or less, malignant SPNs were differentiated from active inflammatory SPNs with high sensitivity (93%) and high specificity (100%). Dynamic MRI values reflect the quantitative and morphologic characteristics of microvessels in SPNs and are a useful tool for differentiating SPNs with little overlap.

Computer-aided differentiation of malignant from benign solitary pulmonary nodules imaged by high-resolution CT

We investigated the possibility of using computer analysis of high-resolution CT images to radiologically classify the shape of pulmonary nodules. From a total of 107 HRCT images of solid, solitary pulmonary nodules with prior differentiation as benign ( n = 55) or malignant ( n = 52), we extracted the desired pulmonary nodules and calculated two quantitative parameters for characterizing nodules: circularity and second central moment. Using discriminant analysis for two thresholds in differentiating malignant from benign states resulted in a sensitivity of 76.9%, a specificity of 80%, a positive predictive value of 78.4%, and a negative predictive value of 78.6%.

A Comparison of the Diagnostic Accuracy of18F-FDG PET and CT in the Characterization of Solitary Pulmonary Nodules

CT and PET are widely used to characterize solitary pulmonary nodules (SPNs). However, most CT accuracy studies have been performed with outdated technology and methods, and previous PET studies have been limited by small sample sizes and incomplete masking. Our objective was to compare CT and PET accuracy in veterans with SPN. Between January 1999 and June 2001, we recruited 532 participants with SPNs newly diagnosed on radiography and untreated. The SPNs were 7-30 mm. All patients underwent (18)F-FDG PET and CT. A masked panel of 3 PET and 3 CT experts rated the studies on a 5-point scale. SPN tissue diagnosis or 2-y follow-up established the final diagnosis. A definitive diagnosis was established for 344 participants. The prevalence of malignancy was 53%. The average size was 16 mm. Likelihood ratios (LRs) for PET and CT results for combined ratings of either definitely benign (33% and 9% of patients, respectively) or probably benign (27% and 12%) were 0.10 and 0.11, respectively. LRs for PET and CT results for combined ratings of indeterminate (1% and 25%), probably malignant (21% and 39%), or definitely malignant (35% and 15%) were 5.18 and 1.61, respectively. Area under the receiver operating characteristic curve was 0.93 (95% confidence interval, 0.90-0.95) for PET and 0.82 (95% confidence interval, 0.77-0.86) for CT (P < 0.0001 for the difference). PET inter- and intraobserver reliability was superior to CT. Definitely and probably benign results on PET and CT strongly predict benign SPN. However, such results were 3 times more common with PET. Definitely malignant results on PET were much more predictive of malignancy than were these results on CT. A malignant final diagnosis was approximately 10 times more likely than a benign final diagnosis in participants with PET results rated definitely malignant.

Usefulness of contrast-enhanced magnetic resonance imaging for evaluating solitary pulmonary nodules

Evaluation of solitary pulmonary nodules (SPNs) poses a challenge to radiologists. Chest computed tomography (CT) is considered the standard technique for assessing morphologic findings and intrathoracic spread of an SPN. Although the clinical role of magnetic resonance imaging (MRI) for SPNs remains limited, considerable experience has been gained with MRI of thoracic diseases. Dynamic MRI and dynamic CT are useful for differentiating between malignant and benign SPNs (especially tuberculomas and hamartomas). Furthermore, dynamic MRI is useful for assessing tumor vascularity, interstitium, and vascular endothelial growth factor expression, and for predicting survival outcome among patients with peripheral pulmonary carcinoma. These advantages make dynamic MRI a promising method and a potential biomarker for characterizing tumor response to anti-angiogenic treatment as well as for predicting survival outcomes after treatment.

Neural network-based computer-aided diagnosis in distinguishing malignant from benign solitary pulmonary nodules by computed tomography

Computer-aided diagnosis (CAD) of lung cancer is the subject of many current researches. Statistical methods and artificial neural networks have been applied to more quantitatively characterize solitary pulmonary nodules (SPNs). In this study, we developed a CAD scheme based on an artificial neural network to distinguish malignant from benign SPNs on thin-section computed tomography (CT) images, and investigated how the CAD scheme can help radiologists with different levels of experience make diagnostic decisions. Two hundred thin-section CT images of SPNs with proven diagnoses (135 small peripheral lung cancers and 65 benign nodules) were analyzed. Three clinical features and nine CT signs of each case were studied by radiologists, and the indices of qualitative diagnosis were quantified. One hundred and forty nodules were selected randomly to form training samples, on which the neural network model was built. The remaining 60 nodules, forming test samples, were presented to 9 radiologists with 3 - 20 years of clinical experience, accompanied by standard reference images. The radiologists were asked to determine whether a nodule was malignant or benign first without and then with CAD output. Diagnostic performance was evaluated by receiver operating characteristic (ROC) analysis. CAD outputs on test samples had higher agreement with pathological diagnoses (Kappa = 0.841, P < 0.001). Compared with diagnostic results without CAD output, the average area under the ROC curve with CAD output was 0.96 (P < 0.001) for junior radiologists, 0.94 (P = 0.014) for secondary radiologists and 0.96 (P = 0.221) for senior radiologists, respectively. The differences in diagnostic performance with CAD output among the three levels of radiologists were not statistically significant (P = 0.584, 0.920 and 0.707, respectively). This CAD scheme based on an artificial neural network could improve diagnostic performance and assist radiologists in distinguishing malignant from benign SPNs on thin-section CT images.

Solitary Pulmonary Nodule

Abstract: Solitary pulmonary nodules (SPN) are intraparenchymal radiographic densities within the lung that are smaller than 3 cm and are not associated with other parenchymal, hilar, or mediastinal disease. Tumors that are larger than 3 cm are considered lung masses and are usually malignant. The clinical assessment of SPNs is based on host factors and features of radiographic morphology. Additional special studies may be warranted. Host factors that favor malignancy are age, smoking experience, and oncologic history. Radiographic parameters indicative of malignancy are size, irregular pattern or spiculated borders, suspicious calcifications, and growth rate. In the appropriate setting, a newly identified SPN may result in a benign diagnosis. The typical differential diagnosis includes inflammatory/infectious lesions, congenital or developmental nodules, vascular malformation, or hamartomas. The most common encountered benign SPN are chondrobronchial hamartomas and granulomas. We present 2 interesting cases of unusual solitary pulmonary nodules that were correctly diagnosed during intraoperative consultation with prevention of more extensive tumor surgery.

AJR Teaching File: Solitary Pulmonary Nodule with Enhancing Rim Sign

Clinical History An 84-year-old man presents with a recent cough but does not have fever or chills. On chest radiography, a solitary pulmonary nodule is identified. Because previous chest radiographs are not available for comparison, the lesion is studied with CT. Radiologic Description An axial CT image through a solitary pulmonary nodule acquired before the administration of IV contrast material (Fig. 1A) shows homogeneous soft-tissue density. After administration of IV contrast material (Fig. 1B), the nodule rim enhances more intensely than the central portion. The center of the nodule enhanced 17 H. Differential Diagnosis The differential diagnosis includes granuloma, metastasis, bronchogenic carcinoma, and round atelectasis. Diagnosis The diagnosis in this patient is benign granuloma. Commentary Solitary pulmonary nodules are commonly encountered in clinical practice. Distinguishing benign from malignant processes with imaging can be a challenge. Contrast-enhanced CT can help characterize solitary pulmonary nodules [1-3]. After the IV administration of iodinated contrast material, enhancement of 15 H or less is a strong predictor of benignancy [4]. In a study of 111 nodules that enhanced 15 H or less, 107 (96%) were benign. Of the 245 nodules that enhanced more than 15 H, 167 (68%) were malignant [4]. Using the technique described by Swensen et al. [1], a new finding has been observed in some benign solitary pulmonary nodules. This has been termed the rim sign because it refers to a rim of enhancing soft tissue at the periphery of a solitary pulmonary nodule that surrounds a homogeneous lower.

A primary study of slice optimization of dynamic contrast-enhanced CT scan and its practical application on solitary pulmonary nodules

目的 利用选层重组的方法改善孤立性肺结节(SPN)CT动态增强扫描各延时像测量层面的一致性,并探讨其临床应用价值.方法 (1) 对3种均质液体行CT螺旋扫描并在Z轴方向同层厚任意多平面重组,比较其原始扫描图像及重组图像密度测量值的差异.(2) 对72例SPN 患者行螺旋CT动态增强扫描,运用一定的选层重组的方法保证各延时像测量层面的一致性.并对其中46例经病理及临床证实的SPN 的CT动态增强特点进行评价,评估其增强前后的CT值、强化峰值、SPN与主动脉的强化值比.结果 (1)不同密度的均质液体同层厚的原始扫描图像及重组图像间密度测量值差异无统计学意义(F=1.544,P＞0.05); (2)67例SPN选层重组前、后各延时像测量层面一致率分别为20.98%(14/67)和97.01%(65/67),其差异有统计学意义(χ2=80.22,P=0.00).多层螺旋CT对5例SPN的选层重组全部成功.(3)SPN的CT动态增强各延时像测量层面一致性优化以后,恶性结节与炎性结节强化峰值[(38.48±14.32)、(42.48±11.55)HU] 和结节与主动脉强化值比[(19.64±9.52)、(21.14±7.77)%] 均明显高于良性结节[(9.52±3.78) HU、(3.41±1.86)%];P值均＜0.01. 炎性结节的强化峰值、结节与主动脉强化值比[(42.48±11.55) HU、(21.14±7.77)%]与恶性结节[(38.48±14.32) HU、(19.64±9.52)%]间的差异无统计学意义(P值均＞0.05).CT动态增强选层重组保证各延时像测量层面一致性后,使其对SPN定性的准确率由78%提升至80%. 结论 螺旋CT扫描Z轴方向同层厚任意重组对均质物质的密度值的测量无明显影响.CT动态增强扫描各延时像测量层面一致性的优化可进一步客观反映SPN的动态增强情况,有利于其形态学的比较及CT值的测量,有望提高其对孤立性肺结节鉴别诊断的能力。

Solitary pulmonary nodules: Association between signal characteristics in dynamic contrast enhanced MRI and tumor angiogenesis

To estimate the association between signal characteristic of dynamic enhanced MRI using curve types and angiogenesis in solitary pulmonary nodules. Thirty-six patients with a solitary pulmonary nodule (SPN) ranging in size from 6 to 37 mm (median 17 mm) underwent dynamic contrast enhanced MRI with a time interval of 10 s over a total period of 4 min. Resulting from the time-intensity curves four different enhancement curve profiles (A-D) were defined: type A with strong increase followed by early washout, type B with strong increase without washout, type C with slow increase and type D without relevant increase. Maximum peak (Pmax), slope of the first bolus transit (slope) and washout were calculated. Microvessel densities (MVD) were counted at the margins and at the center of the nodules. The mean MVD of each nodule was calculated. Enhancement characteristics were correlated with MVD grouped by diagnosis and by curve types. Curve types were correlated with the score of vascular endothelial growth factor (VEGF). The frequency of malignancy was 55% (20/36). Using curve types for differentiation between malignant and benign SPN, the sensitivity, specificity and accuracy were 100%, 75% and 89%, respectively. The correlation between Pmax and MVD(mean) for all nodules was moderate (r(s)=0.4, P=0.02). A relevant correlation was found between Pmax and MVD(margin) in curve type A (r(s)=0.63; P=0.04) and Pmax and MVD(mean) in curve type C (r(s)=0.86; P=0.006). No positive correlation was found between Pmax and MVD (mean, center and margin) in curve type B. No significant correlation was found for slope and washout. VEGF score correlated positively with curve types (r(s)=0.67; P<0.001). A relevant association between perfusion curve profiles and angiogenesis was found in malignant nodules having early washout and in benign lesion with a slow increase of enhancement. In cases of strong signal increase without washout additional factors for enhancement must be considered. The use of curve profiles could allow for the estimation of the extent of VEGF.