Can dynamic imaging, using 18F-FDG PET/CT and CT perfusion differentiate between benign and malignant pulmonary nodules?

BACKGROUND: The aim of the study was to derive and compare metabolic parameters relating to benign and malignant pulmonary nodules using dynamic 2-deoxy-2-[fluorine-18]fluoro-D-glucose (18F-FDG) PET/CT, and nodule perfusion parameters derived through perfusion computed tomography (CT). PATIENTS AND METHODS: Twenty patients with 21 pulmonary nodules incidentally detected on CT underwent a dynamic 18F-FDG PET/CT and a perfusion CT. The maximum standardized uptake value (SUVmax) was measured on conventional 18F-FDG PET/CT images. The influx constant (Ki ) was calculated from the dynamic 18F-FDG PET/CT data using Patlak model. Arterial flow (AF) using the maximum slope model and blood volume (BV) using the Patlak plot method for each nodule were calculated from the perfusion CT data. All nodules were characterized as malignant or benign based on histopathology or 2 year follow up CT. All parameters were statistically compared between the two groups using the nonparametric Mann-Whitney test. RESULTS: Twelve malignant and 9 benign lung nodules were analysed (median size 20.1 mm, 9-29 mm) in 21 patients (male/female = 11/9; mean age ± SD: 65.3 ± 7.4; age range: 50-76 years). The average SUVmax values ± SD of the benign and malignant nodules were 2.2 ± 1.7 vs. 7.0 ± 4.5, respectively (p = 0.0148). Average Ki values in benign and malignant nodules were 0.0057 ± 0.0071 and 0.0230 ± 0.0155 min-1, respectively (p = 0.0311). Average BV for the benign and malignant nodules were 11.6857 ± 6.7347 and 28.3400 ± 15.9672 ml/100 ml, respectively (p = 0.0250). Average AF for the benign and malignant nodules were 74.4571 ± 89.0321 and 89.200 ± 49.8883 ml/100g/min, respectively (p = 0.1613). CONCLUSIONS: Dynamic 18F-FDG PET/CT and perfusion CT derived blood volume had similar capability to differentiate benign from malignant lung nodules.

Correlation study between dual source CT perfusion imaging and the microvascular composition of solitary pulmonary nodules.

OBJECTIVE: To explore the correlation between dual source computed tomography perfusion imaging (CTPI) and microvascular parameters, and evaluate the value of CTPI in the differential diagnosis of solitary pulmonary nodule (SPN). METHODS: 65 consecutive patients with SPN who successfully underwent pre-operative CT perfusion imaging with dual source CT and received a final diagnosis by postoperative pathology. The cases were divided into malignant, benign and inflammatory groups according to the pathological results. CT perfusion parameters, such as blood flow (BF), blood volume (BV), mean transit time (MTT) and permeability surface (PMB) were obtained by performing CTPI of SPNs. The postoperative specimens of SPNs were immunohistochemically stained for CD34 and SMA to detect microvessel density (MVD) and luminal vascular parameters, such as luminal vascular number (LVN), luminal vascular area (LVA) and luminal vascular perimeter (LVP). The receiver operating characteristic (ROC) curve was used to assess the diagnostic efficiency of CT perfusion parameter in diagnosing malignant SPNs. RESULTS: In these 65 cases, malignant, benign and inflammatory SPNs were respectively 39, 14 and 12 cases. Significant difference was observed in LVN/MVD, LVA and LVP among the three groups (P < 0.05). The correlation between CT perfusion parameters (BF, BV and PMB) and the luminal vascular parameters was stronger than that with MVD (P < 0.05). PMB has the strongest correlation with LVN/MVD. Using BF≥60ml/100ml/min, BV≥6.34ml/100ml and PMB≥13.35ml/100 ml/min for the diagnosis, the area under the curve (AUC) of the ROC curve was 0.760, the sensitivity was 82% and the specificity was 61%. CONCLUSIONS: The main indicators reflecting blood perfusion of SPN are the degree of lumen or maturity of microvessels (LVN, LVA and LVP), not just the number of microvessels (e.g. MVD). CT perfusion imaging can be used as an important method to non-invasively evaluate tumour angiogenesis and help to distinguish malignant SPNs from benign and inflammatory SPNs.

Vasculature surrounding a nodule: A novel lung cancer biomarker.

PURPOSE: To investigate whether the vessels surrounding a nodule depicted on non-contrast, low-dose computed tomography (LDCT) can discriminate benign and malignant screen detected nodules. MATERIALS AND METHODS: We collected a dataset consisting of LDCT scans acquired on 100 subjects from the Pittsburgh Lung Screening study (PLuSS). Fifty subjects were diagnosed with lung cancer and 50 subjects had suspicious nodules later proven benign. For the lung cancer cases, the location of the malignant nodule in the LDCT scans was known; while for the benign cases, the largest nodule in the LDCT scan was used in the analysis. A computer algorithm was developed to identify surrounding vessels and quantify the number and volume of vessels that were connected or near the nodule. A nonparametric receiver operating characteristic (ROC) analysis was performed based on a single nodule per subject to assess the discriminability of the surrounding vessels to provide a lung cancer diagnosis. Odds ratio (OR) were computed to determine the probability of a nodule being lung cancer based on the vessel features. RESULTS: The areas under the ROC curves (AUCs) for vessel count and vessel volume were 0.722 (95% CI=0.616-0.811, p<0.01) and 0.676 (95% CI=0.565-0.772), respectively. The number of vessels attached to a nodule was significantly higher in the lung cancer group 9.7 (±9.6) compared to the non-lung cancer group 4.0 (±4.3) CONCLUSION: Our preliminary results showed that malignant nodules are often surrounded by more vessels compared to benign nodules, suggesting that the surrounding vessel characteristics could serve as lung cancer biomarker for indeterminate nodules detected during LDCT lung cancer screening using only the information collected during the initial visit.

Solitary pulmonary nodules: Comparison of dynamic first-pass contrast-enhanced perfusion area-detector CT, dynamic first-pass contrast-enhanced MR imaging, and FDG PET/CT.

PURPOSE: To prospectively compare the capabilities of dynamic perfusion area-detector computed tomography (CT), dynamic magnetic resonance (MR) imaging, and positron emission tomography (PET) combined with CT (PET/CT) with use of fluorine 18 fluorodeoxyglucose (FDG) for the diagnosis of solitary pulmonary nodules. MATERIALS AND METHODS: The institutional review board approved this study, and written informed consent was obtained from each subject. A total of 198 consecutive patients with 218 nodules prospectively underwent dynamic perfusion area-detector CT, dynamic MR imaging, FDG PET/CT, and microbacterial and/or pathologic examinations. Nodules were classified into three groups: malignant nodules (n = 133) and benign nodules with low (n = 53) or high (n = 32) biologic activity. Total perfusion was determined with dual-input maximum slope models at area-detector CT, maximum and slope of enhancement ratio at MR imaging, and maximum standardized uptake value (SUVmax) at PET/CT. Next, all indexes for malignant and benign nodules were compared with the Tukey honest significant difference test. Then, receiver operating characteristic analysis was performed for each index. Finally, sensitivity, specificity, and accuracy were compared with the McNemar test. RESULTS: All indexes showed significant differences between malignant nodules and benign nodules with low biologic activity (P < .0001). The area under the receiver operating characteristic curve for total perfusion was significantly larger than that for other indexes (.0006 ≤ P ≤ .04). The specificity and accuracy of total perfusion were significantly higher than those of maximum relative enhancement ratio (specificity, P < .0001; accuracy, P < .0001), slope of enhancement ratio (specificity, P < .0001; accuracy, P < .0001), and SUVmax (specificity, P < .0001; accuracy, P < .0001). CONCLUSION: Dynamic perfusion area-detector CT is more specific and accurate than dynamic MR imaging and FDG PET/CT in the diagnosis of solitary pulmonary nodules in routine clinical practice.

Intraoperative near-infrared imaging can identify pulmonary nodules.

BACKGROUND: Over 80,000 people undergo pulmonary resection for a lung nodule in the United States each year. Small nodules are frequently missed or difficult to find despite preoperative imaging. We hypothesized that near-infrared (NIR) imaging technology could be used to identify and locate lung nodules during surgery. METHODS: We enrolled 18 patients who were diagnosed with a pulmonary nodule that required resection. All patients had a fine-cut 1-mm computed tomography scan preoperatively. The patients were given systemic 5 mg/kg indocyanine green and then underwent an open thoracotomy 24 hours later. The NIR imaging was used to identify the primary nodule and search for additional nodules that were not found by visual inspection or manual palpation of the ipsilateral lung. RESULTS: Manual palpation and visual inspection identified all 18 primary pulmonary nodules and no additional lesions. Intraoperative NIR imaging detected 16 out of the 18 primary nodules. The NIR imaging also identified 5 additional subcentimeter nodules; 3 metastatic adenocarcinomas and 2 metastatic sarcomas. This technology could identify nodules as small as 0.2 cm and as deep as 1.3 cm from the pleural surface. This approach discovered 3 nodules that were in different lobes than the primary tumor. Nodule fluorescence was independent of size, metabolic activity, histology, tumor grade and vascularity. CONCLUSIONS: This is the first-in-human demonstration of identifying pulmonary nodules during thoracic surgery with NIR imaging without a priori knowledge of their location or existence. The NIR imaging can detect pulmonary nodules during lung resections that are poorly visualized on computed tomography and difficult to discriminate on finger palpation.

Multi-detector spiral CT study of the relationships between pulmonary ground-glass nodules and blood vessels.

OBJECTIVE: To investigate the relationships between pulmonary ground-glass nodules (GGN) and blood vessels and their diagnostic values in differentiating GGNs. METHODS: Multi-detector spiral CT imaging of 108 GGNs was retrospectively reviewed. The spatial relationships between GGNs and supplying blood vessels were categorized into four types: I, vessels passing by GGNs; II, intact vessels passing through GGNs; III, distorted, dilated or tortuous vessels seen within GGNs; IV, more complicated vasculature other than described above. Relationship types were correlated to pathologic and/or clinical findings of GGNs. RESULTS: Of 108 GGNs, 10 were benign, 24 preinvasive nodules and 74 adenocarcinomas that were pathologically proven. Types I, II, III and IV vascular relationships were observed in 9, 58, 21 and 20 GGNs, respectively. Type II relationship was the dominating relationship for each GGN group, but significant differences were shown among them. Correlation analysis showed strong correlation between invasive adenocarcinoma and type III and IV relationships. Subgroup analysis indicated that type III was more commonly seen in IAC with comparison to type IV more likely seen in MIA. CONCLUSION: Different GGNs have different relationships with vessels. Understanding and recognising characteristic GGN-vessel relationships may help identify which GGNs are more likely to be malignant.

Detection of pulmonary nodules in CT images based on fuzzy integrated active contour model and hybrid parametric mixture model.

The segmentation and detection of various types of nodules in a Computer-aided detection (CAD) system present various challenges, especially when (1) the nodule is connected to a vessel and they have very similar intensities; (2) the nodule with ground-glass opacity (GGO) characteristic possesses typical weak edges and intensity inhomogeneity, and hence it is difficult to define the boundaries. Traditional segmentation methods may cause problems of boundary leakage and "weak" local minima. This paper deals with the above mentioned problems. An improved detection method which combines a fuzzy integrated active contour model (FIACM)-based segmentation method, a segmentation refinement method based on Parametric Mixture Model (PMM) of juxta-vascular nodules, and a knowledge-based C-SVM (Cost-sensitive Support Vector Machines) classifier, is proposed for detecting various types of pulmonary nodules in computerized tomography (CT) images. Our approach has several novel aspects: (1) In the proposed FIACM model, edge and local region information is incorporated. The fuzzy energy is used as the motivation power for the evolution of the active contour. (2) A hybrid PMM Model of juxta-vascular nodules combining appearance and geometric information is constructed for segmentation refinement of juxta-vascular nodules. Experimental results of detection for pulmonary nodules show desirable performances of the proposed method.

Preliminary study on the correlation between grading and histology of solitary pulmonary nodules and contrast enhancement and [18F]fluorodeoxyglucose standardised uptake value after evaluation by dynamic multiphase CT and PET/CT.

AIM: To evaluate whether the histology and grading of solitary pulmonary nodules (SPNs) correlated with the results of dynamic multiphase multidetector CT (MDCT) and the [(18)F]fluorodeoxyglucose standardised uptake value (SUV) in 30 patients. METHODS: Chest x-rays of 270 patients with incidentally detected SPNs were retrospectively evaluated. Thirty patients with histologically proven SPNs were enrolled. On MDCT and positron emission tomography (PET)/CT images, two experts measured the density of nodules in all perfusion phases and the SUV. Net enhancement (NE) was calculated by subtracting peak pre-contrast density from peak post-contrast density. The Pearson test was used to correlate nodule NE, SUV, grading, histology and diameter. RESULTS: Of the 30 malignant SPNs, six were classified as G1 (median NE, 31.5 Hounsfield units (HU); median SUV, 4.8 units), 15 were classified as G2 (median NE, 49 HU; median SUV, 6 units), and nine were classified as G3 (median NE, 32 HU; median SUV, 4.5 units). A highly negative correlation was found in G3 SPNs between NE and the corresponding diameters (r=-0.834; p=0.00524). NE increased with the increase in diameter (r=0.982; p=0.284). SUV increased as the SPN diameter increased (r=0.789; p=0.421). NE and SUV were higher in G2 than G1 SPNs, and lower in G2 than G3 SPNs (r=0.97; p=0.137). CONCLUSIONS: The significant correlation in dedifferentiated (G3) SPNs between NE and diameter (r=-0.834; p=0.00524) supports the theory that stroma and neoangiogenesis are fundamental in SPN growth. The highly negative correlation between NE and diameter demonstrates a net decrease in perfusion despite an increase in dimension. The multidisciplinary approach used herein may result in a more precise prognosis and consequently a better therapeutic outcome, particularly in patients with undifferentiated lung cancer.

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.

[Correlation between multi-slice spiral CT pulmonary perfusion imaging and cavity of microvessel in lung cancer].

OBJECTIVE: To investigate the relation between multi-slice spiral CT pulmonary perfusion imaging and the cavity of microvessel in lung cancer. METHODS: Altogether 36 patients with malignant nodules who underwent multi-slice spiral CT perfusion scan were examined.The perfusion parameters were collected and compared with the microvessel density (MVD), the incomplete lumen MVD, and the differentiation of non-small cell lung cancer (NSCLC). The patients were divided into a hyper-perfusion group and a hypo-perfusion group by the value of perfusion parameters. The maturity of microvessel and the degree of differentiation in NSCLC between the 2 groups was analyzed. RESULTS: Blood flow (BF), blood volume (BV), and peak enhancement image(PEI) of the malignant nodules were (39.7±11.5) mL/(100 mg.min), (8.6±3.8)mL/100 g, and (20.1±8.6)HU, respectively. There was a positive correlation between PEI and MVD(r=0.645,P<0.01), and a negative correlation between BF and MVD(r=-0.280,P=0.048). There were negative correlations of BF, BV, PEI with the incomplete lumen MVD (P<0.05). BF had the highest correlation coefficient(r=-0.882,P<0.01).The incomplete lumen MVD of the hyper-perfusion group was significantly lower than that of hypo-perfusion group (P<0.05),but there was no significant difference in MVD between the 2 groups. There were negative correlations of BF, BV,PEI with the degree of differentiation (P<0.05). BF had the highest correlation coefficient(r=-0.751,P<0.01). CONCLUSION: Multi-slice spiral CT pulmonary perfusion imaging is helpful to evaluate the degree of differentiation and status of angiogenesis in lung cancer, and its basis is the cavity of microvessel.

Dynamic enhancement patterns of solitary pulmonary nodules at multi-detector row CT and correlation with vascular endothelial growth factor and microvessel density.

BACKGROUND AND OBJECTIVE: Differential diagnosis of malignant solitary pulmonary nodules (SPNs) from benign ones is difficult based on imaging manifestations. This study was to assess dynamic enhancement patterns of SPNs detected with multi-detector row computed tomography (MDCT), correlate SPN manifestations of MDCT to the expression of vascular endothelial growth factor (VEGF) and microvessel density (MVD), thus to explore the potential value of MDCT imaging in the diagnosis of SPNs. METHODS: Fifty pathologically and one clinically confirmed patients with SPNs (diameter

Peripheral pulmonary nodules: relationship between multi-slice spiral CT perfusion imaging and tumor angiogenesis and VEGF expression.

BACKGROUND: The aim of this study is to investigate the relationship between 16-slice spiral CT perfusion imaging and tumor angiogenesis and VEGF (vascular endothelial growth factor) expression in patients with benign and malignant pulmonary nodules, and differential diagnosis between benign and malignant pulmonary nodules. METHODS: Sixty-four patients with benign and malignant pulmonary nodules underwent 16-slice spiral CT perfusion imaging. The CT perfusion imaging was analyzed for TDC (time density curve), perfusion parametric maps, and the respective perfusion parameters. Immunohistochemical findings of MVD (microvessel density) measurement and VEGF expression was evaluated. RESULTS: The shape of the TDC of peripheral lung cancer was similar to those of inflammatory nodule. PH (peak height), PHpm/PHa (peak height ratio of pulmonary nodule to aorta), BF (blood flow), BV (blood volume) value of peripheral lung cancer and inflammatory nodule were not statistically significant (all P > 0.05). Both showed significantly higher PH, PHpm/PHa, BF, BV value than those of benign nodule (all P < 0.05). Peripheral lung cancer showed significantly higher PS (permeability surface) value than that of inflammatory nodule and benign nodule (all P < 0.05). BV, BF, PS, MTT, PH, PHpm/PHa, and MVD among three groups of peripheral lung cancers were not significantly (all P > 0.05). In the case of adenocarcinoma, BV, BF, PS, PHpm/PHa, and MVD between poorly and well differentiation and between poorly and moderately differentiation were statistically significant (all P < 0.05). The peripheral lung cancers with VEGF positive expression showed significantly higher PH, PHpm/PHa, BF, BV, PS, and MVD value than those of the peripheral lung cancer with VEGF negative expression, and than those of benign nodule with VEGF positive expression (all P < 0.05). When investigating VEGF negative expression, it is found that PH, PHpm/PHa, and MVD of inflammatory nodule were significantly higher than those of peripheral lung cancer, PS of inflammatory nodule were significantly lower than that of peripheral lung cancer (all P < 0.05). PH, PHpm/PHa, BF, and BV of benign nodule were significantly lower than those of inflammatory nodule (all P < 0.05), rather than PS and MTT (mean transit time) (all P > 0.05). PH, PHpm/PHa, BV, and PS of benign nodule were significantly lower than those of peripheral lung cancer (all P < 0.05). In the case of VEGF positive expression, MVD was positively correlated with PH, PHpm/PHa, BF, BV, and PS of peripheral lung cancer and PS of benign nodule (all P < 0.05). CONCLUSION: Multi-slice spiral CT perfusion imaging closely correlated with tumor angiogenesis and reflected MVD measurement and VEGF expression. It provided not only a non-invasive method of quantitative assessment for blood flow patterns of peripheral pulmonary nodules but also an applicable diagnostic method for peripheral pulmonary nodules.

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.

[Combined scores of 64 multi-slice CT perfusion characteristics for evaluating solitary pulmonary nodules].

OBJECTIVE: To study the bloody flow mode and the perfusion feature of solitary pulmonary nodules (SPN) on 64 multi-slice CT, and to evaluate the diagnostic value of combined scores in SPN. METHODS: Fifty-two patients with SPN proved by pathology or follow-up underwent dynamic enhancement CT. Perfusion characteristics, including permeability (P), blood flow, blood volume, patlak blood volume, patlak R square (PRS), patlak residual, peak enhancement, perfusion curve, and false color image were analyzed by the body perfusion software. Perfusion characteristics were compared between benign and malignant nodules. Combined scores composed of significant difference observed parameters were used to differentiate benign or malignant SPN. RESULTS: There were significant differences in the enhancement values at 20, 22, 24, 25, 26, 28, 30, and 34s, PRS, I or II type perfusion curve, and marginal uncomplete enhancement or patchy complete enhancement at 34s between benign and malignant SPN. With the multi-variant combined score > 0.5 as the threshold value to differentiate benign and malignant SPN, its sensitivity and specificity was 94.3% and 41.2%, respectively. CONCLUSION: The combined scores of 64 multi-slice CT can help differentiate the benign or malignant SPN.

Vessel tree reconstruction in thoracic CT scans with application to nodule detection.

Vessel tree reconstruction in volumetric data is a necessary prerequisite in various medical imaging applications. Specifically, when considering the application of automated lung nodule detection in thoracic computed tomography (CT) scans, vessel trees can be used to resolve local ambiguities based on global considerations and so improve the performance of nodule detection algorithms. In this study, a novel approach to vessel tree reconstruction and its application to nodule detection in thoracic CT scans was developed by using correlation-based enhancement filters and a fuzzy shape representation of the data. The proposed correlation-based enhancement filters depend on first-order partial derivatives and so are less sensitive to noise compared with Hessian-based filters. Additionally, multiple sets of eigenvalues are used so that a distinction between nodules and vessel junctions becomes possible. The proposed fuzzy shape representation is based on regulated morphological operations that are less sensitive to noise. Consequently, the vessel tree reconstruction algorithm can accommodate vessel bifurcation and discontinuities. A quantitative performance evaluation of the enhancement filters and of the vessel tree reconstruction algorithm was performed. Moreover, the proposed vessel tree reconstruction algorithm reduced the number of false positives generated by an existing nodule detection algorithm by 38%.

[The value of three-phase pulmonary helical CT in diagnosing peripheral pulmonary cancer (diameter

OBJECTIVE: To evaluate the value of three-phase pulmonary helical CT in diagnosing peripheral pulmonary cancer (diameter

[Value of serum-vascular endothelial growth factor in the differential diagnosis of solitary pulmonary nodule].

OBJECTIVE: To evaluate serum-vascular endothelial growth factor (S-VEGF) in the differentiation of solitary pulmonary nodule (SPN). METHODS: Serum level of VEGF of 68 patients with SPN was measured by ELISA kit, and compared with the control group of 20 normal subjects. The nodules were diagnosed by operation and pathology. RESULTS: The median level of S-VEGF was 42.5 (range from 10 to 170) pg/ml in the control, 44 (range from 18 to 360) pg/ml in benign nodule group and 75 (range from 18 to 890) pg/ml in lung cancer group, with significant difference observed between the nodule group and control (P < 0.01), and between the lung cancer group and the benign nodule group (P < 0.05), but not between the benign nodule group and the control. In addition, when S-VEGF in different pathologic types of the limited number of lung cancer patients were compared, no significant difference was observed. CONCLUSION: S-VEGF is valuable in the differential diagnosis of solitary pulmonary nodule. An elevated S-VEGF level >or= 100 pg/ml in patients with SPN may strongly speak for a malignant nodule. Operation is suggested.