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

Diagnostic accuracy of low-dose dual-input computed tomography perfusion in the differential diagnosis of pulmonary benign and malignant ground-glass nodules

This study aimed to evaluate the value of low-dose dual-input computed tomography perfusion (CTP) imaging in the differential diagnosis of benign and malignant pulmonary ground-glass opacity nodules (GGO). A retrospective study was conducted in patients with GGO who underwent CTP in our hospital from January 2021 to October 2023. All nodules were confirmed via pathological analysis or disappeared during follow-up. Postprocessing analysis was conducted using the dual-input perfusion mode (pulmonary artery and bronchial artery) of the body perfusion software to measure the perfusion parameters of the pulmonary GGOs. A total of 101 patients with pulmonary GGOs were enrolled in this study, including 43 benign and 58 malignant nodules. The dose length product of the CTP (348 mGy.cm) was < 75% of the diagnostic reference level of the unenhanced chest CT (470 mGy.cm). The effective radiation dose was 4.872 mSV. The blood flow (BF), blood volume (BV), mean transit time (MTT), and flow extraction product (FEP) of malignant nodules were higher than those of the benign nodules (p < 0.05). The FEP had the highest accuracy for the diagnosis of malignant nodules (area under the curve [AUC] = 0.821, 95% confidence interval [CI]: 0.735-0.908) followed by BV (AUV = 0.713, 95% CI 0.608-0.819), BF (AUC = 0.688, 95% CI 0.587-0.797), and MTT (AUC = 0.616, 95% CI 0.506-0.726). When the FEP was ≥ 19.12 mL/100 mL/min, the sensitivity was 91.5% and the specificity was 62.8%. To distinguish between benign nodules and malignant nodules, the AUC of the combination of BV and FEP was 0.816 (95% CI 0.728-0.903), whereas the AUC of the combination of BF, BV, MTT, and FEP was 0.814 (95% CI 0.729-0.900). Low-dose dual-input perfusion CT was extremely effective in distinguishing between benign from malignant pulmonary GGOs, with FEP exhibiting the highest diagnostic capability.

The Role of CT Perfusion in Differentiating Benign Versus Malignant Focal Pulmonary Lesions

BACKGROUND

Contrast-enhanced CT scan is the standard imaging for the characterization and evaluation of focal parenchymal lung lesions. It relies on morphology and enhancement patterns for the characterization of lung lesions. However, there is significant overlap among imaging features of various malignant and benign lesions. Hence, it is often necessary to obtain tissue diagnosis with invasive percutaneous or endoscopic-guided tissue sampling. It is often desirable to have non-invasive techniques that can differentiate malignant and benign lung lesions. CT perfusion is an emerging CT technology that allows functional assessment of tissue vascularity through various parameters and can help in differentiating benign and malignant focal lung lesions.

OBJECTIVE

The purpose of this study was to assess the role of the CT perfusion technique in differentiating malignant and benign focal parenchymal lung lesions.

MATERIALS AND METHODS

In this prospective observational study, CT perfusion was performed on 41 patients with focal parenchymal lung lesions from December 2020 to June 2022. The four-dimensional range was planned to cover the entire craniocaudal extent of the lesion, followed by a volume perfusion CT (VPCT) of the lesion. A total of 27 dynamic datasets were acquired with a scan interval of 1.5 seconds and a total scan time of 42 seconds. CT perfusion parameters of blood flow (BF), blood volume (BV), and k-trans of the lesion were measured with mathematical algorithms available in the Syngo.via CT perfusion software (Siemens Healthcare, Erlangen, Germany).

RESULTS

The median BV in benign lesions was found to be 5.5 mL/100 g, with an interquartile range of 3.3-6.9 and a p-value < 0.001. The median BV in malignant lesions was found to be 11.35 mL/100 g, with an interquartile range of 9.57-13.21 and a p-value ≤ 0.001. The median BF for benign lesions was 45.5 mL/100 g/min, with an interquartile range of 33.8-48.5 and a p-value ≤ 0.001. The median BF for malignant lesion was 61.77 mL/100 g/min, with an interquartile range of 33.8-48.5 and a p-value ≤ 0.001. The median k-trans in the case of benign lesions was found to be 4.2 mL/100 g/min, with an interquartile range of 3.13-6.8 and a p-value ≤ 0.001. The median k-trans in the case of the malignant lesion was found to be 12.05 mL/100g/min, with an interquartile range of 7.20-33.42 and a p-value < 0.001. Our study has also shown BV to have an accuracy of 92.68%, sensitivity of 93.3%, and specificity of 90.01%.

CONCLUSION

Our study has shown that CT perfusion values of BV, BF, and k-trans can be used to differentiate between benign and malignant focal lung parenchymal lesions. K-trans is the most sensitive parameter while BV and BF have greater accuracy and specificity.

Area-Detector Computed Tomography for Pulmonary Functional Imaging

An area-detector CT (ADCT) has a 320-detector row and can obtain isotropic volume data without helical scanning within an area of nearly 160 mm. The actual-perfusion CT data within this area can, thus, be obtained by means of continuous dynamic scanning for the qualitative or quantitative evaluation of regional perfusion within nodules, lymph nodes, or tumors. Moreover, this system can obtain CT data with not only helical but also step-and-shoot or wide-volume scanning for body CT imaging. ADCT also has the potential to use dual-energy CT and subtraction CT to enable contrast-enhanced visualization by means of not only iodine but also xenon or krypton for functional evaluations. Therefore, systems using ADCT may be able to function as a pulmonary functional imaging tool. This review is intended to help the reader understand, with study results published during the last a few decades, the basic or clinical evidence about (1) newly applied reconstruction methods for radiation dose reduction for functional ADCT, (2) morphology-based pulmonary functional imaging, (3) pulmonary perfusion evaluation, (4) ventilation assessment, and (5) biomechanical evaluation.

The Diagnostic Accuracy of a Novel Scoring System Using Multi-Detector Computed Tomography to Diagnose Lung Cancer

INTRODUCTION

Lung cancer is the leading cause amongst the cancer deaths in the world. Detection of malignancy at an early stage and with precision is the utmost objective of radiological evaluation. The final diagnosis of lung cancer is histopathological evaluation of the mass. The authors hereby have tried to convert the multi-detector CT (MDCT) characteristics and patient demographics into quantitative data to formulate a scoring system that can predict lung malignancy as close to histopathology as possible.

MATERIALS AND METHODS

After obtaining ethical clearance, 104 cases of suspected lung cancer by history, clinical and radiographic evaluation were enrolled in the study. These patients were undergoing CT thorax (contrast) on 384 slice siemens somatom force. After undergoing the radiological evaluation biopsy of the mass was done either by CT guided or bronchoscopy guided. Radiological and histopathological findings were correlated. Patients aged >50, lymphadenopathy, tumor volume >50 cc, enhancement >15 HU (Hounsfield unit) after contrast injection were given a score of 15 each. History of smoking, bronchus cut off, spiculated/lobulated margins, mediastinal/pleural involvement, and angiogram sign positive were given a score of 20 each. So, a maximum score of 160 can be achieved by history and MDCT evaluation.

RESULTS

Sensitivity, specificity, positive predictive values (PPV), negative predictive values (NPV), and diagnostic accuracy of MDCT by using conventional parameters against histopathology was 97.5%, 85%, 96.29%, 89.47%, and 95.0%. The sensitivity and specificity calculated through Receiver-Operating-Characteristic (ROC) for predicting malignancy were found to be 98.8% and 90.0% for a cut-off score of >97.5 out of maximum of 160.  Conclusion: MDCT serves as a tool for early diagnosis of lung cancer, and it is the utmost important tool for cases where biopsy or fine needle aspiration cytology (FNAC) is not possible. By creating a quantitative criterion to diagnose lung malignancy, the subjective nature of MDCT diagnosis can be converted into an objective based evaluation.

Multimodality CT imaging contributes to improving the diagnostic accuracy of solitary pulmonary nodules: a multi-institutional and prospective study

BACKGROUND

Solitary pulmonary nodules (SPNs) are one of the most common chest computed tomography (CT) abnormalities clinically. We aimed to investigate the value of non-contrast enhanced CT (NECT), contrast enhanced CT (CECT), CT perfusion imaging (CTPI), and dual- energy CT (DECT) used for differentiating benign and malignant SPNs with a multi-institutional and prospective study.

PATIENTS AND METHODS

Patients with 285 SPNs were scanned with NECT, CECT, CTPI and DECT. Differences between the benign and malignant SPNs on NECT, CECT, CTPI, and DECT used separately (NECT combined with CECT, DECT, and CTPI were methods of A, B, and C) or in combination (Method A + B, A + C, B + C, and A + B + C) were compared by receiver operating characteristic curve analysis.

RESULTS

Multimodality CT imaging showed higher performances (sensitivities of 92.81% to 97.60%, specificities of 74.58% to 88.14%, and accuracies of 86.32% to 93.68%) than those of single modality CT imaging (sensitivities of 83.23% to 85.63%, specificities of 63.56% to 67.80%, and accuracies of 75.09% to 78.25%, all p < 0.05).

CONCLUSIONS

SPNs evaluated with multimodality CT imaging contributes to improving the diagnostic accuracy of benign and malignant SPNs. NECT helps to locate and evaluate the morphological characteristics of SPNs. CECT helps to evaluate the vascularity of SPNs. CTPI using parameter of permeability surface and DECT using parameter of normalized iodine concentration at the venous phase both are helpful for improving the diagnostic performance.

Dual-energy computed tomography iodine uptake in differential diagnosis of inflammatory and malignant pulmonary nodules

PURPOSE The aim of this study was to evaluate the diagnostic performance of iodine uptake parameters using dual-energy computed tomography (DECT) in discriminating inflammatory nodules from malignant tumors. METHODS This retrospective study included 116 solid pulmonary nodules from 112 patients who were admitted to our hospital between January and September 2018. All nodules were confirmed by surgery or puncture. The degree of enhancement of a single-section region of interest was evalu ated. After total tumor volume-of-interest segmentation, the mean iodine density of the whole tumor was measured. Meanwhile, iodine uptake parameters, including total iodine uptake vol ume, total iodine concentration, vital iodine uptake volume, and vital iodine concentration, were calculated, and a predictive model was established. The overall ability to discriminate between inflammatory and malignant nodules was analyzed using an independent samples t-test for normally distributed variables. The diagnostic accuracy and prognostic performance of DECT parameters were evaluated and compared using receiver operating characteristic curve analysis and logistic regression analysis. A multivariate logistic regression analysis was used to determine the prognostic factors and goodness-of-fit of the whole tumor mean iodine and iodine uptake parameters for discriminating malignant nodules. RESULTS There were 116 non-calcified nodules, including 64 inflammatory nodules and 52 malignant nodules. The degree of enhancement in malignant nodules was significantly lower than that in inflammatory nodules (P=.043). All iodine uptake parameters in malignant nodules were signifi cantly higher than those in inflammatory nodules (P < .001). The area under the receiver operat ing curve value, accuracy, sensitivity, and specificity of the established model based on iodine uptake parameters were 0.803, 76.72%, 82.69%, and 84.37%, respectively, which exhibited bet ter diagnostic performance than the degree of enhancement on weighted average images with respective values of 0.609, 59.48%, 61.54%, and 59.38%. CONCLUSION The iodine uptake parameters of DECT exhibited better diagnostic accuracy in discriminating inflammatory nodules from malignant nodules than the degree of enhancement on weighted average images.

Combined model of radiomics, clinical, and imaging features for differentiating focal pneumonia-like lung cancer from pulmonary inflammatory lesions: an exploratory study

Background

Only few studies have focused on differentiating focal pneumonia-like lung cancer (F-PLC) from focal pulmonary inflammatory lesion (F-PIL). This exploratory study aimed to evaluate the clinical value of a combined model incorporating computed tomography (CT)-based radiomics signatures, clinical factors, and CT morphological features for distinguishing F-PLC and F-PIL.

Methods

In total, 396 patients pathologically diagnosed with F-PLC and F-PIL from two medical institutions between January 2015 and May 2021 were retrospectively analyzed. Patients from center 1 were included in the training (n = 242) and internal validation (n = 104) cohorts. Moreover, patients from center 2 were classified under the external validation cohort (n = 50). The clinical and CT morphological characteristics of both groups were compared first. And then, a clinical model incorporating clinical and CT morphological features, a radiomics model reflecting the radiomics signature of lung lesions, and a combined model were developed and validated, respectively.

Results

Age, gender, smoking history, respiratory symptoms, air bronchogram, necrosis, and pleural attachment differed significantly between the F-PLC and F-PIL groups (all P < 0.05). For the clinical model, age, necrosis, and pleural attachment were the most effective factors to differentiate F-PIL from F-PLC, with the area under the curves (AUCs) of 0.838, 0.819, and 0.717 in the training and internal and external validation cohorts, respectively. For the radiomics model, five radiomics features were found to be significantly related to the identification of F-PLC and F-PIL (all P < 0.001), with the AUCs of 0.804, 0.877, and 0.734 in the training and internal and external validation cohorts, respectively. For the combined model, five radiomics features, age, necrosis, and pleural attachment were independent predictors for distinguishing between F-PLC and F-PIL, with the AUCs of 0.915, 0.899, and 0.805 in the training and internal and external validation cohorts, respectively. The combined model exhibited a better performance than had the clinical and radiomics models.

Conclusions

The combined model, which incorporates CT-based radiomics signatures, clinical factors, and CT morphological characteristics, is effective in differentiating F-PLC from F-PIL.

Dynamic contrast-enhanced CT compared with positron emission tomography CT to characterise solitary pulmonary nodules: the SPUtNIk diagnostic accuracy study and economic modelling

BACKGROUND

Current pathways recommend positron emission tomography-computerised tomography for the characterisation of solitary pulmonary nodules. Dynamic contrast-enhanced computerised tomography may be a more cost-effective approach.

OBJECTIVES

To determine the diagnostic performances of dynamic contrast-enhanced computerised tomography and positron emission tomography-computerised tomography in the NHS for solitary pulmonary nodules. Systematic reviews and a health economic evaluation contributed to the decision-analytic modelling to assess the likely costs and health outcomes resulting from incorporation of dynamic contrast-enhanced computerised tomography into management strategies.

DESIGN

Multicentre comparative accuracy trial.

SETTING

Secondary or tertiary outpatient settings at 16 hospitals in the UK.

PARTICIPANTS

Participants with solitary pulmonary nodules of ≥ 8 mm and of ≤ 30 mm in size with no malignancy in the previous 2 years were included.

INTERVENTIONS

Baseline positron emission tomography-computerised tomography and dynamic contrast-enhanced computer tomography with 2 years' follow-up.

MAIN OUTCOME MEASURES

Primary outcome measures were sensitivity, specificity and diagnostic accuracy for positron emission tomography-computerised tomography and dynamic contrast-enhanced computerised tomography. Incremental cost-effectiveness ratios compared management strategies that used dynamic contrast-enhanced computerised tomography with management strategies that did not use dynamic contrast-enhanced computerised tomography.

RESULTS

A total of 380 patients were recruited (median age 69 years). Of 312 patients with matched dynamic contrast-enhanced computer tomography and positron emission tomography-computerised tomography examinations, 191 (61%) were cancer patients. The sensitivity, specificity and diagnostic accuracy for positron emission tomography-computerised tomography and dynamic contrast-enhanced computer tomography were 72.8% (95% confidence interval 66.1% to 78.6%), 81.8% (95% confidence interval 74.0% to 87.7%), 76.3% (95% confidence interval 71.3% to 80.7%) and 95.3% (95% confidence interval 91.3% to 97.5%), 29.8% (95% confidence interval 22.3% to 38.4%) and 69.9% (95% confidence interval 64.6% to 74.7%), respectively. Exploratory modelling showed that maximum standardised uptake values had the best diagnostic accuracy, with an area under the curve of 0.87, which increased to 0.90 if combined with dynamic contrast-enhanced computerised tomography peak enhancement. The economic analysis showed that, over 24 months, dynamic contrast-enhanced computerised tomography was less costly (£3305, 95% confidence interval £2952 to £3746) than positron emission tomography-computerised tomography (£4013, 95% confidence interval £3673 to £4498) or a strategy combining the two tests (£4058, 95% confidence interval £3702 to £4547). Positron emission tomography-computerised tomography led to more patients with malignant nodules being correctly managed, 0.44 on average (95% confidence interval 0.39 to 0.49), compared with 0.40 (95% confidence interval 0.35 to 0.45); using both tests further increased this (0.47, 95% confidence interval 0.42 to 0.51).

LIMITATIONS

The high prevalence of malignancy in nodules observed in this trial, compared with that observed in nodules identified within screening programmes, limits the generalisation of the current results to nodules identified by screening.

CONCLUSIONS

Findings from this research indicate that positron emission tomography-computerised tomography is more accurate than dynamic contrast-enhanced computerised tomography for the characterisation of solitary pulmonary nodules. A combination of maximum standardised uptake value and peak enhancement had the highest accuracy with a small increase in costs. Findings from this research also indicate that a combined positron emission tomography-dynamic contrast-enhanced computerised tomography approach with a slightly higher willingness to pay to avoid missing small cancers or to avoid a 'watch and wait' policy may be an approach to consider.

FUTURE WORK

Integration of the dynamic contrast-enhanced component into the positron emission tomography-computerised tomography examination and the feasibility of dynamic contrast-enhanced computerised tomography at lung screening for the characterisation of solitary pulmonary nodules should be explored, together with a lower radiation dose protocol.

STUDY REGISTRATION

This study is registered as PROSPERO CRD42018112215 and CRD42019124299, and the trial is registered as ISRCTN30784948 and ClinicalTrials.gov NCT02013063.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 26, No. 17. See the NIHR Journals Library website for further project information.

Evaluation of dual-energy and perfusion CT parameters for diagnosing solitary pulmonary nodules

Background

To evaluate the correlation and accuracy of dual‐energy CT (DECT) (70/Sn150) and low‐dose volume perfusion CT (VPCT) parameters for the diagnosis of solitary pulmonary nodules (SPN).

Methods

A total of 15 patients with benign SPN (mean age 56 ± 7 years) and 34 patients with malignant SPN and clinical indication for surgery (mean age 58 ± 6 years) were enrolled from July 2017 to September 2019 at a single institution. All the patients underwent low‐dose VPCT with a scan volume of 114 mm on the z‐axis and a venous phase enhancement DECT (70/150 Sn) scan just before surgery on the same day. All CT findings were studied in comparison with the pathological results after surgery. Perfusion and dual‐energy CT parameters such as blood flow (BF), blood volume (BV), mean transit time (MTT), flow extraction product (FED), pulmonary nodule enhancement peak (PPnod) and iodine concentration (IC) were evaluated as well as t‐test, chi‐square test, Pearson correlation analysis, and ROC curve analysis to determine the significance of study parameters.

Results

The effective radiation dosage of the VPCT and DECT scans were 4.67 ± 0.26 mSv and 0.32 ± 0.10 mSv, respectively. Significant correlations were found between iodine concentration from DECT and VPCT parameters (r = 0.376–0.533, p < 0.05). The sensitivity and specificity of IC to differentiate the SPN were 86.67% and 72.73%, which was slightly lower than that of BV (94.44%, 73.33%), FED (88.89%, 80.00%) and PPnod (94.44%, 80.00%).

Conclusions

VPCT scans have low radiation dosage achieved by shortening the z‐axis scan range for assessment of SPN. IC from DECT is significantly correlated with VPCT parameters, and VPCT parameters have better diagnostic performance for SPN than DECT parameters.

[Diagnosis and treatment of benign lung tumors]

Benign lung tumors account 2-12% of all lung neoplasms. The classification of lung tumors, adopted by the World Health Organization in 2015, is reported with a detailed indication of all changes based on immunohistochemical and genetic studies. Diagnosis with computed tomography, dynamic and perfusion computed tomography, virtual bronchoscopy and positron emission tomography is described. These methods ensure 94-98% sensitivity for differentiation with malignancies. CT and ultrasound signs of benign tumors are presented. Surgical strategy for newly diagnosed nodes in the lungs is analyzed depending on their dimensions and risk factors. It was shown that comprehensive examination with possible surgical verification of the diagnosis is necessary for nodes over 6 mm and moderate-to-high risk factors. The authors describe argon plasma and laser destruction, bronchoplastic procedures for central benign tumors, thoracoscopy for peripheral neoplasms. One can conclude that high-tech methods of radiological and nuclear diagnosis are valuable to determine benign neoplasms and their dimensions with a high degree of reliability. Endoscopic and thoracoscopic procedures are successfully used for benign tumors.

Differentiating malignant and benign necrotic lung lesions using kVp-switching dual-energy spectral computed tomography

BACKGROUND

Necrotic pulmonary lesions manifest as relatively low-density internally on contrast-enhanced computed tomography (CT). However, using CT to differentiate malignant and benign necrotic pulmonary lesions is challenging, as these lesions have similar peripheral enhancement. With the introduction of dual-energy spectral CT (DESCT), more quantitative parameters can be obtained and the ability to differentiate material compositions has been highly promoted. This study investigated the use of kVp-switching DESCT in differentiating malignant from benign necrotic lung lesions.

METHODS

From October 2016 to February 2019, 40 patients with necrotic lung cancer (NLC) and 31 with necrotic pulmonary mass-like inflammatory lesion (NPMIL) were enrolled and underwent DESCT. The clinical characteristics of patients, CT morphological features, and DESCT quantitative parameters of lesions were compared between the two groups. Binary logistic regression analysis was performed to identify the independent prognostic factors differentiating NPMIL from NLC. Receiver operating characteristic (ROC) curves were used to assess the diagnostic performance of single-parameter and multiparametric analyses.

RESULTS

Significant differences in age, C-reactive protein concentration, the slope of the spectral curve from 40 to 65 keV (K_40-65 keV) of necrosis in non-contrast-enhanced scanning (NCS), arterial phase (AP) and venous phase (VP), effective atomic number of necrosis in NCS, and iodine concentration (IC) of the solid component in VP were observed between groups (all p < 0.05). The aforementioned parameters had area under the ROC curve (AUC) values of 0.747, 0.691, 0.841, 0.641, 0.660, 0.828, and 0.754, respectively, for distinguishing between NLC and NPMIL. Multiparametric analysis showed that age, K_40-65 keV of necrosis in NCS, and IC of the solid component in VP were the most effective factors for differentiating NLC from NPMIL, with an AUC of 0.966 and percentage of correct class of 88.7%.

CONCLUSIONS

DESCT can differentiate malignant from benign necrotic lung lesions with a relatively high accuracy.

Differentiating the lung lesions using Intravoxel incoherent motion diffusion-weighted imaging: a meta-analysis

Background and objectives

The diagnostic performance of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) in the differential diagnosis of pulmonary tumors remained debatable among published studies. This study aimed to pool and summary the relevant results to provide more robust evidence in this issue using a meta-analysis method.

Materials and methods

The researches regarding the differential diagnosis of lung lesions using IVIM-DWI were systemically searched in Pubmed, Embase, Web of science and Wangfang database without time limitation. Review Manager 5.3 was used to calculate the standardized mean difference (SMD) and 95% confidence intervals of apparent diffusion coefficient (ADC), tissue diffusivity (D), pseudo-diffusivity (D*), and perfusion fraction (f). Stata 12.0 was used to pool the sensitivity, specificity, and area under the curve (AUC), as well as publication bias and heterogeneity. Fagan’s nomogram was used to predict the post-test probabilities.

Results

Eleven studies with 481 malignant and 258 benign lung lesions were included. Most include studies showed a low to unclear risk of bias and low concerns regarding applicability. Lung cancer demonstrated a significant lower ADC (SMD = -1.17, P < 0.001), D (SMD = -1.02, P < 0.001) and f values (SMD = -0.43, P = 0.005) than benign lesions, except D* value (SMD = 0.01, P = 0.96). D value demonstrated the best diagnostic performance (sensitivity = 89%, specificity = 71%, AUC = 0.90) and highest post-test probability (57, 57, 43 and 43% for D, ADC, f and D* values) in the differential diagnosis of lung tumors, followed by ADC (sensitivity = 85%, specificity = 72%, AUC = 0.86), f (sensitivity = 71%, specificity = 61%, AUC = 0.71) and D* values (sensitivity = 70%, specificity = 60%, AUC = 0.66).

Conclusion

IVIM-DWI parameters show potentially strong diagnostic capabilities in the differential diagnosis of lung tumors based on the tumor cellularity and perfusion characteristics, and D value demonstrated better diagnostic performance compared to mono-exponential ADC.

Dynamic contrast-enhanced computed tomography for the diagnosis of solitary pulmonary nodules: a systematic review and meta-analysis

INTRODUCTION

A systematic review and meta-analysis were performed to determine the diagnostic performance of dynamic contrast-enhanced computed tomography (DCE-CT) for the differentiation between malignant and benign pulmonary nodules.

METHODS

Ovid MEDLINE and EMBASE were searched for studies published up to October 2018 on the diagnostic accuracy of DCE-CT for the characterisation of pulmonary nodules. For the index test, studies with a minimum of a pre- and post-contrast computed tomography scan were evaluated. Studies with a reference standard of biopsy for malignancy, and biopsy or 2-year follow-up for benign disease were included. Study bias was assessed using QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies). The sensitivities, specificities, and diagnostic odds ratios were determined along with 95% confidence intervals (CIs) using a bivariate random effects model.

RESULTS

Twenty-three studies were included, including 2397 study participants with 2514 nodules of which 55.3% were malignant (1389/2514). The pooled accuracy results were sensitivity 94.8% (95% CI 91.5; 96.9), specificity 75.5% (69.4; 80.6), and diagnostic odds ratio 56.6 (24.2-88.9). QUADAS 2 assessment showed intermediate/high risk of bias in a large proportion of the studies (52-78% across the domains). No difference was present in sensitivity or specificity between subgroups when studies were split based on CT technique, sample size, nodule size, or publication date.

CONCLUSION

DCE-CT has a high diagnostic accuracy for the diagnosis of pulmonary nodules although study quality was indeterminate in a large number of cases.

KEY POINTS

• The pooled accuracy results were sensitivity 95.1% and specificity 73.8% although individual studies showed wide ranges of values. • This is comparable to the results of previous meta-analyses of PET/CT (positron emission tomography/computed tomography) diagnostic accuracy for the diagnosis of solitary pulmonary nodules. • Robust direct comparative accuracy and cost-effectiveness studies are warranted to determine the optimal use of DCE-CT and PET/CT in the diagnosis of SPNs.

Imaging protocols for CT chest: A recommendation

Computed Tomography (CT) is the mainstay of diagnostic imaging evaluation of thoracic disorders. However, there are a number of CT protocols ranging from a simple non-contrast CT at one end of the spectrum, and CT perfusion as a complex protocol available only on high-end scanners. With the growing diversity, there is a pressing need for radiologists, and clinicians to have a basic understanding of the recommended CT examinations for individual indications. This brief review aims to summarise the currently prevalent CT examination protocols, including their recommended indications, as well as technical specifications for performing them.

Long-Term Follow-Up of Ground-Glass Nodules After 5 Years of Stability

INTRODUCTION

Small ground-glass nodules (GGNs) or those with an indeterminate risk on low-dose computed tomography (LDCT) of the chest are recommended at 5-year follow-up, but the rationale for follow-up beyond 5 years is unclear.

METHODS

An observational study was conducted to investigate the natural course of GGNs that had been stable for 5 years by LDCT over 10 years. All eligible GGNs were detected during regular health checkups. Baseline characteristics were compared between GGNs with and without growth. Risk factors for GGN growth were evaluated.

RESULTS

A total of 208 GGNs were detected in 160 participants. GGN growth was identified in 27 (13.0%) GGNs during a follow-up of 136 months on LDCT scans. In approximately 95% of these GGNs, the initial size was less than 6 mm, with 3.2 mm of growth over 8.5 years. Biopsies were performed in 3 of 27 GGNs, revealing adenocarcinoma. In 8 of 27 cases, GGN growth preceded the development of a new solid component. In a multivariate analysis, bubble lucency (p = 0.001), a history of cancer other than lung cancer (p = 0.036), and development of a new solid component (p < 0.001) were significant risk factors for GGN growth.

CONCLUSIONS

GGNs should not be ignored, even when smaller than 6 mm and stable for 5 years, especially when a new solid component appears during follow-up.

Diagnostic Performance of Perfusion Computed Tomography for Differentiating Lung Cancer from Benign Lesions: A Meta-Analysis

Background

Numerous studies have explored diagnosis of pulmonary nodules using perfusion computed tomography (CT); however, findings were not always consistent between studies. Th e present study aimed to summarize evidence on the diagnostic value of perfusion CT for distinguishing between lung cancer and benign lesions.

Material/Methods

We performed a systematic literature search on lung cancer and benign pulmonary lesions performed with perfusion CT. The searches were undertaken in English or Chinese language in Medline, PubMed, Embase, Cochrane Library, Web of Science, and China National Knowledge Infrastructure database from Jan 2010 to Nov 2018. Standardized mean differences (SMDs) and 95% confidence intervals (CIs) of blood volume (BV), blood flow (BF), mean transit time (MTT), and permeability surface (PS) were calculated using Review Manager 5.3. Publication bias, sensitivity, specificity, and the area under the curve (AUC) were calculated using Stata12.0.

Results

Fourteen studies comprising 1032 malignant and 447 benign pulmonary lesions were analyzed. Lung cancer had higher BV, BF, MTT, and PS values than benign lesions. SMDs and 95% CIs of BV, BF, MTT, and PS were 2.29 (1.43, 3.16), 0.50 (0.14, 0.86), 0.55 (0.39, 0.72), and 1.21 (0.87, 1.56), respectively. AUC values of BV and PS were 0.92 (0.90, 0.94) and 0.83 (0.80, 0.86), respectively.

Conclusions

CT perfusion imaging is a valuable technique for the diagnosis of pulmonary nodules. Lung cancer had higher perfusion and permeability than benign lesions. The evidence suggests blood volume is the best surrogate marker for characterizing the blood supply, while permeability surface has a high specificity in quantifying the vascular permeability.

Solitary pulmonary nodule: Comparison of quantitative capability for differentiation and management among dynamic CE-perfusion MRI at 3 T system, dynamic CE-perfusion ADCT and FDG-PET/CT

PURPOSE

To prospectively compare the capability of dynamic first-pass contrast-enhanced (CE) perfusion MR imaging with ultra-short TE and area-detector CT (ADCT), analyzed with the same mathematical methods, and that of FDG-PET/CT for diagnosis and management of solitary pulmonary nodules (SPNs).

METHODS AND MATERIALS

Our institutional review board approved this study and written informed consent was obtained from all subjects. A total 57 consecutive patients with 71 nodules prospectively underwent dynamic CE-perfusion ADCT and MR imaging with ultra-short TE, FDG-PET/CT, as well as microbacterial and/or pathological examinations. The nodules were classified into malignant nodules (n = 45) and benign nodules (n = 26). Pulmonary arterial, systemic arterial and total perfusions were determined by means of dual-input maximum slope models on ADCT and MR imaging and maximum values of standard uptake values (SUV_max) on PET/CT. Receiver operating characteristic (ROC) analysis was performed for each index, and sensitivity, specificity and accuracy were compared by McNemar's test.

RESULTS

Areas under the curve (Azs) of total perfusion on ADCT (Az = 0.89) and MR imaging (Az = 0.88) were significantly larger than those of systemic arterial perfusion and MR imaging (p<0.05). Accuracy of total perfusion on ADCT (87.3% [62/71]) and MR imaging (87.3% [62/71]) was significantly higher than that of systemic arterial perfusion for both methods (77.5% [55/71] p = 0.02) and SUV_max (78.9% [56/71], p = 0.03).

CONCLUSION

Dynamic CE-perfusion MR imaging with ultra-short TE and ADCT and have similar potential capabilities, and are superior to FDG-PET/CT in this setting.

Differentiation of focal organising pneumonia and peripheral adenocarcinoma in solid lung lesions using thin-section CT-based radiomics

AIM

To evaluate the predictive role of radiomics based on computed tomography (CT) in discriminating focal organising pneumonia (FOP) from peripheral lung adenocarcinoma (LA).

MATERIALS AND METHODS

Institutional research board approval was obtained for this retrospective study. One hundred and seventeen patients with FOP and 109 patients with LA who underwent thin-section CT from January 2011 to August 2017 were reviewed systematically and analysed. The clinical and radiological features were established as model A and multi-feature-based radiomics as model B. The diagnostic performance of model A, model B, and model A+B were evaluated and compared via receiver operating characteristic (ROC) curve analysis and logistic regression analysis.

RESULTS

Sex, symptoms, necrosis, and the halo sign were identified as independent predictors of LA. The area under the ROC curve (Az value), accuracy, sensitivity, and specificity of model A were 0.839, 75.7%, 82.6%, and 69.2% respectively. Model B showed significantly higher accuracy than model A (83.6% versus 75.7%, p=0.032). The top four best-performing features, WavEnLH_s-3, WavEnHH_s-3, Teta3, and Volume, performed as independent factors for discriminating LA. Regression analysis indicated that model B had superior model fit than model A with Akaike information criterion (AIC) values of 73.6% versus 59.1%, respectively. Combining model A with model B is useful in achieving better diagnostic performance in discriminating FOP from LA: the Az value, accuracy, sensitivity, and specificity were 0.956, 87.6%, 85.3%, and 89.7% respectively.

CONCLUSIONS

Radiomics based on CT exhibited better diagnostic accuracy and model fit than clinical and radiological features in discriminating FOP from LA. Combination of both achieved better diagnostic performance.

Computer-Aided Diagnosis of Ground-Glass Opacity Nodules Using Open-Source Software for Quantifying Tumor Heterogeneity

OBJECTIVE

The purposes of this study are to develop quantitative imaging biomarkers obtained from high-resolution CTs for classifying ground-glass nodules (GGNs) into atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC); to evaluate the utility of contrast enhancement for differential diagnosis; and to develop and validate a support vector machine (SVM) to predict the GGN type.

MATERIALS AND METHODS

The heterogeneity of 248 GGNs was quantified using custom software. Statistical analysis with a univariate Kruskal-Wallis test was performed to evaluate metrics for significant differences among the four GGN groups. The heterogeneity metrics were used to train a SVM to learn and predict the lesion type.

RESULTS

Fifty of 57 and 51 of 57 heterogeneity metrics showed statistically significant differences among the four GGN groups on unenhanced and contrast-enhanced CT scans, respectively. The SVM predicted lesion type with greater accuracy than did three expert radiologists. The accuracy of classifying the GGNs into the four groups on the basis of the SVM algorithm was 70.9%, whereas the accuracy of the radiologists was 39.6%. The accuracy of SVM in classifying the AIS and MIA nodules was 73.1%, and the accuracy of the radiologists was 35.7%. For indolent versus invasive lesions, the accuracy of the SVM was 88.1%, and the accuracy of the radiologists was 60.8%. We found that contrast enhancement does not significantly improve the differential diagnosis of GGNs.

CONCLUSION

Compared with the GGN classification done by the three radiologists, the SVM trained regarding all the heterogeneity metrics showed significantly higher accuracy in classifying the lesions into the four groups, differentiating between AIS and MIA and between indolent and invasive lesions. Contrast enhancement did not improve the differential diagnosis of GGNs.

Contrast-enhanced CT- and MRI-based perfusion assessment for pulmonary diseases: basics and clinical applications

Assessment of regional pulmonary perfusion as well as nodule and tumor perfusions in various pulmonary diseases are currently performed by means of nuclear medicine studies requiring radioactive macroaggregates, dual-energy computed tomography (CT), and dynamic first-pass contrast-enhanced perfusion CT techniques and unenhanced and dynamic first-pass contrast enhanced perfusion magnetic resonance imaging (MRI), as well as time-resolved three-dimensional or four-dimensional contrast-enhanced magnetic resonance angiography (MRA). Perfusion scintigraphy, single-photon emission tomography (SPECT) and SPECT fused with CT have been established as clinically available scintigraphic methods; however, they are limited by perfusion information with poor spatial resolution and other shortcomings. Although positron emission tomography with 15O water can measure absolute pulmonary perfusion, it requires a cyclotron for generation of a tracer with an extremely short half-life (2 min), and can only be performed for academic purposes. Therefore, clinicians are concentrating their efforts on the application of CT-based and MRI-based quantitative and qualitative perfusion assessment to various pulmonary diseases. This review article covers 1) the basics of dual-energy CT and dynamic first-pass contrast-enhanced perfusion CT techniques, 2) the basics of time-resolved contrast-enhanced MRA and dynamic first-pass contrast-enhanced perfusion MRI, and 3) clinical applications of contrast-enhanced CT- and MRI-based perfusion assessment for patients with pulmonary nodule, lung cancer, and pulmonary vascular diseases. We believe that these new techniques can be useful in routine clinical practice for not only thoracic oncology patients, but also patients with different pulmonary vascular diseases.

Use of diffusion-weighted magnetic resonance imaging to distinguish between lung cancer and focal inflammatory lesions: a comparison of intravoxel incoherent motion derived parameters and apparent diffusion coefficient

Background Using imaging techniques to diagnose malignant and inflammatory lesions in the lung can be challenging. Purpose To compare intravoxel incoherent motion (IVIM) and apparent diffusion coefficient (ADC) magnetic resonance imaging (MRI) analysis in their ability to discriminate lung cancer from focal inflammatory lung lesions. Material and Methods Thirty-eight patients with lung masses were included: 30 lung cancers and eight inflammatory lesions. Patients were imaged with 3.0T MRI diffusion weighted imaging (DWI) using 10 b values (range, 0-1000 s/mm²). Tissue diffusivity ( D), pseudo-diffusion coefficient ( D*), and perfusion fraction ( f) were calculated using segmented biexponential analysis. ADC (total) was calculated with monoexponential fitting of the DWI data. D, D*, f, and ADC were compared between lung cancer and inflammatory lung lesions. Receiver operating characteristic analysis was performed for all DWI parameters. Results The ADC was significantly higher for inflammatory lesions than for lung cancer ([1.21 ± 0.20] × 10^-3 mm²/s vs. [0.97 ± 0.15] × 10^-3 mm²/s; P = 0.004). By IVIM, f was found to be significantly higher in inflammatory lesions than lung cancer ([46.10 ± 12.92] % vs. [29.29 ± 10.89] %; P = 0.005). There was no difference in D and D* between lung cancer and inflammatory lesions ( P = 0.747 and 0.124, respectively). f showed comparable diagnostic performance with ADC in differentiating lung cancer from inflammatory lung lesions, with areas under the curve of 0.833 and 0.826, sensitivity 80.0% and 73.3%, and specificity 75.0% and 87.5%, respectively. Conclusion The IVIM parameter f value provides comparable diagnostic performance with ADC and could be used as a surrogate marker for differentiating lung cancer from inflammatory lesions.

Differential Diagnosis of Solitary Pulmonary Inflammatory Lesions and Peripheral Lung Cancers with Contrast-enhanced Computed Tomography

OBJECTIVES:

To clarify differences between solitary pulmonary inflammatory lesions and peripheral lung cancers with contrast-enhanced computed tomography.

METHODS:

In total, 64 and 132 patients with solitary pulmonary inflammatory masses/nodules and peripheral lung cancers, respectively, were enrolled in this study. Their computed tomographic findings were summarized and compared retrospectively.

RESULTS:

Compared with the peripheral lung cancers, the inflammatory lesions were located closer to the pleura (p<0.0001). The majority of the inflammatory lesions were patchy and oval-shaped (82.8%), whereas most of the tumors were lobulated (82.6%). Almost all the inflammatory cases were unclear (93.8%), whereas most of the tumors had spiculated margins (72.7%). Computed tomography values were significantly higher for the inflammatory lesions than for the cancers (p<0.0001). More than half of the inflammatory lesions had defined necrosis (59.3%). Furthermore, 49.2% of the cancers enhanced inhomogeneously, but only 24.6% had ill-defined necrosis or cavities. The peripheral zones of 98.4% of the inflammatory lesions and 72.7% of the tumors were unclear, with peripheral scattered patches (92.2%) and beam-shaped opacity (66.7%) being the most common findings, respectively. Adjacent pleural thickening was more frequent for the inflammatory lesions than the cancers (95.3% vs. 21.1%, p<0.0001), whereas pleural indentation was found in 67.4% of the subjects with cancer. In addition, hilar (p=0.034) and mediastinal (p=0.003) lymphadenopathy were more commonly detected in the cancers than in the inflammatory cases.

CONCLUSIONS:

Contrast-enhanced computed tomography findings for pulmonary inflammatory lesions and peripheral lung cancers were significantly different in many aspects. Developing a comprehensive understanding of these differences is helpful for directing their management.

Quantitative Computed Tomography Imaging Biomarkers in the Diagnosis and Management of Lung Cancer

Tumor diameter has traditionally been used as a standard metric in terms of diagnosis and prognosis prediction of lung cancer. However, recent advances in imaging techniques and data analyses have enabled novel quantitative imaging biomarkers that can characterize disease status more comprehensively and/or predict tumor behavior more precisely. The most widely used imaging modality for lung tumor assessment is computed tomography. Therefore, we focused on computed tomography imaging biomarkers such as tumor volume and mass, ground-glass opacities, perfusion parameters, as well as texture features in this review. Herein, we first appraised the conventional 1- or 2-dimensional measurement with brief discussion on their limits and then introduced the potential imaging biomarkers with emphasis on the current understanding of their clinical usefulness with respect to the malignancy differentiation, treatment response monitoring, and patient outcome prediction.

First pass dual input volume CT-perfusion of lung lesions: The influence of the CT- value range settings on the perfusion values of benign and malignant entities

OBJECTIVE

To assess the influence of the lower threshold for segmentation of the volume of interest on the perfusion values in first-pass dual input volume CT-perfusion of lung lesions.

MATERIALS AND METHODS

Dual input maximum slope volume CT-perfusion was performed in 48 patients (mean age±standard deviation [SD], 68±10years; range, 46-87 years) who underwent subsequent CT-guided biopsy to evaluate a lung lesion. Using commercial perfusion software, a lower and upper threshold was set for determination of the CT-value range, which again determined the volume of interest for perfusion calculation. The pulmonary arterial flow (PAF), bronchial arterial flow (BAF), and perfusion index (PI; PAF/(PAF+BAF)) were calculated at following pre contrast CT value range settings: -80 to 150HU (setting 1), -200 to 150HU (setting 2), -300 to 150HU (setting 3), and -500 to 150HU (setting 4). Perfusion parameters were compared between benign (n, 15) and malignant (n, 33) lesions for each setting. Intraobserver- and interobserver reliability were calculated for setting 4.

RESULTS

Median PAF was significantly higher in malignant lesions than in benign lesions for all settings (53-96 versus 29-62mL/min/100mL, P<0.05). There was no significant difference in BAF between malignant and benign lesions. Median PAF of all lesions was significantly influenced by the CT value range setting (P<0.05), whereas the values increased from setting 1 to 4. Intraobserver analysis as well as interobserver analysis of PAF at setting 4 showed excellent reliability (Cronbach's alpha 0.98 and 0.95, respectively, P<0.01).

CONCLUSION

PAF derived from first-pass dual-input maximum slope volume CT perfusion is statistically significantly higher in malignant than in benign lesion, whereas the measurements are influenced by the lower threshold of the CT value range setting. This has to be considered when using cutoff values provided in the literature for differentiation between benign and malignant lung lesions.

Assessment of bronchial and pulmonary blood supply in non-small cell lung cancer subtypes using computed tomography perfusion

OBJECTIVES

The aim of this study was to investigate the dual blood supply of non-small cell lung cancer (NSCLC) and its association with tumor subtype, size, and stage, using computed tomography perfusion (CTP).

MATERIALS AND METHODS

A total of 54 patients (median age, 65 years; range, 42-79 years; 15 women, 39 men) with suspected lung cancer underwent a CTP scan of the lung tumor. Pulmonary and bronchial vasculature regions of interest were used to calculate independently CTP parameters (blood flow [BF], blood volume [BV], and mean transit time [MTT]) of the tumor tissue. The mean and maximum pulmonary and bronchial perfusion indexes (PImean and PImax) were calculated. The tumoral volume and the largest tumoral diameter were assessed. Differences in CTP parameters and indexes among NSCLC subtypes, tumor stages and tumor dimensions were analyzed using non-parametric tests.

RESULTS

According to biopsy, 37 patients had NSCLC (22 adenocarcinomas [ACs], 8 squamous cell carcinomas [SCCs], 7 large-cell carcinomas [LCC]). The mean bronchial BF/pulmonary BF, bronchial BV/pulmonary BV, and bronchial MTT/pulmonary MTT was 41.2 ± 30.0/36.9 ± 24.2 mL/100 mL/min, 11.4 ± 9.7/10.4 ± 9.4 mL/100 mL, and 11.4 ± 4.3/14.9 ± 4.4 seconds, respectively. In general, higher bronchial BF than pulmonary BF was observed in NSCLC (P = 0.014). Using a tumoral volume cutoff of 3.5 cm, a significant difference in pulmonary PImax was found (P = 0.028). There was a significantly higher mean pulmonary BF in LCCs and SCCs compared with ACs (P = 0.018 and P = 0.044, respectively), whereas the mean bronchial BF was only significantly higher in LCCs compared with ACs (P = 0.024). Correspondingly, the PImax was significantly higher in LCCs and SCCs than in ACs (P = 0.001 for both). Differences between bronchial and pulmonary PImean and PImax among T stages and Union Internationale Contre le Cancer stages were not statistically significant (P values ranging from 0.691 to 0.753).

CONCLUSIONS

The known dual blood supply of NSCLC, which depends on tumor size and histological subtype, is reflected in CTP parameters, with parameters depending both on tumor size and histological subtype. This has to be accounted for when analyzing NSCLC with CTP.

Functional imaging in lung cancer

Lung cancer represents an increasingly frequent cancer diagnosis worldwide. An increasing awareness on smoking cessation as an important mean to reduce lung cancer incidence and mortality, an increasing number of therapy options and a steady focus on early diagnosis and adequate staging have resulted in a modestly improved survival. For early diagnosis and precise staging, imaging, especially positron emission tomography combined with CT (PET/CT), plays an important role. Other functional imaging modalities such as dynamic contrast-enhanced CT (DCE-CT) and diffusion-weighted MR imaging (DW-MRI) have demonstrated promising results within this field. The purpose of this review is to provide the reader with a brief and balanced introduction to these three functional imaging modalities and their current or potential application in the care of patients with lung cancer.

Dynamic contrast-enhanced CT in suspected lung cancer: quantitative results

OBJECTIVES

To examine whether dynamic contrast-enhanced CT (DCE-CT) could be used to characterise and safely distinguish between malignant and benign lung tumours in patients with suspected lung cancer.

METHODS

Using a quantitative approach to DCE-CT, two separate sets of regions of interest (ROIs) in tissues were placed in each tumour: large ROIs over the entire tumour and small ROIs over the maximally perfused parts of the tumour. Using mathematical modelling techniques and dedicated perfusion software, this yielded a plethora of results.

RESULTS

First, because of their non-normal distribution, DCE-CT measurements must be analysed using log scale data transformation. Second, there were highly significant differences between large ROI and small ROI measurements (p<0.001). Thus, the ROI method used in a given study should always be specified in advance. Third, neither quantitative parameters (blood flow and blood volume) nor semi-quantitative parameters (peak enhancement) could be used to distinguish between malignant and benign tumours. This was irrespective of the method of quantification used for large ROIs (0.13<p<0.76) and small ROIs (0.084<p<0.31). Fourth, although there were no indications of systematic reproducibility bias, the 95% limits of agreement were so broad that the risk of disagreement between the measurements could affect the clinical use of the measurements. This lack of reproducibility should be addressed. CONCLUSION AND ADVANCES IN KNOWLEDGE: A quantitative approach to DCE-CT is not a clinically usable method for characterising lung tumours.

Does volume perfusion computed tomography enable differentiation of metastatic and non-metastatic mediastinal lymph nodes in lung cancer patients? A feasibility study

OBJECTIVES

To compare the perfusion characteristics of mediastinal lymph node metastases with those of non-metastatic nodes in patients with newly diagnosed lung cancer using volume perfusion computed tomography (VPCT).

MATERIALS AND METHODS

Between January 2010 and October 2011, 101 patients with histologically confirmed, untreated lung cancer received a 40-s VPCT of the tumor bulk; 32/101 patients had evident hilar/mediastinal metastatic disease and 17/101 patients had proven non-metastasized lymph nodes within the VPCT scan range. Validation or exclusion of metastatic node involvement was proven by mediastinoscopy, biopsy, positron emission tomography imaging and/or unequivocal volume dynamics on follow-up computed tomography. A total of 45 metastases and 23 non-metastatic lymph nodes were found within the scan range and subsequently evaluated. Blood flow (BF), blood volume (BV) and K(trans) were determined. Tumor volume was recorded as whole tumor volume.

RESULTS

In a comparison between metastatic and non-metastatic lymph nodes, we controlled for age, lymph node volume, lung tumor volume, lung tumor location, and histologic type effects and found no significant differences with respect to BF, BV, K(trans) or heterogeneity in nodal perfusion (P > 0.05, respectively), even after adjusting lymph node perfusion values to the perfusion parameters of the primary tumor (P > 0.05, respectively). Metastatic lymph node volume had a significant increasing effect on perfusion heterogeneity (P < 0.05, respectively) and BV in the primary was a highly significant factor for BV in metastatic disease (P < 0.001).

CONCLUSION

Perfusion characteristics of mediastinal metastatic and non-metastatic lymph nodes in untreated lung cancer show considerable overlap, so that a reliable differentiation via VPCT is not possible.

Evaluation of individuals with pulmonary nodules: when is it lung cancer? Diagnosis and management of lung cancer, 3rd ed: American College of Chest Physicians evidence-based clinical practice guidelines

OBJECTIVES

The objective of this article is to update previous evidence-based recommendations for evaluation and management of individuals with solid pulmonary nodules and to generate new recommendations for those with nonsolid nodules.

METHODS

We updated prior literature reviews, synthesized evidence, and formulated recommendations by using the methods described in the "Methodology for Development of Guidelines for Lung Cancer" in the American College of Chest Physicians Lung Cancer Guidelines, 3rd ed.

RESULTS

We formulated recommendations for evaluating solid pulmonary nodules that measure > 8 mm in diameter, solid nodules that measure ≤ 8 mm in diameter, and subsolid nodules. The recommendations stress the value of assessing the probability of malignancy, the utility of imaging tests, the need to weigh the benefits and harms of different management strategies (nonsurgical biopsy, surgical resection, and surveillance with chest CT imaging), and the importance of eliciting patient preferences.

CONCLUSIONS

Individuals with pulmonary nodules should be evaluated and managed by estimating the probability of malignancy, performing imaging tests to better characterize the lesions, evaluating the risks associated with various management alternatives, and eliciting their preferences for management.

Advances and perspectives in lung cancer imaging using multidetector row computed tomography

The introduction of multidetector row computed tomography (CT) into clinical practice has revolutionized many aspects of the clinical work-up. Lung cancer imaging has benefited from various breakthroughs in computing technology, with advances in the field of lung cancer detection, tissue characterization, lung cancer staging and response to therapy. Our paper discusses the problems of radiation, image visualization and CT examination comparison. It also reviews the most significant advances in lung cancer imaging and highlights the emerging clinical applications that use state of the art CT technology in the field of lung cancer diagnosis and follow-up.

Circulating endothelial cells and tumor blood volume as predictors in lung cancer

The current criteria for evaluating antiangiogenic efficacy is insufficient as tumor shrinkage occurs after blood perfusion decreases. Tumor blood volume (BV) in computed tomography perfusion imaging and circulating endothelial cells (CEC) might predict the status of angiogenesis. The present study aimed to validate their representation as feasible predictors in non-small-cell lung carcinoma (NSCLC). A total of 74 patients was categorized randomly into two arms undergoing regimens of vinorelbine and cisplatin (Navelbine and platinum [NP]) with rh-endostatin or single NP. The response rate, perfusion imaging indexes and activated CEC (aCEC) during treatment were recorded. Progression-free survival (PFS) was determined through follow up. Correlations among the above indicators, response and PFS were analyzed: aCEC increased significantly in cases of progressive disease after single NP chemotherapy (P = 0.024). Tumor BV decreased significantly in cases with a clinical benefit in the combined arm (P = 0.026), whereas inverse correlations existed between ∆aCEC (post-therapeutic value minus the pre-therapeutic value) and PFS (P = 0.005) and between ∆BV and PFS (P = 0.044); a positive correlation existed between ∆aCEC and ∆BV. Therefore, both aCEC and tumor BV can serve as predictors, and detection of both indicators can help evaluate the chemo-antiangiogenic efficacy in NSCLC more accurately.

Differentiation between malignant and benign solitary pulmonary nodules: use of volume first-pass perfusion and combined with routine computed tomography

PURPOSE

To evaluate the capability of first-pass volume perfusion computed tomography (PCT) for differentiation of solitary pulmonary nodules (SPNs) and to compare that of combination of PCT and routine CT with CT alone for the differentiation.

MATERIALS AND METHODS

Our institutional review board approved this study and informed consent was obtained. With nine excluded, 65 consecutive patients having a SPN with histopathologic proof or follow-up underwent a 30s PCT using the deconvolution model were evaluated. Kruskal-Wallis tests and receiver operating characteristics (ROC) analysis were underwent. Four radiologists assessed nodules independently and retrospectively. Diagnostic capability was compared for CT alone and PCT plus CT. ROC analysis, McNemar test, and weighted kappa statistics were performed.

RESULTS

Significant differences were found in parameters between malignant and benign nodules (p<0.0001 for blood flow, blood volume, and permeability surface area product), SPNs were more likely to be malignant by using threshold values of more than 55 ml/100 g/min, 2.5 ml/100 g, and 10 ml/100 g/min, respectively. PCT plus CT was significantly better in overall sensitivity (93%, p=0.004) and accuracy (94%, p=0.003) compared to CT alone, not specificity (96%). Area under the curve for ROC analyses of PCT plus CT was significantly larger than that of CT alone (p=0.018). Mean weighted kappa for PCT plus CT was 0.715, that for CT alone was 0.447.

CONCLUSION

Volume first-pass PCT can distinguish SPNs. Using PCT plus routine CT may be more sensitive and accurate for differentiating malignant from benign nodules than CT alone and allows more confidence and constancy.

Effect of scan time on perfusion and flow extraction product (K-trans) measurements in lung cancer using low-dose volume perfusion CT (VPCT)

RATIONALE AND OBJECTIVES

To assess the effect of measurement time on blood flow (BF), blood volume (BV), and k-trans-values (flow extraction product) in patients undergoing volume perfusion computed tomography (VPCT) for lung cancer.

MATERIALS AND METHODS

This prospective study was approved by our local Research Ethics Committee and informed consent was obtained in all patients. Between December 2009 and December 2010, 75 VPCT scans were obtained in 54 consecutive patients (15 women, 39 men) with histologically confirmed lung cancer. A 64-second VPCT of the tumor (80 kV, 60 mAs) using 128 × 0.6-mm collimation, 6.9-cm z-axis coverage and a total of 26 volume measurements, was performed. BF, BV, and K(trans) were determined. Data evaluation was performed for different measurement times (64 seconds, 45 seconds, 39 seconds, and 36 seconds) by removing the last two, four, and five scans and repeating the analysis. A one-way repeated-measures analysis of variance was used to test for effects of measurement time on BF, BV, and k-trans and unpaired/paired Student t-tests were applied for comparisons within/between groups, respectively.

RESULTS

No effect of measurement time on BF values was noted (P > .05), whereas a significant decrease of BV values (at 39 seconds: 71% ± 2% of 64-second values) and a significant increase of k-trans-values (at 39 seconds: 146% ± 8% of 64-second values) were observed with progressively shortened measurement time (P < .05, respectively). Additionally, with reduced measurement time, the increase in k-trans-values was significantly more pronounced in those patient groups with higher BV (at 39 seconds: 171% ± 15% versus 120% ± 3% of 64-second measurements), and those with lower k-trans (at 39 seconds: 167% ± 16% versus 126% ± 4% of 64-second measurements) (P < .05, respectively).

CONCLUSION

Whereas estimation of BF in lung cancer was independent from VPCT measurement time within the chosen ranges, approximation of both BV and k-trans was affected by measurement duration. A fixed measurement time of 40 seconds is recommended.