Preliminary comparison of diffusion-weighted MRI and PET/CT in predicting histological type and malignancy of lung cancer

A comparison study of monoexponential and fractional order calculus diffusion models and 18F-FDG PET in differentiating benign and malignant solitary pulmonary lesions and their pathological types

Objective

To evaluate the application value of monoexponential, fractional order calculus (FROC) diffusion models and PET imaging to distinguish between benign and malignant solitary pulmonary lesions (SPLs) and malignant SPLs with different pathological types and explore the correlation between each parameter and Ki67 expression.

Methods

A total of 112 patients were enrolled in this study. Prior to treatment, all patients underwent a dedicated thoracic ¹⁸F-FDG PET/MR examination. Five parameters [including apparent diffusion coefficient (ADC) derived from the monoexponential model; diffusion coefficient (D), a microstructural quantity (μ), and fractional order parameter (β) derived from the FROC model and maximum standardized uptake value (SUVmax) derived from PET] were compared between benign and malignant SPLs and different pathological types of malignant SPLs. Independent sample t test, Mann-Whitney U test, DeLong test and receiver operating characteristic (ROC) curve analysis were used for statistical evaluation. Pearson correlation analysis was used to calculate the correlations between Ki-67 and ADC, D, μ, β, and SUVmax.

Results

The ADC and D values were significantly higher and the μ and SUVmax values were significantly lower in the benign group [1.57 (1.37, 2.05) μm²/ms, 1.59 (1.52, 1.72) μm²/ms, 5.06 (3.76, 5.66) μm, 5.15 ± 2.60] than in the malignant group [1.32 (1.03, 1.51) μm²/ms, 1.43 (1.29, 1.52) μm²/ms, 7.06 (5.87, 9.45) μm, 9.85 ± 4.95]. The ADC, D and β values were significantly lower and the μ and SUVmax values were significantly higher in the squamous cell carcinoma (SCC) group [1.29 (0.66, 1.42) μm²/ms, 1.32 (1.02, 1.42) μm²/ms, 0.63 ± 0.10, 9.40 (7.76, 15.38) μm, 11.70 ± 5.98] than in the adenocarcinoma (AC) group [1.40 (1.28, 1.67) μm²/ms, 1.52 (1.44, 1.64) μm²/ms, 0.70 ± 0.10, 5.99 (4.54, 6.87) μm, 8.76 ± 4.18]. ROC curve analysis showed that for a single parameter, μ exhibited the best AUC value in discriminating between benign and malignant SPLs groups and AC and SCC groups (AUC = 0.824 and 0.911, respectively). Importantly, the combination of monoexponential, FROC models and PET imaging can further improve diagnostic performance (AUC = 0.872 and 0.922, respectively). The Pearson correlation analysis showed that Ki67 was positively correlated with μ value and negatively correlated with ADC and D values (r = 0.402, -0.346, -0.450, respectively).

Conclusion

The parameters D and μ derived from the FROC model were superior to ADC and SUVmax in distinguishing benign from malignant SPLs and adenocarcinoma from squamous cell carcinoma, in addition, the combination of multiple parameters can further improve diagnostic performance. The non-Gaussian FROC diffusion model is expected to become a noninvasive quantitative imaging technique for identifying SPLs.

Influencing Factors and Prognostic Value of 18F-FDG PET/CT Metabolic and Volumetric Parameters in Non-Small Cell Lung Cancer

Objective

This study aims to explore factors influencing metabolic and volumetric parameters of [¹⁸F]fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) imaging in non-small cell lung cancer (NSCLC) and the predictive value for prognosis of NSCLC.

Methods

Retrospective analysis was performed on 133 NSCLC patients who received ¹⁸F-FDG PET/CT imaging. After ¹⁸F-FDG injection at 3.7 MBq/kg, 1 h early imaging and 2 h delayed imaging were performed. The metabolic and volumetric parameters such as SUVmax, SUVpeak, SULmax, SULpeak, MTV and TLG were measured. The tumor markers including CFYRA21-1, NSE, SCC-ag and the immunohistochemical biomarkers including Ki-67, P53 and CK-7 were examined. All patients were followed up for 24 months, and the 1-year and 2-year overall survival rate (OS) were recorded.

Results

There were significant differences in metabolic and volumetric parameters (SUVmax, SUVpeak, SULmax, SULpeak and TLG) between adenocarcinoma and squamous cell carcinoma of NSCLC. SUVmax, SUVpeak, SULmax, SULpeak, MTV and TLG were correlated with tumor marker NSE and TNM stage. MTV and TLG were related to CYFRA21-1, and only MTV was associated with SCC-ag. SUVpeak and SULmax were related to P53. In addition, early SULpeak and delayed MTV were significant prognostic factors of 1-year OS, while early SUVpeak, delayed TLG and delayed MTV were predictive factors of 2-year OS in NSCLC.

Conclusion

The metabolic and volumetric parameters of ¹⁸F-FDG PET/CT were related to a variety of factors such as NSE, CFYRA21-1, SCC-ag, P53 and TNM stage, and have a predictive value in prognosis of NSCLC.

Descriptive profile of risk factors for cardiovascular diseases using WHO STEP wise approach in Madhya Pradesh

BACKGROUND

Periodic information on risk factor distribution is critical for public health response for reduction in non-communicable disease (NCDs). For this purpose, the WHO has developed STEPs wise approach. State representative population-based STEPS survey was last conducted in 2007-08 in seven states of In India. Since then no such work has been reported from low ETL states. This survey was carried out to assess the prevalence of risk factors associated with NCDs and the prevalence of NCDs in the low ETL state of Madhya Pradesh using the WHO STEPs approach.

METHODS

A total of 5680 persons aged 18-69 years were selected from the state of Madhya Pradesh using multi-stage cluster random sampling. Using the WHO STEPs approach, details were collected on demographics, STEP 1 variables (tobacco consumption, alcohol consumption, physical activity, diet), STEP 2 variables (weight, height, waist circumference, blood pressure) and STEP 3 variables (fasting blood glucose, blood cholesterol).

RESULTS

We found that 9.4% individuals smoked tobacco, 15.3% were overweight/obese, 22.3% had hypertension, and 6.8% have diabetes mellitus. As compared to women, men were less likely to be overweight or obese, but more likely to smoke tobacco, and have diabetes mellitus. Hypertension was also more common in men. Overall, about a fourth of all adults had three or more risk factors for cardiovascular disease.

CONCLUSION

The survey shows that a large section of the population from Madhya Pradesh is either suffering from NCDs or have risk factors which predispose them to acquire NCDs. This state representative survey provides benchmarking information for behavioural and biological risk factor distribution for recently scaled up National Programme for the Prevention and Control of Cancer, Diabetes, Cardiovascular Diseases, and Stroke (NPCDCS).

Elaboration of a multimodal MRI-based radiomics signature for the preoperative prediction of the histological subtype in patients with non-small-cell lung cancer

BACKGROUND

Non-invasive discrimination between lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD) subtypes of non-small-cell lung cancer (NSCLC) could be very beneficial to the patients unfit for the invasive diagnostic procedures. The aim of this study was to investigate the feasibility of utilizing the multimodal magnetic resonance imaging (MRI) radiomics and clinical features in classifying NSCLC. This retrospective study involved 148 eligible patients with postoperative pathologically confirmed NSCLC. The study was conducted in three steps: (1) feature extraction was performed using the online freely available package with the multimodal MRI data; (2) feature selection was performed using the Student's t test and support vector machine (SVM)-based recursive feature elimination method with the training cohort (n = 100), and the performance of these selected features was evaluated using both the training and the validation cohorts (n = 48) with a non-linear SVM classifier; (3) a Radscore model was then generated using logistic regression algorithm; (4) Integrating the Radscore with the semantic clinical features, a radiomics-clinical nomogram was developed, and its overall performance was evaluated with both cohorts.

RESULTS

Thirteen optimal features achieved favorable discrimination performance with both cohorts, with area under the curve (AUC) of 0.819 and 0.824, respectively. The radiomics-clinical nomogram integrating the Radscore with the independent clinical predictors exhibited more favorable discriminative power, with AUC improved to 0.901 and 0.872 in both cohorts, respectively. The Hosmer-Lemeshow test and decision curve analysis results furtherly showed good predictive precision and clinical usefulness of the nomogram.

CONCLUSION

Non-invasive histological subtype stratification of NSCLC can be done favorably using multimodal MRI radiomics features. Integrating the radiomics features with the clinical features could further improve the performance of the histological subtype stratification in patients with NSCLC.

Standardized Uptake Values Derived from 18F-FDG PET May Predict Lung Cancer Microvessel Density and Expression of KI 67, VEGF, and HIF-1α but Not Expression of Cyclin D1, PCNA, EGFR, PD L1, and p53

Background

Our purpose was to provide data regarding relationships between ¹⁸F-FDG PET and histopathological parameters in lung cancer.

Methods

MEDLINE library was screened for associations between PET parameters and histopathological features in lung cancer up to December 2017. Only papers containing correlation coefficients between PET parameters and histopathological findings were acquired for the analysis. Overall, 40 publications were identified.

Results

Associations between SUV and KI 67 were reported in 23 studies (1362 patients). The pooled correlation coefficient was 0.44. In 2 studies (180 patients), relationships between SUV and expression of cyclin D1 were analyzed (pooled correlation coefficient = 0.05). Correlation between SUV and HIF-1α was investigated in 3 studies (288 patients), and the pooled correlation coefficient was 0.42. In 5 studies (310 patients), associations between SUV and MVD were investigated (pooled correlation coefficient = 0.54). In 6 studies (305 patients), relationships between SUV and p53 were analyzed (pooled correlation coefficient = 0.30). In 6 studies (415 patients), associations between SUV and VEGF expression were investigated (pooled correlation coefficient = 0.44). In 5 studies (202 patients), associations between SUV and PCNA were investigated (pooled correlation coefficient = 0.32). In 3 studies (718 patients), associations between SUV and expression of PD L1 were analyzed (pooled correlation coefficient = 0.36). Finally, in 5 studies (409 patients), associations between SUV and EGFR were investigated (pooled correlation coefficient = 0.38).

Conclusion

SUV may predict microvessel density and expression of VEGF, KI 67, and HIF-1α in lung cancer.

Parameters of simultaneous 18F-FDG-PET/MRI predict tumor stage and several histopathological features in uterine cervical cancer

The purpose of this study was to analyze associations between apparent diffusion coefficient (ADC) and standardized uptake values (SUV) values and different histopathological parameters in uterine cervical cancer. 21 patients with primary uterine cervical cancer were involved into the study. All patients underwent a whole body simultaneous¹⁸F-FDG PET/MRI. Mean and maximum SUV were noted (SUV_mean and SUV_max). In all tumors minimal, mean, and maximal ADC values (ADC_min, ADC_mean, and ADC_max) were estimated. Combined parameters were calculated: SUV_max/SUV_mean, ADC_min/ ADC_mean, SUV_max/ADC_min and SUV_max/ADC_mean. In all cases the diagnosis was confirmed histopathologically by tumor biopsy. Histological slices were stained by hematoxilin and eosin, MIB 1 monoclonal antibody, and p16. All histopathological images were digitalized and analyzed by using a ImageJ software 1.48v. The following parameters were estimated: cell count, proliferation index KI 67, total and average nucleic areas, epithelial and stromal areas. Spearman's correlation coefficient was used to analyze associations between ADC and SUV values and histological parameters. P values ≤ 0.05 were considered as statistically significant. ADC_min and ADC_min/ ADC_mean were statistically significant lower in N positive tumors. KI 67 correlated statistically significant with SUV_max (r = 0.59, p = 0.005), SUV_mean (0.45, p = 0.04), ADC_min (r = −0.48, p = 0.03), SUV_max/ADC_min (r = 0.71, p = 0.001), SUV_max/ADC_mean (0.75, p = 0.001). SUV_max correlated well with epithelial area (r = 0.71, p = 0.001) and stromal areas (r = −0.71, p = 0.001). SUV values, ADC_min, SUV_max/ADC_min and SUV_max/ADC_mean correlated statistically significant with KI 67 and can be used to estimate the proliferation potential of tumors. SUV values correlated strong with epithelial area of tumor reflected metabolic active areas.

Correlations of 18F-FDG and 18F-FLT uptake on PET with Ki-67 expression in patients with lung cancer: a meta-analysis

Background Positron emission tomography (PET) imaging using the radiotracers 18F-fluorodeoxyglucose (FDG) or 18F-fluorothymidine (FLT) has been proposed as imaging biomarkers of cell proliferation. Purpose To explore the correlations of FDG and FLT uptake with the Ki-67 labeling index in patients with lung cancer. Material and Methods Major databases were systematically searched for all relevant literature published in English. The correlation coefficient (rho) and its 95% confidence interval (CI) of individual studies were meta-analyzed using a random-effects model. The sources of heterogeneity were explored by subgroup analyses. Results Twenty-seven articles involving 1213 patients were included in this meta-analysis, comprising 22 studies for FDG uptake/Ki-67 expression correlation and eight for FLT uptake/Ki-67 expression correlation. The pooled rho values for 18F-FDG/Ki-67 correlation and 18F-FLT/Ki-67 correlation were 0.45 (95% CI, 0.41-0.50) and 0.65 (95% CI, 0.56-0.73), respectively, which indicated a moderate correlation for the former and a significant one for the latter. Although the subgroup analyses based on study design, scanner, sample method, and Ki-67 labeling method did not significantly explain the heterogeneity, these factors were potential sources of heterogeneity. In lung cancer, the pooled SUVmax of FDG uptake was significantly higher than that of FLT uptake (7.59 versus 3.86, P < 0.05). In addition, compared to FDG, FLT showed higher specificity yet lower sensitivity for the diagnosis of pulmonary lesions. Conclusion Both 18F-FDG and 18F-FLT correlate significantly with the Ki-67 labeling index in pulmonary lesions, and the latter, with a stronger correlation, may be more reliable for assessing tumor cell proliferation in lung cancer.

Combining PET/CT with serum tumor markers to improve the evaluation of histological type of suspicious lung cancers

OBJECTIVE

Histological type is important for determining the management of patients with suspicious lung cancers. In this study, PET/CT combined with serum tumor markers were used to evaluate the histological type of lung lesions.

MATERIALS AND METHODS

Patients with suspicious lung cancers underwent 18F-FDG PET/CT and serum tumor markers detection. SUVmax of the tumor and serum levels of tumor markers were acquired. Differences in SUVmax and serum levels of tumor markers among different histological types of lung cancers and between EGFR mutation statues of adenocarcinoma were compared. The diagnostic efficiencies of SUVmax alone, each serum tumor marker alone, combined tumor markers and the combination of both methods were further assessed and compared.

RESULTS

SCC had the highest level of SUVmax, followed by SCLC and adenocarcinoma, and benign lesions had a lowest level. CYFRA21-1 and SCC-Ag were significantly higher in SCC, NSE was significantly higher in SCLC (P<0.001), and CEA was higher in adenocarcinoma (P = 0.343). The diagnostic efficiencies in evaluating histological types of suspicious lung cancers were insufficient when using each serum tumor marker or SUVmax alone. When combined, the AUC, sensitivity and specificity increased significantly (P<0.05 for all). Additionally, to adenocarcinoma, no significant difference was found between EGFR mutation statuses in SUVmax or serum tumor markers (P>0.05 for all).

CONCLUSIONS

SUVmax and serum tumor markers show values in evaluating the histological types of suspicious lung cancers. When properly combined, the diagnostic efficiency can increase significantly.

Associations between apparent diffusion coefficient (ADC) and KI 67 in different tumors: a meta-analysis. Part 1: ADCmean

Diffusion weighted imaging (DWI) is a magnetic resonance imaging (MRI) technique based on measure of water diffusion in tissues. This diffusion can be quantified by apparent diffusion coefficient (ADC). Some reports indicated that ADC can reflect tumor proliferation potential. The purpose of this meta-analysis was to provide evident data regarding associations between ADC and KI 67 in different tumors. Studies investigating the relationship between ADC and KI 67 in different tumors were identified. MEDLINE library was screened for associations between ADC and KI 67 in different tumors up to April 2017. Overall, 42 studies with 2026 patients were identified. The following data were extracted from the literature: authors, year of publication, number of patients, tumor type, and correlation coefficients. Associations between ADC and KI 67 were analyzed by Spearman's correlation coefficient. The reported Pearson correlation coefficients in some studies were converted into Spearman correlation coefficients. The pooled correlation coefficient between ADC_mean and KI 67 for all included tumors was ρ = -0.44. Furthermore, correlation coefficient for every tumor entity was calculated. The calculated correlation coefficients were as follows: ovarian cancer: ρ = -0.62, urothelial carcinomas: ρ = -0.56, cerebral lymphoma: ρ = -0.55, neuroendocrine tumors: ρ = -0.52, glioma: ρ = -0.51, lung cancer: ρ = -0.50, prostatic cancer: ρ = -0.43, rectal cancer: ρ = -0.42, pituitary adenoma:ρ = -0.44, meningioma, ρ = -0.43, hepatocellular carcinoma: ρ = -0.37, breast cancer: ρ = -0.22.

Meta-Analysis of the Correlation between Apparent Diffusion Coefficient and Standardized Uptake Value in Malignant Disease

The objective of this meta-analysis is to explore the correlation between the apparent diffusion coefficient (ADC) on diffusion-weighted MR and the standard uptake value (SUV) of ¹⁸F-FDG on PET/CT in patients with cancer. Databases such as PubMed (MEDLINE included), EMBASE, and Cochrane Database of Systematic Review were searched for relevant original articles that explored the correlation between SUV and ADC in English. After applying Fisher's r-to-z transformation, correlation coefficient (r) values were extracted from each study and 95% confidence intervals (CIs) were calculated. Sensitivity and subgroup analyses based on tumor type were performed to investigate the potential heterogeneity. Forty-nine studies were eligible for the meta-analysis, comprising 1927 patients. Pooled r for all studies was −0.35 (95% CI: −0.42–0.28) and exhibited a notable heterogeneity (I² = 78.4%; P < 0.01). In terms of the cancer type subgroup analysis, combined correlation coefficients of ADC/SUV range from −0.12 (lymphoma, n = 5) to −0.59 (pancreatic cancer, n = 2). We concluded that there is an average negative correlation between ADC and SUV in patients with cancer. Higher correlations were found in the brain tumor, cervix carcinoma, and pancreas cancer. However, a larger, prospective study is warranted to validate these findings in different cancer types.

Non-small cell lung cancer: Whole-lesion histogram analysis of the apparent diffusion coefficient for assessment of tumor grade, lymphovascular invasion and pleural invasion

PURPOSE

Investigating the diagnostic accuracy of histogram analyses of apparent diffusion coefficient (ADC) values for determining non-small cell lung cancer (NSCLC) tumor grades, lymphovascular invasion, and pleural invasion.

MATERIALS AND METHODS

We studied 60 surgically diagnosed NSCLC patients. Diffusion-weighted imaging (DWI) was performed in the axial plane using a navigator-triggered single-shot, echo-planar imaging sequence with prospective acquisition correction. The ADC maps were generated, and we placed a volume-of-interest on the tumor to construct the whole-lesion histogram. Using the histogram, we calculated the mean, 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles of ADC, skewness, and kurtosis. Histogram parameters were correlated with tumor grade, lymphovascular invasion, and pleural invasion. We performed a receiver operating characteristics (ROC) analysis to assess the diagnostic performance of histogram parameters for distinguishing different pathologic features.

RESULTS

The ADC mean, 10th, 25th, 50th, 75th, 90th, and 95th percentiles showed significant differences among the tumor grades. The ADC mean, 25th, 50th, 75th, 90th, and 95th percentiles were significant histogram parameters between high- and low-grade tumors. The ROC analysis between high- and low-grade tumors showed that the 95th percentile ADC achieved the highest area under curve (AUC) at 0.74. Lymphovascular invasion was associated with the ADC mean, 50th, 75th, 90th, and 95th percentiles, skewness, and kurtosis. Kurtosis achieved the highest AUC at 0.809. Pleural invasion was only associated with skewness, with the AUC of 0.648.

CONCLUSIONS

ADC histogram analyses on the basis of the entire tumor volume are able to stratify NSCLCs' tumor grade, lymphovascular invasion and pleural invasion.

Diffusion weighted imaging: Technique and applications

Diffusion weighted imaging (DWI) is a method of signal contrast generation based on the differences in Brownian motion. DWI is a method to evaluate the molecular function and micro-architecture of the human body. DWI signal contrast can be quantified by apparent diffusion coefficient maps and it acts as a tool for treatment response evaluation and assessment of disease progression. Ability to detect and quantify the anisotropy of diffusion leads to a new paradigm called diffusion tensor imaging (DTI). DTI is a tool for assessment of the organs with highly organised fibre structure. DWI forms an integral part of modern state-of-art magnetic resonance imaging and is indispensable in neuroimaging and oncology. DWI is a field that has been undergoing rapid technical evolution and its applications are increasing every day. This review article provides insights in to the evolution of DWI as a new imaging paradigm and provides a summary of current role of DWI in various disease processes.