Diffusion-weighted imaging and positron emission tomography in various cytological subtypes of primary lung adenocarcinoma

The value of T2-weighted MRI contrast ratio combined with DWI in evaluating the pathological grade of solid lung adenocarcinoma

AIM

To assess the predictive value of T2-weighted (T2W) magnetic resonance imaging (MRI) in combination with diffusion-weighted imaging (DWI) for determining the pathological grading of solid lung adenocarcinoma.

MATERIALS AND METHODS

The clinical and imaging data from 153 cases of solid lung adenocarcinoma (82 men, 71 women, mean age 63.2 years) confirmed at histopathology in The First Affiliated Hospital of Xi'an Jiaotong University from January 2017 to May 2022 were analysed retrospectively. Adenocarcinomas were classified into low-grade (G1 and G2) and high-grade (G3) groups following the 2020 pathological grading system proposed by the International Association for the Study of Lung Cancer. The T2-weighted contrast ratio (T2CR), calculated as the T2 signal intensity of the lung mass/nodule divided by the T2 signal intensity of the right rhomboid muscle was utilised. Two experienced radiologists reviewed the MRI images independently, measured the T2CR, and obtained apparent diffusion coefficient (ADC) values. The Mann-Whitney U-test was used to compare general characteristics (sex, age, maximum diameter), T2CR, and ADC values between the low-grade and high-grade groups. The non-parametric Kruskal-Wallis test determined differences in T2CR and ADC values among the five adenocarcinoma subtypes. Receiver characteristic curve (ROC) analysis, along with area under the curve (AUC) calculation, assessed the effectiveness of each parameter in distinguishing the pathological grade of lung adenocarcinoma. A Z-test was used to compare the AUC values.

RESULTS

Among the 153 patients with adenocarcinoma, 103 had low-grade adenocarcinoma, and 50 had high-grade adenocarcinoma. The agreement between T2CR and ADC observers was good (0.948 and 0.929, respectively). None of the parameters followed a normal distribution (p<0.05). The ADC value was lower in the high-grade adenocarcinoma group compared to the low-grade adenocarcinoma group (p=0.004), while the T2CR value was higher in the high-grade group (p=0.011). Statistically significant differences were observed in maximum diameter and gender between the two groups (p<0.001 and p=0.005, respectively), while no significant differences were noted in age (p=0.980). Among the five adenocarcinoma subtypes, only the lepidic and micropapillary subtypes displayed statistical differences in ADC values (p=0.047), with the remaining subtypes showing no statistical differences (p>0.05). The AUC values for distinguishing high-grade adenocarcinoma from low-grade adenocarcinoma were 0.645 for ADC and 0.627 for T2CR. Combining T2CR, ADC, sex, and maximum diameter resulted in an AUC of 0.778, sensitivity of 70%, and specificity of 75%. This combination significantly improved diagnostic efficiency compared to T2CR and ADC alone (p=0.008, z = 2.624; p=0.007, z = 2.679).

CONCLUSION

The MRI quantitative parameters are useful for distinguishing the pathological grades of solid lung adenocarcinoma, offering valuable insights for precise lung cancer treatment.

Cytological characteristics of histological types of lung cancer by cytomorphometric and flow cytometric analyses using liquid-based cytology materials

BACKGROUND

Distinguishing the histological types of lung cancer is essential for determining treatment strategies in clinical practice. In this study, cytomorphological characteristics and proliferative activities were compared among histological types of lung cancer by cytomorphometric and flow cytometric analyses using liquid-based cytology (LBC) samples.

METHODS

Scraped LBC samples from 73 surgically resected specimens were collected between August 2018 and November 2019. Papanicolaou-stained and paired Ki-67-stained slides were used for cytomorphometric analyses. Another sample for each case was analyzed using a flow cytometric system (LC-1000). The cell proliferation index (CPIx) was calculated to evaluate proliferative activity.

RESULTS

In total, 73 cases, including cases of adenocarcinoma (n = 53), squamous cell carcinoma (n = 14), small cell carcinoma (n = 1), large cell neuroendocrine carcinoma (NEC; n = 3), and pleomorphic carcinoma (n = 2) were evaluated. Small cell carcinoma and large cell NEC were categorized into a single group, NEC. The adenocarcinoma group tended to have a larger nuclear area and longer perimeter than other histological types. The NEC group had a considerably higher Ki-67 labeling index and significantly higher CPIx than other histological types (p = .030). A significant positive correlation was observed between the Ki-67 labeling index and CPIx for all cases (r = 0.362, p = .002).

CONCLUSION

The Ki-67 labeling index and flow cytometric analyses focus on proliferative activity for the distinction of histological types of lung cancer, thereby guiding clinical decision-making.

Cytomorphometric and flow cytometric analyses using liquid-based cytology materials in subtypes of lung adenocarcinoma

BACKGROUND

The histological classifications of invasive lung adenocarcinoma subtypes are considered to predict patient prognosis after surgical treatment. The objectives of this study were to evaluate cytomorphological characteristics and proliferative activities among the histological predominant patterns by performing cytomorphometric and flow cytometric analyses using liquid-based cytology materials.

METHODS

Cytological samples fixed by liquid-based cytology preservatives from 53 surgically-resected lung adenocarcinoma specimens were obtained between August 2018 and November 2019. The Papanicolaou-stained and paired Ki-67-stained slides were analyzed for calculating nuclear morphology (nuclear area, nuclear perimeter and nuclear circularity) and Ki-67 labeling index using software. The cell proliferation index (CPIx) was calculated and cellular information including cell cycle stage of tumor cells was obtained by flow cytometry.

RESULTS

The 53 cases included papillary (n = 29), acinar (n = 8), lepidic (n = 5), and solid (n = 4) subtypes, and invasive mucinous adenocarcinoma (n = 7) were also included. In the lepidic pattern, nuclear area (79.6 ± 28.8 μm² ) and perimeter (34.1 ± 6.1 μm) were relatively larger and longer than those of the other predominant patterns. The Ki-67 labeling index of the solid pattern (27.9 ± 12.5%) was highest compared with those of other predominant patterns. There were statistically significant differences in the lepidic versus solid patterns and the papillary versus solid patterns (p = .013 and p = .039, respectively). The calculated mean CPIx of the lepidic and the acinar patterns were approximately two-fold higher than those of the other predominant patterns.

CONCLUSION

By revealing the differences of cytomorphological characteristics, these methodologies might be used for diagnosing cytopathological materials using digital cytopathology.

Comparison of the diagnostic accuracy of diffusion-weighted magnetic resonance imaging and positron emission tomography/computed tomography in pulmonary nodules: a prospective study

Purpose

Computed tomography (CT) and positron emission tomography (PET) are the mainstay imaging methods in the evaluation and follow-up of pulmonary nodules. But they both have high radiation risk for patients. Diffusion- weighted magnetic resonance imaging (DW-MRI), on the other hand, is a radiation free imaging method that gives information about the biological structure of tissues at the molecular level by measuring random movement of water in biological tissues. In this prospective study we aimed to compare the computed tomography characteristics of the nodules in terms of malignancy and to compare the accuracy of DW-MRI and PET/CT results in those patients.

Material and methods

Seventy-six patients suspicious for lung cancer on thorax CT imaging were prospectively further evaluated by thorax diffusion-weighted imaging and PET/CT. Pulmonary lesion characteristics, apparent diffusion coefficient (ADC), and maximum standardised uptake values (SUV_max) were compared with histopathological results.

Results

There was statistically significant moderate negative correlation between PET-SUV_max and ADC values of lung lesions. ADC values below the cut-off was 97.1%, specificity was 97.6%, positive predictive value was 97.1%, and the negative predictive value was 97.6%.

Conclusions

DAG-MRI and PET/CT have similar success in the differentiation of benign and malignant lung lesions.

A severe combined immunodeficiency disease mouse model of human adenocarcinoma with lepidic-predominant growth

Severe combined immunodeficiency disease (SCID) mice with human lepidic adenocarcinoma were established by the intrabronchial implantation of fresh surgically resected specimens. Human pulmonary adenocarcinoma tissue from 16 different cases was transplanted into SCID mice, and SCID mouse tumors were established from four of these cases (25%). Among the four tumors, the tumor cells of two SCID mice showed replacement lepidic growth of mouse alveolar structures accompanied by multiple intrapulmonary lesions. Human lung carcinoma cell lines showing lepidic growth are rare and the xenograft models using the SCID mouse model developed in the current study will be useful for analyzing the growth and/or progression patterns and clinical behavior of lepidic adenocarcinoma, the major histological subtype of human carcinoma of the lung.

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.

A Population-Based Gaussian Mixture Model Incorporating 18F-FDG PET and Diffusion-Weighted MRI Quantifies Tumor Tissue Classes

The aim of our study was to create a novel Gaussian mixture modeling (GMM) pipeline to model the complementary information derived from(18)F-FDG PET and diffusion-weighted MRI (DW-MRI) to separate the tumor microenvironment into relevant tissue compartments and follow the development of these compartments longitudinally.

METHODS

Serial (18)F-FDG PET and apparent diffusion coefficient (ADC) maps derived from DW-MR images of NCI-H460 xenograft tumors were coregistered, and a population-based GMM was implemented on the complementary imaging data. The tumor microenvironment was segmented into 3 distinct regions and correlated with histology. ANCOVA was applied to gauge how well the total tumor volume was a predictor for the ADC and (18)F-FDG, or if ADC was a good predictor of (18)F-FDG for average values in the whole tumor or average necrotic and viable tissues.

RESULTS

The coregistered PET/MR images were in excellent agreement with histology, both visually and quantitatively, and allowed for validation of the last-time-point measurements. Strong correlations were found for the necrotic (r = 0.88) and viable fractions (r = 0.87) between histology and clustering. The GMM provided probabilities for each compartment with uncertainties expressed as a mixture of tissues in which the resolution of scans was inadequate to accurately separate tissues. The ANCOVA suggested that both ADC and (18)F-FDG in the whole tumor (P = 0.0009, P = 0.02) as well as necrotic (P = 0.008, P = 0.02) and viable (P = 0.003, P = 0.01) tissues were a positive, linear function of total tumor volume. ADC proved to be a positive predictor of (18)F-FDG in the whole tumor (P = 0.001) and necrotic (P = 0.02) and viable (P = 0.0001) tissues.

CONCLUSION

The complementary information of (18)F-FDG and ADC longitudinal measurements in xenograft tumors allows for segmentation into distinct tissues when using the novel GMM pipeline. Leveraging the power of multiparametric PET/MRI in this manner has the potential to take the assessment of disease outcome beyond RECIST and could provide an important impact to the field of precision medicine.

Correlation between the Uptake of 18F-Fluorodeoxyglucose (18F-FDG) and the Expression of Proliferation-Associated Antigen Ki-67 in Cancer Patients: A Meta-Analysis

Objective

To study the correlation between ¹⁸F-FDG uptake and cell proliferation in cancer patients by meta-analysis of published articles.

Methods

We searched PubMed (MEDLINE included), EMBASE, and Cochrane Database of Systematic Review, and selected research articles on the relationship between ¹⁸F-FDG uptake and Ki-67 expression (published between August 1, 1994-August 1, 2014), according to the literature inclusion and exclusion criteria. The publishing language was limited to English. The quality of included articles was evaluated according to the Quality Assessment of Diagnosis Accuracy Studies-2 (QUADAS-2). The correlation coefficient (r) was extracted from the included articles and processed by Fisher's r-to-z transformation. The combined correlation coefficient (r) and the 95% confidence interval (CI) were calculated with STATA 11.0 software under a random-effects model. Begg's test was used to analyze the existence of publication bias and draw funnel plot, and the sources of heterogeneity were explored by sensitivity and subgroup analyses.

Results

According to the inclusion and exclusion criteria, 79 articles were finally included, including 81 studies involving a total of 3242 patients. All the studies had a combined r of 0.44 (95% CI, 0.41-0.46), but with a significant heterogeneity (I² = 80.9%, P<0.01). Subgroup analysis for different tumor types indicated that most subgroups showed a reduced heterogeneity. Malignant melanoma (n = 1) had the minimum correlation coefficient (-0.22) between ¹⁸F-FDG uptake and Ki-67 expression, while the thymic epithelial tumors (TETs; n = 2) showed the maximum correlation coefficient of 0.81. The analytical results confirmed that correlation between ¹⁸F-FDG uptake and Ki-67 expression was extremely significant in TETs, significant in gastrointestinal stromal tumors (GISTs), moderate in patients with lung, breast, bone and soft tissue, pancreatic, oral, thoracic, and uterine and ovarian cancers, average in brain, esophageal and colorectal cancers, and poor in head and neck, thyroid, gastric and malignant melanoma tumors. Subgroup analysis indicated that positron emission tomography (PET) or PET/CT imaging technology or Ki-67 and standardized uptake value (SUV) measurement technology did not significantly affect the results of r values, and Begg's test showed no significant publication bias.

Conclusion

In cancer patients, ¹⁸F-FDG uptake showed a moderate positive correlation with tumor cell proliferation. Different tumor types exhibited varied degree of correlation, and the correlation was significant in TETs and GSTs. However, our results need further validation by clinical trials with a large sample of different tumor types.

Evaluation of apparent diffusion coefficient associated with pathological grade of lung carcinoma, before therapy

PURPOSE

To investigate the feasibility and utility of apparent diffusion coefficient (ADC) in predicting the tumor cellular density and grades of lung cancers.

MATERIALS AND METHODS

Forty-one consecutive patients (26 men and 15 women; mean age, 59.9 years) with histologically proven lung cancers were enrolled in the study and underwent MR examination. ADC values and tumor cellular density of different histological grades were analyzed. The relationship of the ADC with tumor cellular density and grades were also evaluated.

RESULTS

The ADC values of lung cancer in grade III was significantly lower than those in grade I and grade II (P = 0.008 and 0.011, respectively). The cellular density in grade III was significantly higher than other two grades (P = 0.029 and 0.022, respectively). ADC value of lung cancer correlated negatively with grades and tumor cellular density (P = 0.001 and P = 0.001, respectively). According to the ROC analysis, the cutoff value of ADC was 1.175 × 10(-3) mm(2) /s with the optimal sensitivity (88.2%) and specificity (62.5%), respectively.

CONCLUSION

ADC measurement of lung cancer was a helpful method to evaluate the pathological grade and tumor cellular density. The quantitative analysis of ADC in conjunction with conventional MR findings could provide more valuable information for the assessment of pulmonary tumor. J

Advances in lung adenocarcinoma classification: a summary of the new international multidisciplinary classification system (IASLC/ATS/ERS)

Due to advances in the understanding of lung adenocarcinoma since the advent of its 2004 World Health System classification, an international multidisciplinary panel [sponsored by the International Association for the Study of Lung Cancer (IASLC), American Thoracic Society (ATS), and European Respiratory Society (ERS)] has recently updated the classification system for lung adenocarcinoma, the most common histologic type of lung cancer. Here, we summarize and highlight the new criteria and terminology, certain aspects of its clinical relevance and its potential treatment impact, and future avenues of research related to the new system.