Diagnostic Yield of Staging Brain MRI in Patients with Newly Diagnosed Non-Small Cell Lung Cancer

Does clinical T1N0 GGN really require checking for distant metastasis during initial staging for lung cancer?

BACKGROUND

Accurate clinical staging is crucial for selection of optimal oncological treatment strategies in non-small cell lung cancer (NSCLC). Although brain MRI, bone scintigraphy and whole-body PET/CT play important roles in detecting distant metastases, there is a lack of evidence regarding the indication for metastatic staging in early NSCLCs, especially ground-grass nodules (GGNs). Our aim was to determine whether checking for distant metastasis is required in cases of clinical T1N0 GGN.

METHODS

This was a retrospective study of initial staging using imaging tests in patients who had undergone complete surgical R0 resection for clinical T1N0 Stage IA NSCLC.

RESULTS

A total of 273 patients with cT1N0 GGNs (n = 183) or cT1N0 solid tumors (STs, n = 90) were deemed eligible. No cases of distant metastasis were detected on initial routine imaging evaluations. Among all cT1N0M0 cases, there were 191 incidental findings on various modalities (128 in the GGN). Most frequently detected on brain MRI was cerebral leukoaraiosis, which was found in 98/273 (35.9%) patients, while cerebral infarction was detected in 12/273 (4.4%) patients. Treatable neoplasms, including brain meningioma and thyroid, gastric, renal and colon cancers were also detected on PET/CT (and/or MRI). Among those, 19 patients were diagnosed with a treatable disease, including other-site cancers curable with surgery.

CONCLUSIONS

Extensive staging (MRI, scintigraphy, PET/CT etc.) for distant metastasis is not required for patients diagnosed with clinical T1N0 GGNs, though various imaging modalities revealed the presence of adventitious diseases with the potential to increase surgical risks, lead to separate management, and worsen patient outcomes, especially in elderly patients. If clinically feasible, it could be considered to complement staging with whole-body procedures including PET/CT.

A systematic review of brain metastases from lung cancer using magnetic resonance neuroimaging: Clinical and technical aspects

INTRODUCTION

Brain metastases (BMs) are common in lung cancer (LC) and are associated with poor prognosis. Magnetic resonance imaging (MRI) plays a vital role in the detection, diagnosis and management of BMs. This review summarises recent advances in MRI techniques for BMs from LC.

METHODS

This systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A comprehensive literature search was conducted in three electronic databases: PubMed, Scopus and the Web of Science. The search was limited to studies published between January 2000 and March 2023. The quality of the included studies was evaluated using appropriate tools for different study designs. A narrative synthesis was carried out to describe the key findings of the included studies.

RESULTS

Sixty-five studies were included. Standard MRI sequences such as T1-weighted (T1w), T2-weighted (T2w) and fluid-attenuated inversion recovery (FLAIR) were commonly used. Advanced techniques included perfusion-weighted imaging (PWI), diffusion-weighted imaging (DWI) and radiomics analysis. DWI and PWI parameters could distinguish tumour recurrence from radiation necrosis. Radiomics models predicted genetic mutations and the risk of BMs. Diagnostic accuracy was improved with deep learning (DL) approaches. Prognostic factors such as performance status and concurrent chemotherapy impacted survival.

CONCLUSION

Advanced MRI techniques and specialised MRI methods have emerging roles in managing BMs from LC. PWI and DWI improve diagnostic accuracy in treated BMs. Radiomics and DL facilitate personalised prognosis and treatment. Magnetic resonance imaging plays a key role in the continuum of care for BMs of patients with LC, from screening to treatment monitoring.

Canadian Consensus Recommendations for the Management of Operable Stage II/III Non-Small-Cell Lung Cancer: Results of a Modified Delphi Process

The treatment paradigm for patients with stage II/III non-small-cell lung cancer (NSCLC) is rapidly evolving. We performed a modified Delphi process culminating at the Early-stage Lung cancer International eXpert Retreat (ELIXR23) meeting held in Montreal, Canada, in June 2023. Participants included medical and radiation oncologists, thoracic surgeons and pathologists from across Quebec. Statements relating to diagnosis and treatment paradigms in the preoperative, operative and postoperative time periods were generated and modified until all held a high level of consensus. These statements are aimed to help guide clinicians involved in the treatment of patients with stage II/III NSCLC.

High-precision bladder cancer diagnosis method: 2D Raman spectrum figures based on maintenance technology combined with automatic weighted feature fusion network

BACKGROUND

Raman spectroscopy has been extensively utilized as a marker-free detection method in the complementary diagnosis of cancer. Multivariate statistical classification analysis is frequently employed for Raman spectral data classification. Nevertheless, traditional multivariate statistical classification analysis performs poorly when analyzing large samples and multicategory spectral data. In addition, with the advancement of computer vision, convolutional neural networks (CNNs) have demonstrated extraordinarily precise analysis of two-dimensional image processing.

RESULT

Combining 2D Raman spectrograms with automatic weighted feature fusion network (AWFFN) for bladder cancer detection is presented in this paper. Initially, the s-transform (ST) is implemented for the first time to convert 1D Raman data into 2D spectrograms, achieving 99.2% detection accuracy. Second, four upscaling techniques, including short time fourier transform (STFT), recurrence map (RP), markov transform field (MTF), and grammy angle field (GAF), were used to transform the 1D Raman spectral data into a variety of 2D Raman spectrograms. In addition, a particle swarm optimization (PSO) algorithm is combined with VGG19, ResNet50, and ResNet101 to construct a weighted feature fusion network, and this parallel network is employed for evaluating multiple spectrograms. Class activation mapping (CAM) is additionally employed to illustrate and evaluate the process of feature extraction via the three parallel network branches. The results demonstrate that the combination of a 2D Raman spectrogram along with a CNN for the diagnosis of bladder cancer obtains a 99.2% accuracy rate，which indicates that it is an extremely promising auxiliary technology for cancer diagnosis.

SIGNIFICANCE

The proposed two-dimensional Raman spectroscopy method has an improved precision than one-dimensional spectroscopic data, which presents a potential methodology for assisted cancer detection and providing crucial technical support for assisted diagnosis.

The American Association for Thoracic Surgery (AATS) 2023 Expert Consensus Document: Staging and multidisciplinary management of patients with early-stage non-small cell lung cancer

Novel targeted therapy and immunotherapy drugs have recently been approved for use in patients with surgically resectable lung cancer. Accurate staging, early molecular testing, and knowledge of recent trials are critical to optimize oncologic outcomes in these patients.

Use of "Diagnostic Yield" in Imaging Research Reports: Results from Articles Published in Two General Radiology Journals

OBJECTIVE

"Diagnostic yield," also referred to as the detection rate, is a parameter positioned between diagnostic accuracy and diagnosis-related patient outcomes in research studies that assess diagnostic tests. Unfamiliarity with the term may lead to incorrect usage and delivery of information. Herein, we evaluate the level of proper use of the term "diagnostic yield" and its related parameters in articles published in Radiology and Korean Journal of Radiology (KJR).

MATERIALS AND METHODS

Potentially relevant articles published since 2012 in these journals were identified using MEDLINE and PubMed Central databases. The initial search yielded 239 articles. We evaluated whether the correct definition and study setting of "diagnostic yield" or "detection rate" were used and whether the articles also reported companion parameters for false-positive results. We calculated the proportion of articles that correctly used these parameters and evaluated whether the proportion increased with time (2012-2016 vs. 2017-2022).

RESULTS

Among 39 eligible articles (19 from Radiology and 20 from KJR), 17 (43.6%; 11 from Radiology and 6 from KJR) correctly defined "diagnostic yield" or "detection rate." The remaining 22 articles used "diagnostic yield" or "detection rate" with incorrect meanings such as "diagnostic performance" or "sensitivity." The proportion of correctly used diagnostic terms was higher in the studies published in Radiology than in those published in KJR (57.9% vs. 30.0%). The proportion improved with time in Radiology (33.3% vs. 80.0%), whereas no improvement was observed in KJR over time (33.3% vs. 27.3%). The proportion of studies reporting companion parameters was similar between journals (72.7% vs. 66.7%), and no considerable improvement was observed over time.

CONCLUSION

Overall, a minority of articles accurately used "diagnostic yield" or "detection rate." Incorrect usage of the terms was more frequent without improvement over time in KJR than in Radiology. Therefore, improvements are required in the use and reporting of these parameters.

Epidermal growth factor receptor mutations and brain metastases in non-small cell lung cancer

Studies have revealed that non-small cell lung cancer (NSCLC) with epidermal growth factor receptor (EGFR) mutations has a high incidence of brain metastases (BMs). However, the association between EGFR mutations and BMs remains unknown. This review summarizes detailed information about the incidence of BMs, clinical and imaging characteristics of BMs, brain surveillance strategies, influence of treatments on BMs, prognosis after BMs, and differences in EGFR mutations between paired primary tumors and BMs in EGFR-mutated NSCLC. The prognostic results demonstrate that patients with mutated EGFR have a higher incidence of BMs, EGFR tyrosine kinase inhibitors (EGFR-TKIs) (afatinib and osimertinib) delay the development of BMs, and patients with mutated EGFR with synchronous or early BMs have better overall survival after BMs than those with wild-type EGFR. The EGFR mutation status of BM sites is not always in accordance with the primary tumors, which indicates that there is heterogeneity in EGFR gene status between paired primary tumors and BMs. However, the EGFR gene status of the primary site can largely represent that of BM sites. Among patients developing synchronous BMs, patients with mutated EGFR are less likely to have central nervous system (CNS) symptoms than patients with wild-type EGFR. However, the possibility of neuro-symptoms is high in patients with metachronous BMs. Patients with mutated EGFR tend to have multiple BMs as compared to patients with wild-type EGFR. Regarding very early-stage NSCLC patients without neuro-symptoms, regular neuroimaging follow-up is not recommended. Among advanced NSCLC patients with EGFR mutation, liberal brain imaging follow-up in the first several years showed more advantages in terms of cost.

Diagnostic yield of MR myelography in patients with newly diagnosed spontaneous intracranial hypotension: a systematic review and meta-analysis

OBJECTIVES

To investigate the pooled diagnostic yield of MR myelography in patients with newly diagnosed spontaneous intracranial hypotension (SIH).

METHODS

A literature search of the MEDLINE/PubMed and Embase databases was conducted until July 25, 2021, including studies with the following inclusion criteria: (a) population: patients with newly diagnosed SIH; (b) diagnostic modality: MR myelography or MR myelography with intrathecal gadolinium for evaluation of CSF leakage; (c) outcomes: diagnostic yield of MR myelography or MR myelography with intrathecal gadolinium. The risk of bias was evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. DerSimonian-Laird random-effects modeling was used to calculate the pooled estimates. Subgroup analysis regarding epidural fluid collection and meta-regression were additionally performed.

RESULTS

Fifteen studies with 643 patients were included. Eight studies used MR myelography with intrathecal gadolinium, and 11 used MR myelography. The overall quality of the included studies was moderate. The pooled diagnostic yield of MR myelography was 86% (95% CI, 80-91%) and that of MR myelography with intrathecal gadolinium was 83% (95% CI, 51-96%). There was no significant difference in pooled diagnostic yield between MR myelography and MR myelography with intrathecal gadolinium (p = 0.512). In subgroup analysis, the pooled diagnostic yield of the epidural fluid collection was 91% (95% CI, 84-94%). In meta-regression, the diagnostic yield was unaffected regardless of consecutive enrollment, magnet strength, or 2D/3D.

CONCLUSIONS

MR myelography had a high diagnostic yield in patients with SIH. MR myelography is non-invasive and not inferior to MR myelography with intrathecal gadolinium.

KEY POINTS

• The pooled diagnostic yield of MR myelography was 86% (95% CI, 80-91%) in patients with spontaneous intracranial hypotension. • There was no significant difference in pooled diagnostic yield between MR myelography and MR myelography with intrathecal gadolinium. • MR myelography is non-invasive and not inferior to MR myelography with intrathecal gadolinium.

Hippocampal Metastasis Rate Based on Non-Small Lung Cancer TNM Stage and Molecular Markers

Hippocampal-avoidance whole-brain radiation therapy (HA-WBRT) is justified because of low hippocampal brain metastases (BM) rate and its prevention of cognitive decline. However, we hypothesize that the risk of developing BM in the hippocampal-avoidance region (HAR) may differ depending on the lung-cancer stage and molecular status. We retrospectively reviewed 123 patients with non-small cell lung cancer (NSCLC) at the initial diagnosis of BM. The number of BMs within the HAR (5 mm expansion) was counted. The cohort was divided into patients with and without BMs in the HAR, and their clinical variables, TNM stage, and epidermal growth factor receptor (EGFR) status were compared. The most influential variable predicting BMs in the HAR was determined using multi-variable logistic regression, classification and regression tree (CART) analyses, and gradient boosting method (GBM). The feasibility of HAR expansion was tested using generalized estimating equation marginal model. Patients with BMs in the HAR were more frequently non-smokers, and more likely to have extra-cranial metastases and EGFR mutations (p<0.05). Multi-variable analysis revealed that extra-cranial metastases were independently associated with the presence of BM in the HAR (odds ratio=8.75, p=0.04). CART analysis and GBM revealed that the existence of extra-cranial metastasis was the most influential variable predicting BM occurrence in the HAR (variable importance: 23% and relative influence: 37.38). The estmated BM incidence of patients without extra-cranial metastases in th extended HAR (7.5-mm and 10-mm expansion) did not differ significantly from that in the conventional HAR. In conclusion, NSCLC patients with extra-cranial metastases were more likely to have BMs in the HAR than those without extra-cranial metastases.

Revisiting Indications for Brain Imaging During the Clinical Staging Evaluation of Lung Cancer

Introduction

Available guidelines are inconsistent as to whether patients with newly diagnosed clinical stage II NSCLC should receive routine brain imaging.

Methods

The National Cancer Database was queried for the prevalence of isolated brain metastases among patients with newly diagnosed NSCLC in 2016 and 2017. Patients with metastases in locations other than the brain were excluded. The prevalences were then stratified by clinical T and N classifications and further stratified into a summary stage, which was calculated based on T and N classifications. The summary stage represents the clinical stage that would have been available at the time of decision for brain imaging.

Results

A total of 6,949 of 149,958 patients (4.6%) with clinical stages I, II, III, or brain-limited stage IV NSCLC had dissemination limited to the brain. As T and N stages increased, prevalence of brain metastases generally increased. Among patients with node-negative (N0) NSCLC, the prevalence of brain-only metastases increased from 1.2% in patients with T1a to 3.8% among patients with T4 (p < 0.001). Among patients with T1a, the prevalence of brain-only metastases increased from 1.2% for patients with N0 to 7.9% for patients with N3 (p < 0.001). The prevalence of brain-limited metastases generally increased with increasing summary stage. The prevalence of brain-only metastases among patients with stage IA was 1.7% whereas that among patients with stage IIIA was 6.7% (p < 0.001). Of note, the prevalence of brain-limited metastases was approximately 6% for both summary stages II and III.

Conclusions

Considering the similarity in prevalence of isolated brain metastases and the potential hazards associated with brain imaging in early stage NSCLC, practitioners may consider a more liberal use of brain imaging when interpreting conflicting guidelines.

No Prognostic Impact of Staging Brain MRI in Patients with Stage IA Non-Small Cell Lung Cancer

Background Although various guidelines discourage performing brain MRI for staging purposes in asymptomatic patients with clinical stage IA non-small cell lung cancer (NSCLC), evidence regarding their postoperative survival is lacking. Purpose To investigate the survival benefit of performing brain MRI in asymptomatic patients with early-stage NSCLC. Materials and Methods Patients who underwent curative resection between February 2009 and March 2016 for clinical TNM stage T1N0M0 NSCLC were retrospectively included. Patient survival and development of brain metastasis during postoperative surveillance were documented. The cumulative survival rate and incidence of brain metastasis were compared between patients who underwent surgery with or without staging brain MRI by using Cox regression and a Fine-Gray subdistribution hazard model, respectively, for multivariable adjustment. Propensity score matching and inverse probability of treatment weighting were applied for confounder adjustment. Results A total of 628 patients (mean age, 64 years ± 10 [SD]; 319 men) were included, of whom 53% (331 of 628) underwent staging brain MRI. In the multivariable analyses, brain MRI did not show prognostic benefits for brain metastasis-free survival (hazard ratio [HR], 1.06; 95% CI: 0.69, 1.63; P = .79), time to brain metastasis (HR, 1.60; 95% CI: 0.70, 3.94; P = .29), and overall survival (HR, 0.86; 95% CI, 0.54, 1.37; P = .54). Consistent results were obtained after propensity score matching (brain metastasis-free survival [HR, 0.97; 95% CI: 0.60, 1.57; P = .91], time to brain metastasis [HR, 1.29; 95% CI: 0.50, 3.33; P = .60], and overall survival [HR, 0.89; 95% CI: 0.53, 1.51; P = .67]) and inverse probability of treatment weighting. Conclusion No difference was observed between asymptomatic patients with clinical stage IA non-small cell lung cancer who underwent staging brain MRI and those who did not in terms of brain metastasis-free survival, time to brain metastasis, and overall survival. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Bizzi and Pascuzzo in this issue.

Imaging Advances for Central Nervous System Tumors

This article reviews recent advances in the use of standard and advanced imaging techniques for diagnosis and treatment of central nervous system (CNS) tumors, including glioma and brain metastasis. Following the recent transition from a histology-based approach in classifying CNS tumors to one that integrates histology with the molecular information of tumor, the approaches for imaging CNS tumors have also been adapted to this new framework. Some challenges related to the diagnosis and treatment of CNS tumors, such as differentiating tumor from treatment-related imaging changes, require further progress to implement advanced imaging for clinical use.

Accurate diagnosis of lung tissues for 2D Raman spectrogram by deep learning based on short-time Fourier transform

Multivariate statistical analysis methods have an important role in spectrochemical analyses to rapidly identify and diagnose cancer and the subtype. However, utilizing these methods to analyze lager amount spectral data is challenging, and poses a major bottleneck toward achieving high accuracy. Here, a new convolutional neural networks (CNN) method based on short-time Fourier transform (STFT) to diagnose lung tissues via Raman spectra readily is proposed. The models yield that the accuracies of the new method are higher than the conventional methods (principal components analysis -linear discriminant analysis and support vector machine) for validation group (95.2% vs 85.5%, 94.4%) and test group (96.5% vs 90.4%, 93.9%) after cross-validation. The results illustrate that the new method which converts one-dimensional Raman data into two-dimensional Raman spectrograms improve the discriminatory ability of lung tissues and can achieve automatically accurate diagnosis of lung tissues.

Identification of predictors for brain metastasis in newly diagnosed non-small cell lung cancer: a single-center cohort study

OBJECTIVES

To identify clinical and staging chest CT characteristics predictive of brain metastasis in patients with newly diagnosed NSCLC dichotomized according to resectability.

METHODS

Patients newly diagnosed with NSCLC of clinical stages II-IV between November 2017 and October 2018 were enrolled and classified into resectable (stage II+IIIA) and unresectable stages (stage IIIB/C+IV) according to chest CT. Associations of clinicopathological characteristics and CT findings with brain metastasis were analyzed using logistic regression. Predictive models were evaluated using receiver operating characteristics curve analysis. A subgroup analysis for unresectable-stage patients with known epidermal growth factor receptor gene (EGFR) mutation status was performed.

RESULTS

This study included 911 NSCLC patients (mean age, 65 ± 11 years; 620 men), 194 of whom were diagnosed with brain metastasis. For resectable stages, independent predictors for brain metastasis were N2-stage (13 of 25 patients), absence of air-bronchogram/bubble lucency (23 of 25 patients), and presence of spiculation (15 of 25 patients), with a model combining the two imaging features showing an AUC of 0.723. In unresectable stages, independent predictors of brain metastasis were younger age, female sex, extrathoracic metastasis, and adenocarcinoma, with models combining these showing AUCs of 0.675-0.766. In the subgroup with known EGFR-mutation status, extrathoracic metastasis and positive EGFR mutation were independent predictors of brain metastasis, with the model showing AUCs of 0.641-0.732.

CONCLUSION

CT-derived imaging features, clinical stages, lung cancer subtype, and EGFR mutation were associated with brain metastasis in patients with newly diagnosed NSCLC. The predictors were completely different between resectable and unresectable stages.

KEY POINTS

• In resectable stages of NSCLC, two imaging features (absence of air-bronchogram/bubble lucency and presence of spiculation) and N2 stage were independent predictors of brain metastasis. • In unresectable stages of NSCLC, younger age, female sex, extrathoracic metastasis, and adenocarcinoma were associated with brain metastasis. • In the subgroup of NSCLC with known EGFR-mutation status, extrathoracic metastasis and positive EGFR mutation were independent predictors of brain metastasis.

Development of Brain Metastases in Patients With Non-Small Cell Lung Cancer and No Brain Metastases at Initial Staging Evaluation: Cumulative Incidence and Risk Factor Analysis

Background: While established guidelines give indications for performing staging brain MRI at initial non-small cell lung cancer (NSCLC) diagnosis, guidelines are lacking for performing surveillance brain MRI in patients without brain metastases at presentation. Objective: To estimate the cumulative incidence of, and risk factors associated with, brain metastasis development in patients with NSCLC without brain metastases at initial presentation. Methods: This retrospective study included 1495 patients with NSCLC (mean age 65±10 years; 920 men, 575 women) without brain metastases at initial evaluation that included brain MRI. Follow-up brain MRI was ordered at referrer physicians' discretion. MRI examinations were reviewed in combination with clinical records for brain metastasis development; patients not undergoing MRI were deemed to have not developed metastases through last clinical follow-up. Cumulative incidence of brain metastases was determined with death as a competing risk and stratified by clinical stage group, cell type, and epidermal growth factor receptor (EGFR) status. Univariable and multivariable Cox proportional hazards regression analyses were performed. Results: A total of 258/1495 (17.3%) patients underwent follow-up brain MRI, and 72/1495 (4.8%) developed brain metastases at a median of 12.3 months after initial NSCLC diagnosis. Among the 72 patients developing metastases, 44% had no neurologic symptoms, and 58% had stable primary thoracic disease. Cumulative incidence of brain metastases at 6, 12, 18, and 24 months was 0.6%, 2.1%, 4.2% and 6.8%, respectively. Cumulative incidence was higher (P<.001) in clinical stage III-IV (1.3%, 3.9%, 7.7%, and 10.9%) than I-II (0.0%, 0.8%, 1.2%, and 2.6%) disease, and higher (P<.001) in EGFR positive (0.7%, 2.5%, 6.3%, and 12.3%) than EGFR negative (0.4%, 1.8%, 2.9%, and 4.4%) adenocarcinoma. Among 1109 patients with adenocarcinoma, independent risk factors for brain metastasis development were clinical stage III-IV (hazard ratio [HR]=9.39; P<.001) and EGFR positivity (HR=1.78; P=.04). Brain metastasis incidence over the study interval was 8.7% in clinical stage III-IV disease and 8.6% in EGFR positive adenocarcinoma. Conclusion: Clinical stage III-IV and EGFR positive adenocarcinoma are independent risk factors for brain metastasis development. Clinical impact: Surveillance brain MRI may be warranted 12 months after initial evaluation in clinical stage III-IV disease or EGFR-positive adenocarcinoma.