Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET)/MRI for Lung Cancer Staging

Multidisciplinary approach for locally advanced non-small cell lung cancer (NSCLC): 2023 expert consensus of the Spanish Lung Cancer Group GECP

INTRODUCTION

Recent advances in the treatment of locally advanced NSCLC have led to changes in the standard of care for this disease. For the selection of the best approach strategy for each patient, it is necessary the homogenization of diagnostic and therapeutic interventions, as well as the promotion of the evaluation of patients by a multidisciplinary oncology team.

OBJECTIVE

Development of an expert consensus document with suggestions for the approach and treatment of locally advanced NSCLC leaded by Spanish Lung Cancer Group GECP.

METHODS

Between March and July 2023, a panel of 28 experts was formed. Using a mixed technique (Delphi/nominal group) under the guidance of a coordinating group, consensus was reached in 4 phases: 1. Literature review and definition of discussion topics 2. First round of voting 3. Communicating the results and second round of voting 4. Definition of conclusions in nominal group meeting. Responses were consolidated using medians and interquartile ranges. The threshold for agreement was defined as 85% of the votes.

RESULTS

New and controversial situations regarding the diagnosis and management of locally advanced NSCLC were analyzed and reconciled based on evidence and clinical experience. Discussion issues included: molecular diagnosis and biomarkers, radiologic and surgical diagnosis, mediastinal staging, role of the multidisciplinary thoracic committee, neoadjuvant treatment indications, evaluation of response to neoadjuvant treatment, postoperative evaluation, and follow-up.

CONCLUSIONS

Consensus clinical suggestions were generated on the most relevant scenarios such as diagnosis, staging and treatment of locally advanced lung cancer, which will serve to support decision-making in daily practice.

Chest Magnetic Resonance Imaging: Advances and Clinical Care

Many promising study results as well as technical advances for chest magnetic resonance imaging (MRI) have demonstrated its academic and clinical potentials during the last few decades, although chest MRI has been used for relatively few clinical situations in routine clinical practice. However, the Fleischner Society as well as the Japanese Society of Magnetic Resonance in Medicine have published a few white papers to promote chest MRI in routine clinical practice. In this review, we present clinical evidence of the efficacy of chest MRI for 1) thoracic oncology and 2) pulmonary vascular diseases.

Clinical usability of 3D gradient-echo-based ultrashort echo time imaging: Is it enough to facilitate diagnostic decision in real-world practice?

BACKGROUND

With recent advances in magnetic resonance imaging (MRI) technology, the practical role of lung MRI is expanding despite the inherent challenges of the thorax. The purpose of our study was to evaluate the current status of the concurrent dephasing and excitation (CODE) ultrashort echo-time sequence and the T1-weighted volumetric interpolated breath-hold examination (VIBE) sequence in the evaluation of thoracic disease by comparing it with the gold standard computed tomography (CT).

METHODS

Twenty-four patients with lung cancer and mediastinal masses underwent both CT and MRI including T1-weighted VIBE and CODE. For CODE images, data were acquired in free breathing and end-expiratory images were reconstructed using retrospective respiratory gating. All images were evaluated through qualitative and quantitative approaches regarding various anatomical structures and lesions (nodule, mediastinal mass, emphysema, reticulation, honeycombing, bronchiectasis, pleural plaque and lymphadenopathy) inside the thorax in terms of diagnostic performance in making specific decisions.

RESULTS

Depiction of the lung parenchyma, mediastinal and pleural lesion was not significant different among the three modalities (p > 0.05). Intra-tumoral and peritumoral features of lung nodules were not significant different in the CT, VIBE or CODE images (p > 0.05). However, VIBE and CODE had significantly lower image quality and poorer depiction of airway, great vessels, and emphysema compared to CT (p < 0.05). Image quality of central airways and depiction of bronchi were significantly better in CODE than in VIBE (p < 0.001 and p = 0.005). In contrast, the depiction of the vasculature was better for VIBE than CODE images (p = 0.003). The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were significant greater in VIBE than CODE except for SNRlung and SNRnodule (p < 0.05).

CONCLUSIONS

Our study showed the potential of CODE and VIBE sequences in the evaluation of localized thoracic abnormalities including solid pulmonary nodules.

Revolutionizing tumor detection and classification in multimodality imaging based on deep learning approaches: Methods, applications and limitations

BACKGROUND

The emergence of deep learning (DL) techniques has revolutionized tumor detection and classification in medical imaging, with multimodal medical imaging (MMI) gaining recognition for its precision in diagnosis, treatment, and progression tracking.

OBJECTIVE

This review comprehensively examines DL methods in transforming tumor detection and classification across MMI modalities, aiming to provide insights into advancements, limitations, and key challenges for further progress.

METHODS

Systematic literature analysis identifies DL studies for tumor detection and classification, outlining methodologies including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and their variants. Integration of multimodality imaging enhances accuracy and robustness.

RESULTS

Recent advancements in DL-based MMI evaluation methods are surveyed, focusing on tumor detection and classification tasks. Various DL approaches, including CNNs, YOLO, Siamese Networks, Fusion-Based Models, Attention-Based Models, and Generative Adversarial Networks, are discussed with emphasis on PET-MRI, PET-CT, and SPECT-CT.

FUTURE DIRECTIONS

The review outlines emerging trends and future directions in DL-based tumor analysis, aiming to guide researchers and clinicians toward more effective diagnosis and prognosis. Continued innovation and collaboration are stressed in this rapidly evolving domain.

CONCLUSION

Conclusions drawn from literature analysis underscore the efficacy of DL approaches in tumor detection and classification, highlighting their potential to address challenges in MMI analysis and their implications for clinical practice.

State of the Art MR Imaging for Lung Cancer TNM Stage Evaluation

Since the Radiology Diagnostic Oncology Group (RDOG) report had been published in 1991, magnetic resonance (MR) imaging had limited clinical availability for thoracic malignancy, as well as pulmonary diseases. However, technical advancements in MR systems, such as sequence and reconstruction methods, and adjustments in the clinical protocol for gadolinium contrast media administration have provided fruitful results and validated the utility of MR imaging (MRI) for lung cancer evaluations. These techniques include: (1) contrast-enhanced MR angiography for T-factor evaluation, (2) short-time inversion recovery turbo spin-echo sequences as well as diffusion-weighted imaging (DWI) for N-factor assessment, and (3) whole-body MRI with and without DWI and with positron emission tomography fused with MRI for M-factor or TNM stage evaluation as well as for postoperative recurrence assessment of lung cancer or other thoracic tumors using 1.5 tesla (T) or 3T systems. According to these fruitful results, the Fleischner Society has changed its position to approve of MRI for lung or thoracic diseases. The purpose of this review is to analyze recent advances in lung MRI with a particular focus on lung cancer evaluation, clinical staging, and recurrence assessment evaluation.

Computed DWI MRI Results in Superior Capability for N-Stage Assessment of Non-Small Cell Lung Cancer Than That of Actual DWI, STIR Imaging, and FDG-PET/CT

BACKGROUND

Computed diffusion-weighted imaging (cDWI) is a mathematical computation technique that generates DWIs for any b-value by using actual DWI (aDWI) data with at least two different b-values and may improve differentiation of metastatic from nonmetastatic lymph nodes.

PURPOSE

To determine the appropriate b-value for cDWI to achieve a better diagnostic capability for lymph node staging (N-staging) in non-small cell lung cancer (NSCLC) patients compared to aDWI, short inversion time (TI) inversion recovery (STIR) imaging, or positron emission tomography with 2-[fluorine-18] fluoro-2-deoxy-d-glucose combined with computed tomography (FDG-PET/CT).

STUDY TYPE

Prospective.

SUBJECTS

A total of 245 (127 males and 118 females; mean age 72 years) consecutive histopathologically confirmed NSCLC patients.

FIELD STRENGTH/SEQUENCE

A 3 T, half-Fourier single-shot turbo spin-echo sequence, electrocardiogram (ECG)-triggered STIR fast advanced spin-echo (FASE) sequence with black blood and STIR acquisition and DWI obtained by FASE with b-values of 0 and 1000 sec/mm² .

ASSESSMENT

From aDWIs with b-values of 0 and 1000 (aDWI₁₀₀₀ ) sec/mm² , cDWI using 400 (cDWI₄₀₀ ), 600 (cDWI₆₀₀ ), 800 (cDWI₈₀₀ ), and 2000 (cDWI₂₀₀₀ ) sec/mm² were generated. Then, 114 metastatic and 114 nonmetastatic nodes (mediastinal and hilar lymph nodes) were selected and evaluated with a contrast ratio (CR) for each cDWI and aDWI, apparent diffusion coefficient (ADC), lymph node-to-muscle ratio (LMR) on STIR, and maximum standard uptake value (SUV_max ).

STATISTICAL TESTS

Receiver operating characteristic curve (ROC) analysis, Youden index, and McNemar's test.

RESULTS

Area under the curve (AUC) of CR₆₀₀ was significantly larger than the CR₄₀₀ , CR₈₀₀ , CR₂₀₀₀ , aCR₁₀₀₀ , and SUV_max . Comparison of N-staging accuracy showed that CR₆₀₀ was significantly higher than CR₄₀₀ , CR₂₀₀₀ , ADC, aCR₁₀₀₀ , and SUV_max , although there were no significant differences with CR₈₀₀ (P = 0.99) and LMR (P = 0.99).

DATA CONCLUSION

cDWI with b-value at 600 sec/mm² may have potential to improve N-staging accuracy as compared with aDWI, STIR, and PET/CT.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 2.

Comparison of Interobserver Agreement and Diagnostic Accuracy for IASLC/ITMIG Thymic Epithelial Tumor Staging Among Co-registered FDG-PET/MRI, Whole-body MRI, Integrated FDG-PET/CT, and Conventional Imaging Examination with and without Contrast Media Administrations

RATIONALE AND OBJECTIVES

The purpose of this study was to compare the interobserver agreements and diagnostic accuracies for IASLC/ITMIG (International Association for the Study of Lung Cancer/International Thymic Malignancies Interest Group) thymic epithelial tumor staging of co-registered fluorodeoxyglucose positron emission tomography/magnetic resonance imaging (FDG-PET/MRI), MRI, integrated fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT), and conventional imaging examination.

MATERIALS AND METHODS

Prospective whole-body MRI including diffusion-weighted imaging, integrated PET/CTs, conventional imaging examinations, pathological examinations, and surgical reports, as well as follow-up examinations, were performed for 64 consecutive patients with thymic epithelial tumor. All FDG-PET/MRIs were co-registered PET data with MRI. TNM staging was evaluated by two radiologists on the basis of the IASLC/ITMIG thymic epithelial tumor staging system. Kappa statistics were determined for evaluations of agreements of all factors between each of the methods and final diagnosis. Finally, the diagnostic accuracy of each factor and of determination of the clinical stage was statistically compared to each other using McNemar test.

RESULTS

Agreements for all factors between each method and final diagnosis were assessed as fair, moderate, substantial, or almost perfect (0.28 ≤ kappa value ≤ 0.80; P < .0001). Diagnostic accuracy for N factor of PET/MRI (93.8% [60/64]) and MRI (93.8% [60/64]) was significantly higher than that of conventional imaging examination (81.3% [52/64] vs PET/MRI and MRI; P = .008). In addition, diagnostic accuracy for staging of PET/MRI (84.4% [54/64]) and MRI (84.4 [54/64]) was significantly higher than that of conventional imaging examination (71.9% [46/64] vs PET/MRI and MRI; P = .008).

CONCLUSIONS

Whole-body PET/MRI, MRI, and PET/CT have better interobserver agreements and accuracies than conventional imaging examination for the new IASLC/ITMIG thymic epithelial tumor staging.

Magnetic Fields and Cancer: Epidemiology, Cellular Biology, and Theranostics

Humans are exposed to a complex mix of man-made electric and magnetic fields (MFs) at many different frequencies, at home and at work. Epidemiological studies indicate that there is a positive relationship between residential/domestic and occupational exposure to extremely low frequency electromagnetic fields and some types of cancer, although some other studies indicate no relationship. In this review, after an introduction on the MF definition and a description of natural/anthropogenic sources, the epidemiology of residential/domestic and occupational exposure to MFs and cancer is reviewed, with reference to leukemia, brain, and breast cancer. The in vivo and in vitro effects of MFs on cancer are reviewed considering both human and animal cells, with particular reference to the involvement of reactive oxygen species (ROS). MF application on cancer diagnostic and therapy (theranostic) are also reviewed by describing the use of different magnetic resonance imaging (MRI) applications for the detection of several cancers. Finally, the use of magnetic nanoparticles is described in terms of treatment of cancer by nanomedical applications for the precise delivery of anticancer drugs, nanosurgery by magnetomechanic methods, and selective killing of cancer cells by magnetic hyperthermia. The supplementary tables provide quantitative data and methodologies in epidemiological and cell biology studies. Although scientists do not generally agree that there is a cause-effect relationship between exposure to MF and cancer, MFs might not be the direct cause of cancer but may contribute to produce ROS and generate oxidative stress, which could trigger or enhance the expression of oncogenes.

Small Cell Lung Cancer Staging: Prospective Comparison of Conventional Staging Tests, FDG PET/CT, Whole-Body MRI, and Coregistered FDG PET/MRI

Background: Whole-body MRI and FDG PET/MRI have shown encouraging results for staging of thoracic malignancy, but are poorly studied for staging of small cell lung cancer (SCLC). Objective: To compare the performance of conventional staging tests, FDG PET/CT, whole-body MRI, and FDG PET/MRI for staging of SCLC. Methods: This prospective study included 98 patients (64 men, 34 women; median age, 74 years) with SCLC who underwent conventional staging tests (brain MRI; neck, chest, and abdominopelvic CT; bone scintigraphy), FDG PET/CT, and FDG PET/MRI, within 2 weeks before treatment; coregistered FDG PET/MRI was generated. Two nuclear medicine physicians independently reviewed conventional tests and FDG PET/CT examinations in separate sessions; two chest radiologists independently reviewed whole-body MRI and FDG PET/MRI examinations in separate sessions. Readers assessed T, N, and M categories; TNM stage; and Veterans Administration Lung Cancer Study Group (VALSG) stage. Reader pairs subsequently reached consensus. Stages determined clinically during tumor board sessions served as reference. Results: Accuracy for T category was higher (p<.05) for whole-body MRI (94.9%) and FDG PET/MRI (94.9%) than for FDG PET/CT (85.7%). Accuracy for N category was higher (p<.05) for whole-body MRI (84.7%), FDG PET/MRI (83.7%), and FDG PET/CT (81.6%) than for conventional staging tests (75.5%). Accuracy for M category was higher (p<.05) for whole-body MRI (94.9%), FDG PET/MRI (94.9%), and FDG PET/CT (94.9%) than for conventional staging tests (84.7%). Accuracy for TNM stage was higher (p<.05) for whole-body MRI (88.8%) and FDG PET/MRI (86.7%) than for FDG PET/CT (77.6%) and conventional staging tests (72.4%). Accuracy for VALSG stage was higher (p<.05) for whole-body MRI (95.9%), FDG PET/MRI (95.9%), and FDG PET/CT (98.0%) than for conventional staging tests (82.7%). Interobserver agreement, expressed as kappa, ranged from 0.81 to 0.94 across imaging tests and staging endpoints. Conclusion: FDG PET/CT, whole-body MRI, and coregistered FDG PET/MRI outperformed conventional tests for various staging endpoints in patients with SCLC. Whole-body MRI and FDG PET/MRI outperformed FDG PET/CT for T category and thus TNM stage, indicating utility of MRI for assessing extent of local invasion in SCLC. Clinical Impact: Incorporation of either MRI approach may improve initial staging evaluation in SCLC.

Development and Validation of a Combined Model for Preoperative Prediction of Lymph Node Metastasis in Peripheral Lung Adenocarcinoma

Background

Based on the “seed and soil” theory proposed by previous studies, we aimed to develop and validate a combined model of machine learning for predicting lymph node metastasis (LNM) in patients with peripheral lung adenocarcinoma (PLADC).

Methods

Radiomics models were developed in a primary cohort of 390 patients (training cohort) with pathologically confirmed PLADC from January 2016 to August 2018. The patients were divided into the LNM (−) and LNM (+) groups. Thereafter, the patients were subdivided according to TNM stages N0, N1, N2, and N3. Radiomic features from unenhanced computed tomography (CT) were extracted. Radiomic signatures of the primary tumor (R1) and adjacent pleura (R2) were built as predictors of LNM. CT morphological features and clinical characteristics were compared between both groups. A combined model incorporating R1, R2, and CT morphological features, and clinical risk factors was developed by multivariate analysis. The combined model’s performance was assessed by receiver operating characteristic (ROC) curve. An internal validation cohort containing 166 consecutive patients from September 2018 to November 2019 was also assessed.

Results

Thirty-one radiomic features of R1 and R2 were significant predictors of LNM (all P < 0.05). Sex, smoking history, tumor size, density, air bronchogram, spiculation, lobulation, necrosis, pleural effusion, and pleural involvement also differed significantly between the groups (all P < 0.05). R1, R2, tumor size, and spiculation in the combined model were independent risk factors for predicting LNM in patients with PLADC, with area under the ROC curves (AUCs) of 0.897 and 0.883 in the training and validation cohorts, respectively. The combined model identified N0, N1, N2, and N3, with AUCs ranging from 0.691–0.927 in the training cohort and 0.700–0.951 in the validation cohort, respectively, thereby indicating good performance.

Conclusion

CT phenotypes of the primary tumor and adjacent pleura were significantly associated with LNM. A combined model incorporating radiomic signatures, CT morphological features, and clinical risk factors can assess LNM of patients with PLADC accurately and non-invasively.

State-of-the-art MR Imaging for Thoracic Diseases

Since thoracic MR imaging was first used in a clinical setting, it has been suggested that MR imaging has limited clinical utility for thoracic diseases, especially lung diseases, in comparison with x-ray CT and positron emission tomography (PET)/CT. However, in many countries and states and for specific indications, MR imaging has recently become practicable. In addition, recently developed pulmonary MR imaging with ultra-short TE (UTE) and zero TE (ZTE) has enhanced the utility of MR imaging for thoracic diseases in routine clinical practice. Furthermore, MR imaging has been introduced as being capable of assessing pulmonary function. It should be borne in mind, however, that these applications have so far been academically and clinically used only for healthy volunteers, but not for patients with various pulmonary diseases in Japan or other countries. In 2020, the Fleischner Society published a new report, which provides consensus expert opinions regarding appropriate clinical indications of pulmonary MR imaging for not only oncologic but also pulmonary diseases. This review article presents a brief history of MR imaging for thoracic diseases regarding its technical aspects and major clinical indications in Japan 1) in terms of what is currently available, 2) promising but requiring further validation or evaluation, and 3) developments warranting research investigations in preclinical or patient studies. State-of-the-art MR imaging can non-invasively visualize lung structural and functional abnormalities without ionizing radiation and thus provide an alternative to CT. MR imaging is considered as a tool for providing unique information. Moreover, prospective, randomized, and multi-center trials should be conducted to directly compare MR imaging with conventional methods to determine whether the former has equal or superior clinical relevance. The results of these trials together with continued improvements are expected to update or modify recommendations for the use of MRI in near future.

Added Value of Magnetic Resonance Imaging for the Evaluation of Mediastinal Lesions

The high soft tissue contrast and tissue characterization properties of magnetic resonance imaging allow further characterization of indeterminate mediastinal lesions on chest radiography and computed tomography, increasing diagnostic specificity, preventing unnecessary intervention, and guiding intervention or surgery when needed. The combination of its higher soft tissue contrast and ability to image dynamically during free breathing, without ionizing radiation exposure, allows more thorough and readily appreciable assessment of a lesion's invasiveness and assessment of phrenic nerve involvement, with significant implications for prognostic clinical staging and surgical management.

Screening and staging for non-small cell lung cancer by serum laser Raman spectroscopy

OBJECTIVE

Lung cancer is the leading cause of cancer-related death worldwide. Current clinical screening methods to detect lung cancer are expensive and associated with many complications. Raman spectroscopy is a spectroscopic technique that offers a convenient method to gain molecular information about biological samples. In this study, we measured the serum Raman spectral intensity of healthy volunteers and patients with different stages of non-small cell lung cancer. The purpose of this study was to evaluate the application of serum laser Raman spectroscopy as a low cost alternative method in the screening and staging of non-small cell lung cancer (NSCLC).

METHODS

The Raman spectra of the sera of peripheral venous blood were measured with a LabRAM HR 800 confocal Micro Raman spectrometer for individuals from five groups including 14 healthy volunteers (control group), 23 patients with stage I NSCLC (stage I group), 24 patients with stage II NSCLC (stage II group), 19 patients with stage III NSCLC (stage III group), 11 patients with stage IV NSCLC (stage IV group). Each serum sample was measured 3 times at different spots and the average spectra represented the signal of Raman spectra in each case. The Raman spectrum signal data of the five groups were statistically analyzed by analysis of variance (ANOVA), principal component analysis (PCA), linear discriminant analysis (LDA), and cross-validation.

RESULTS

Raman spectral intensity was sequentially reduced in serum samples from control group, stage I group, stage II group and stage III/IV group. The strongest peak intensity was observed in the control group, and the weakest one was found in the stage III/IV group at bands of 848 cm^-1, 999 cm^-1, 1152 cm^-1, 1446 cm^-1 and 1658 cm^-1 (P < 0.05). Linear discriminant analysis showed that the sensitivity to identify healthy people, stage I, stage II, and stage III/IV NSCLC was 86%, 65%, 75%, and 87%, respectively; the specificity was 95%, 94%, 88%, and 93%, respectively; and the overall accuracy rate was 92% (71/77).

CONCLUSION

The laser Raman spectroscopy can effectively identify patients with stage I, stage II or stage III/IV Non-Small Cell Lung cancer using patient serum samples.

Dilemmas in Lung Cancer Staging

The advent of the 8th edition of the lung cancer staging system reflects a further meticulous evidence-based advance in the stratification of the survival of patients with lung cancer. Although addressing many limitations of earlier staging systems, several limitations in staging remain. This article reviews from a radiological perspective the limitations of the current staging system, highlighting the process of TNM restructuring, the residual issues with regards to the assignment of T, N, M descriptors, and their associated stage groupings and how these dilemmas impact guidance of multidisciplinary teams taking care of patients with lung cancer.

Radiomics and its emerging role in lung cancer research, imaging biomarkers and clinical management: State of the art

With the development of functional imaging modalities we now have the ability to study the microenvironment of lung cancer and its genomic instability. Radiomics is defined as the use of automated or semi-automated post-processing and analysis of large amounts of quantitative imaging features that can be derived from medical images. The automated generation of these analytical features helps to quantify a number of variables in the imaging assessment of lung malignancy. These imaging features include: tumor spatial complexity, elucidation of the tumor genomic heterogeneity and composition, subregional identification in terms of tumor viability or aggressiveness, and response to chemotherapy and/or radiation. Therefore, a radiomic approach can help to reveal unique information about tumor behavior. Currently available radiomic features can be divided into four major classes: (a) morphological, (b) statistical, (c) regional, and (d) model-based. Each category yields quantitative parameters that reflect specific aspects of a tumor. The major challenge is to integrate radiomic data with clinical, pathological, and genomic information to decode the different types of tissue biology. There are many currently available radiomic studies on lung cancer for which there is a need to summarize the current state of the art.