Update of MR Imaging for Evaluation of Lung Cancer

Imaging of Solid Pulmonary Nodules

Early detection with accurate classification of solid pulmonary nodules is critical in reducing lung cancer morbidity and mortality. Computed tomography (CT) remains the most widely used imaging examination for pulmonary nodule evaluation; however, other imaging modalities, such as PET/CT and MRI, are increasingly used for nodule characterization. Current advances in solid nodule imaging are largely due to developments in machine learning, including automated nodule segmentation and computer-aided detection. This review explores current multi-modality solid pulmonary nodule detection and characterization with discussion of radiomics and risk prediction models.

[18F]FDG PET/MRI combined with chest HRCT in early cancer detection: a retrospective study of 3020 asymptomatic subjects

PURPOSE

PET/MRI has become an important medical imaging approach in clinical practice. In this study, we retrospectively investigated the detectability of fluorine-18 (18F)-fluorodeoxyglucose positron emission tomography/magnetic resonance imaging ([18F]FDG PET/MRI) combined with chest computerized tomography (CT) for early cancer in a large cohort of asymptomatic subjects.

METHODS

This study included a total of 3020 asymptomatic subjects who underwent whole-body [18F]FDG PET/MRI and chest HRCT examinations. All subjects received a 2-4-year follow-up for cancer development. Cancer detection rate, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the [18F]FDG PET/MRI with or without chest HRCT were calculated and analyzed.

RESULTS

Sixty-one subjects were pathologically diagnosed with cancers, among which 59 were correctly detected by [18F]FDG PET/MRI combined with chest HRCT. Of the 59 patients (32 with lung cancer, 9 with breast cancer, 6 with thyroid cancer, 5 with colon cancer, 3 with renal cancer, 1 with prostate cancer, 1 with gastric cancer, 1 with endometrial cancer, and 1 with lymphoma), 54 (91.5%) were at stage 0 or stage I (according to the 8th edition of the tumor-node-metastasis [TNM] staging system), 33 (55.9%) were detected by PET/MRI alone (27 with non-lung cancers and 6 with lung cancer). Cancer detection rate, sensitivity, specificity, PPV, and NPV for PET/MRI combined with chest CT were 2.0%, 96.7%, 99.6%, 83.1%, and 99.9%, respectively. For PET/MRI alone, the metrics were 1.1%, 54.1%, 99.6%, 73.3%, and 99.1%, respectively, and for PET/MRI in non-lung cancers, the metrics were 0.9%, 93.1%, 99.6%, 69.2%, and 99.9%, respectively.

CONCLUSIONS

[18F]FDG PET/MRI holds great promise for the early detection of non-lung cancers, while it seems insufficient for detecting early-stage lung cancers. Chest HRCT can be complementary to whole-body PET/MRI for early cancer detection.

TRIAL REGISTRATION

ChiCTR2200060041. Registered 16 May 2022. Public site: https://www.chictr.org.cn/index.html.

Deep Learning Reconstruction to Improve the Quality of MR Imaging: Evaluating the Best Sequence for T-category Assessment in Non-small Cell Lung Cancer Patients

PURPOSE

Deep learning reconstruction (DLR) has been recommended as useful for improving image quality. Moreover, compressed sensing (CS) or DLR has been proposed as useful for improving temporal resolution and image quality on MR sequences in different body fields. However, there have been no reports regarding the utility of DLR for image quality and T-factor assessment improvements on T2-weighted imaging (T2WI), short inversion time (TI) inversion recovery (STIR) imaging, and unenhanced- and contrast-enhanced (CE) 3D fast spoiled gradient echo (GRE) imaging with and without CS in comparison with thin-section multidetector-row CT (MDCT) for non-small cell lung cancer (NSCLC) patients. The purpose of this study was to determine the utility of DLR for improving image quality and the appropriate sequence for T-category assessment for NSCLC patients.

METHODS

As subjects for this study, 213 pathologically diagnosed NSCLC patients who underwent thin-section MDCT and MR imaging as well as T-factor diagnosis were retrospectively enrolled. SNR of each tumor was calculated and compared by paired t-test for each sequence with and without DLR. T-factor for each patient was assessed with thin-section MDCT and all MR sequences, and the accuracy for T-factor diagnosis was compared among all sequences and thin-section CT by means of McNemar's test.

RESULTS

SNRs of T2WI, STIR imaging, unenhanced thin-section Quick 3D imaging, and CE-thin-section Quick 3D imaging with DLR were significantly higher than SNRs of those without DLR (P < 0.05). Diagnostic accuracy of STIR imaging and CE-thick- or thin-section Quick 3D imaging was significantly higher than that of thin-section CT, T2WI, and unenhanced thick- or thin-section Quick 3D imaging (P < 0.05).

CONCLUSION

DLR is thus considered useful for image quality improvement on MR imaging. STIR imaging and CE-Quick 3D imaging with or without CS were validated as appropriate MR sequences for T-factor evaluation in NSCLC patients.

Theranostic applications of selenium nanomedicines against lung cancer

The incidence and mortality rates of lung cancer are among the highest in the world. Traditional treatment methods include surgery, chemotherapy, and radiotherapy. Although rapid progress has been achieved in the past decade, treatment limitations remain. It is therefore imperative to identify safer and more effective therapeutic methods, and research is currently being conducted to identify more efficient and less harmful drugs. In recent years, the discovery of antitumor drugs based on the essential trace element selenium (Se) has provided good prospects for lung cancer treatments. In particular, compared to inorganic Se (Inorg-Se) and organic Se (Org-Se), Se nanomedicine (Se nanoparticles; SeNPs) shows much higher bioavailability and antioxidant activity and lower toxicity. SeNPs can also be used as a drug delivery carrier to better regulate protein and DNA biosynthesis and protein kinase C activity, thus playing a role in inhibiting cancer cell proliferation. SeNPs can also effectively activate antigen-presenting cells to stimulate cell immunity, exert regulatory effects on innate and regulatory immunity, and enhance lung cancer immunotherapy. This review summarizes the application of Se-based species and materials in lung cancer diagnosis, including fluorescence, MR, CT, photoacoustic imaging and other diagnostic methods, as well as treatments, including direct killing, radiosensitization, chemotherapeutic sensitization, photothermodynamics, and enhanced immunotherapy. In addition, the application prospects and challenges of Se-based drugs in lung cancer are examined, as well as their forecasted future clinical applications and sustainable development.

Detection of solid and subsolid pulmonary nodules with lung MRI: performance of UTE, T1 gradient-echo, and single-shot T2 fast spin echo

BACKGROUND

Although MRI is a radiation-free imaging modality, it has historically been limited in lung imaging due to inherent technical restrictions. The aim of this study is to explore the performance of lung MRI in detecting solid and subsolid pulmonary nodules using T1 gradient-echo (GRE) (VIBE, Volumetric interpolated breath-hold examination), ultrashort time echo (UTE) and T2 Fast Spin Echo (HASTE, Half fourier Single-shot Turbo spin-Echo).

METHODS

Patients underwent a lung MRI in a 3 T scanner as part of a prospective research project. A baseline Chest CT was obtained as part of their standard of care. Nodules were identified and measured on the baseline CT and categorized according to their density (solid and subsolid) and size (> 4 mm/ ≤ 4 mm). Nodules seen on the baseline CT were classified as present or absent on the different MRI sequences by two thoracic radiologists independently. Interobserver agreement was determined using the simple Kappa coefficient. Paired differences were compared using nonparametric Mann-Whitney U tests. The McNemar test was used to evaluate paired differences in nodule detection between MRI sequences.

RESULTS

Thirty-six patients were prospectively enrolled. One hundred forty-nine nodules (100 solid/49 subsolid) with mean size 10.8 mm (SD = 9.4) were included in the analysis. There was substantial interobserver agreement (k = 0.7, p = 0.05). Detection for all nodules, solid and subsolid nodules was respectively; UTE: 71.8%/71.0%/73.5%; VIBE: 61.6%/65%/55.1%; HASTE 72.4%/72.2%/72.7%. Detection rate was higher for nodules > 4 mm in all groups: UTE 90.2%/93.4%/85.4%, VIBE 78.4%/88.5%/63.4%, HASTE 89.4%/93.8%/83.8%. Detection of lesions ≤4 mm was low for all sequences. UTE and HASTE performed significantly better than VIBE for detection of all nodules and subsolid nodules (diff = 18.4 and 17.6%, p = < 0.01 and p = 0.03, respectively). There was no significant difference between UTE and HASTE. There were no significant differences amongst MRI sequences for solid nodules.

CONCLUSIONS

Lung MRI shows adequate performance for the detection of solid and subsolid pulmonary nodules larger than 4 mm and can serve as a promising radiation-free alternative to CT.

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.

18F-FDG PET/MRI in Detection of Pulmonary Malignancies: A Systematic Review and Meta-Analysis

Background There have been conflicting results regarding fluorine 18-labeled fluorodeoxyglucose (¹⁸F-FDG) PET/MRI diagnostic performance in lung malignant neoplasms. Purpose To evaluate the diagnostic performance of ¹⁸F-FDG PET/MRI for the detection of pulmonary malignant neoplasms. Materials and Methods A systematic search was conducted within the Scopus, Web of Science, and PubMed databases until December 31, 2021. Published original articles that met the following criteria were considered eligible for meta-analysis: (a) detecting malignant lesions in the lung, (b) comparing ¹⁸F-FDG PET/MRI with a valid reference standard, and (c) providing data for the meta-analytic calculations. A hierarchical method was used to pool the performances. The bivariate model was used to find the summary points and 95% CIs. The hierarchical summary receiver operating characteristic model was used to draw the summary receiver operating characteristic curve and calculate the area under the curve. The Higgins I² statistic and Cochran Q test were used for heterogeneity assessment. Results A total of 43 studies involving 1278 patients met the inclusion criteria and were included in the meta-analysis. ¹⁸F-FDG PET/MRI had a pooled sensitivity and specificity of 96% (95% CI: 84, 99) and 100% (95% CI: 98, 100), respectively. ¹⁸F-FDG PET/CT had a pooled sensitivity and specificity of 99% (95% CI: 61, 100) and 99% (95% CI: 94, 100), respectively, which were comparable with those of ¹⁸F-FDG PET/MRI. At meta-regression, studies in which contrast media (P = .03) and diffusion-weighted imaging (P = .04) were used as a part of a pulmonary ¹⁸F-FDG PET/MRI protocol showed significantly higher sensitivities. Conclusion Fluorine 18-labeled fluorodeoxyglucose (¹⁸F-FDG) PET/MRI was found to be accurate and comparable with ¹⁸F-FDG PET/CT in the detection of malignant pulmonary lesions, with significantly improved sensitivity when advanced acquisition protocols were used. © RSNA, 2023 Supplemental material is available for this article.

Pulmonary MRI Radiomics and Machine Learning: Effect of Intralesional Heterogeneity on Classification of Lesion

RATIONALE AND OBJECTIVES

To investigate the effect of intralesional heterogeneity on differentiating benign and malignant pulmonary lesions, quantitative magnetic resonance imaging (MRI) radiomics, and machine learning methods were adopted.

MATERIALS AND METHODS

A total of 176 patients with multiparametric MRI were involved in this exploratory study. To investigate the effect of intralesional heterogeneity on lesion classification, a radiomics model called tumor heterogeneity model was developed and compared to the conventional radiomics model based on the entire tumor. In tumor heterogeneity model, each lesion was divided into five sublesions depending on the spatial location through clustering algorithm. From the five sublesions in multi-parametric MRI sequences, 1100 radiomics features were extracted. The recursive feature elimination method was employed to select features and support vector machine classifier was used to distinguish benign and malignant lesion. The performance of classification was evaluated with the receiver operating characteristic curve and the area under the curve (AUC) was the figure of merit. The 3-fold cross-validation (CV) with and without nesting was used to validate the model, respectively.

RESULTS

The tumor heterogeneity model (AUC = 0.74 ± 0.04 and 0.90 ± 0.03, CV with and without nesting, respectively) outperforms conventional model (AUC = 0.68 ± 0.04 and 0.87 ± 0.03). The difference between the two models is statistically significant (p = 0.03) for lesions greater than 18.80 cm³.

CONCLUSION

Intralesional heterogeneity influences the classification of pulmonary lesions. The tumor heterogeneity model tends to perform better than conventional radiomics model.

Efficacy of Ultrashort Echo Time Pulmonary MRI for Lung Nodule Detection and Lung-RADS Classification

Background Pulmonary MRI with ultrashort echo time (UTE) has been compared with chest CT for nodule detection and classification. However, direct comparisons of these methods' capabilities for Lung CT Screening Reporting and Data System (Lung-RADS) evaluation remain lacking. Purpose To compare the capabilities of pulmonary MRI with UTE with those of standard- or low-dose thin-section CT for Lung-RADS classification. Materials and Methods In this prospective study, standard- and low-dose chest CT (270 mA and 60 mA, respectively) and MRI with UTE were used to examine consecutive participants enrolled between January 2017 and December 2020 who met American College of Radiology Appropriateness Criteria for lung cancer screening with low-dose CT. Probability of nodule presence was assessed for all methods with a five-point visual scoring system by two board-certified radiologists. All nodules were then evaluated in terms of their Lung-RADS classification using each method. To compare nodule detection capability of the three methods, consensus for performances was rated by using jackknife free-response receiver operating characteristic analysis, and sensitivity was compared by means of the McNemar test. In addition, weighted κ statistics were used to determine the agreement between Lung-RADS classification obtained with each method and the reference standard generated from standard-dose CT evaluated by two radiologists who were not included in the image analysis session. Results A total of 205 participants (mean age: 64 years ± 7 [standard deviation], 106 men) with 1073 nodules were enrolled. Figure of merit (FOM) (P < .001) had significant differences among three modalities (standard-dose CT: FOM = 0.91, low-dose CT: FOM = 0.89, pulmonary MRI with UTE: FOM = 0.94), with no evidence of false-positive findings in participants with all modalities (P > .05). Agreements for Lung-RADS classification between all modalities and the reference standard were almost perfect (standard-dose CT: κ = 0.82, P < .001; low-dose CT: κ = 0.82, P < .001; pulmonary MRI with UTE: κ = 0.82, P < .001). Conclusion In a lung cancer screening population, ultrashort echo time pulmonary MRI was comparable to standard- or low-dose CT for Lung CT Screening Reporting and Data System classification. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Wielpütz in this issue.

Local Therapies and Modulation of Tumor Surrounding Stroma in Malignant Pleural Mesothelioma: A Translational Approach

Malignant Pleural Mesothelioma (MPM) is a rare and aggressive neoplasm of the pleural mesothelium, mainly associated with asbestos exposure and still lacking effective therapies. Modern targeted biological strategies that have revolutionized the therapy of other solid tumors have not had success so far in the MPM. Combination immunotherapy might achieve better results over chemotherapy alone, but there is still a need for more effective therapeutic approaches. Based on the peculiar disease features of MPM, several strategies for local therapeutic delivery have been developed over the past years. The common rationale of these approaches is: (i) to reduce the risk of drug inactivation before reaching the target tumor cells; (ii) to increase the concentration of active drugs in the tumor micro-environment and their bioavailability; (iii) to reduce toxic effects on normal, non-transformed cells, because of much lower drug doses than those used for systemic chemotherapy. The complex interactions between drugs and the local immune-inflammatory micro-environment modulate the subsequent clinical response. In this perspective, the main interest is currently addressed to the development of local drug delivery platforms, both cell therapy and engineered nanotools. We here propose a review aimed at deep investigation of the biologic effects of the current local therapies for MPM, including cell therapies, and the mechanisms of interaction with the tumor micro-environment.

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.

Canadian Society of Thoracic Radiology/Canadian Association of Radiologists Clinical Practice Guidance for Non-Vascular Thoracic MRI

Historically thoracic MRI has been limited by the lower proton density of lung parenchyma, cardiac and respiratory motion artifacts and long acquisition times. Recent technological advancements in MR hardware systems and improvement in MR pulse sequences have helped overcome these limitations and expand clinical opportunities for non-vascular thoracic MRI. Non-vascular thoracic MRI has been established as a problem-solving imaging modality for characterization of thymic, mediastinal, pleural chest wall and superior sulcus tumors and for detection of endometriosis. It is increasingly recognized as a powerful imaging tool for detection and characterization of lung nodules and for assessment of lung cancer staging. The lack of ionizing radiation makes thoracic MRI an invaluable imaging modality for young patients, pregnancy and for frequent serial follow-up imaging. Lack of familiarity and exposure to non-vascular thoracic MRI and lack of consistency in existing MRI protocols have called for clinical practice guidance. The purpose of this guide, which was developed by the Canadian Society of Thoracic Radiology and endorsed by the Canadian Association of Radiologists, is to familiarize radiologists, other interested clinicians and MR technologists with common and less common clinical indications for non-vascular thoracic MRI, discuss the fundamental imaging findings and focus on basic and more advanced MRI sequences tailored to specific clinical questions.

Evaluating Heterogeneity of Primary Lung Tumor Using Clinical Routine Magnetic Resonance Imaging and a Tumor Heterogeneity Index

Objective

To improve the assessment of primary tumor heterogeneity in magnetic resonance imaging (MRI) of non-small cell lung cancer (NSCLC), we proposed a method using basic measurements from T1- and T2-weighted MRI.

Methods

One hundred and four NSCLC patients with different T stages were studied. Fifty-two patients were analyzed as training group and another 52 as testing group. The ratios of standard deviation (SD)/mean signal value of primary tumor from T1-weighted (T1WI), T1-enhanced (T1C), T2-weighted (T2WI), and T2 fat suppression (T2fs) images were calculated. In the training group, correlation analyses were performed between the ratios and T stages. Then an ordinal regression model was built to generate the tumor heterogeneous index (THI) for evaluating the heterogeneity of tumor. The model was validated in the testing group.

Results

There were 11, 32, 40, and 21 patients with T1, T2, T3, and T4 disease, respectively. In the training group, the median SD/mean on T1WI, T1C, T2WI, and T2fs sequences was 0.11, 0.19, 0.16, and 0.15 respectively. The SD/mean on T1C (p=0.003), T2WI (p=0.000), and T2fs sequences (p=0.002) correlated significantly with T stages. Patients with more advanced T stage showed higher SD/mean on T2-weighted, T2fs, and T1C sequences. The median THI in the training group was 2.15. THI correlated with T stage significantly (p=0.000). In the testing group, THI was also significantly related to T stages (p=0.001). Higher THI had relevance to more advanced T stage.

Conclusions

The proposed ratio measurements and THI based on MRI can serve as functional radiomic markers that correlated with T stages for evaluating heterogeneity of lung tumors.

Measurement Variability in Treatment Response Determination for Non-Small Cell Lung Cancer: Improvements Using Radiomics

Multimodality imaging measurements of treatment response are critical for clinical practice, oncology trials, and the evaluation of new treatment modalities. The current standard for determining treatment response in non-small cell lung cancer (NSCLC) is based on tumor size using the RECIST criteria. Molecular targeted agents and immunotherapies often cause morphological change without reduction of tumor size. Therefore, it is difficult to evaluate therapeutic response by conventional methods. Radiomics is the study of cancer imaging features that are extracted using machine learning and other semantic features. This method can provide comprehensive information on tumor phenotypes and can be used to assess therapeutic response in this new age of immunotherapy. Delta radiomics, which evaluates the longitudinal changes in radiomics features, shows potential in gauging treatment response in NSCLC. It is well known that quantitative measurement methods may be subject to substantial variability due to differences in technical factors and require standardization. In this review, we describe measurement variability in the evaluation of NSCLC and the emerging role of radiomics.

Management of incidental pulmonary nodules: current strategies and future perspectives

Introduction: Detection and characterization of pulmonary nodules is an important issue, because the process is the first step in the management of lung cancers.Areas covered: Literature review was performed on May 15 2019 by using the PubMed, US National Library of Medicine National Institutes of Health, and the National Center for Biotechnology information. CT features helping identify the druggable mutations and predict the prognosis of malignant nodules were presented. Technical advancements in MRI and PET/CT were introduced for providing functional information about malignant nodules. Advances in various tissue biopsy techniques enabling molecular analysis and histologic diagnosis of indeterminate nodules were also presented. New techniques such as radiomics, deep learning (DL) technology, and artificial intelligence showing promise in differentiating between malignant and benign nodules were summarized. Recently, updated management guidelines for solid and subsolid nodules incidentally detected on CT were described. Risk stratification and prediction models for indeterminate nodules under active investigation were briefly summarized.Expert opinion: Advancement in CT knowledge has led to a better correlation between CT features and genomic alterations or tumor histology. Recent advances like PET/CT, MRI, radiomics, and DL-based approach have shown promising results in the characterization and prognostication of pulmonary nodules.

Role of advanced magnetic resonance imaging in the assessment of malignancies of the mediastinum

In the new era of functional magnetic resonance imaging (MRI), the utility of chest MRI is increasing exponentially due to several advances, including absence of ionizing radiation, excellent tissue contrast and high capability for lesion characterization and treatment monitoring. The application of several of these diagnostic weapons in a multiparametric fashion enables to better characterize thymic epithelial tumors and other mediastinal tumoral lesions, accurate assessment of the invasion of adjacent structures and detection of pathologic lymph nodes and metastasis. Also, “do not touch lesions” could be identified with the associated impact in the management of those patients. One of the hot-spots of the multiparametric chest MR is its ability to detect with acuity early response to treatment in patients with mediastinal malignant neoplasms. This has been related with higher rates of overall survival and progression free survival. Therefore, in this review we will analyze the current functional imaging techniques available (¹⁸F-Fluorodeoxiglucose positron emission tomography/computed tomography, diffusion-weighted imaging, dynamic contrast-enhanced MRI, diffusion tensor imaging and MR spectroscopy) for the evaluation of mediastinal lesions, with a focus in their correct acquisition and post-processing. Also, to review the clinical applications of these techniques in the diagnostic approach of benign and malignant conditions of the mediastinum.

MR Volumetry of Lung Nodules: A Pilot Study

Introduction: Computed tomography (CT) is currently the reference modality for the detection and follow-up of pulmonary nodules. While 2D measurements are commonly used in clinical practice to assess growth, increasingly 3D volume measurements are being recommended. The goal of this pilot study was to evaluate preliminarily the capabilities of 3D MRI using ultra-short echo time for lung nodule volumetry, as it would provide a radiation-free modality for this task. Material and Methods: Artificial nodules were manufactured out of Agar and measured using an ultra-short echo time MRI sequence. CT data were also acquired as a reference. Image segmentation was carried out using an algorithm based on signal intensity thresholding (SIT). For comparison purposes, we also performed manual slice by slice segmentation. Volumes obtained with MRI and CT were compared. Finally, the volumetry of a lung nodule was evaluated in one human subject in comparison with CT. Results: Using the SIT technique, minimal bias was observed between CT and MRI across the entire range of volumes (2%) with limits of agreement below 14%. Comparison of manually segmented MRI and CT resulted in a larger bias (8%) and wider limits of agreement (-23% to 40%). In vivo, nodule volume differed of <16% between modalities with the SIT technique. Conclusion: This pilot study showed very good concordance between CT and UTE-MRI to quantify lung nodule volumes, in both a phantom and human setting. Our results enhance the potential of MRI to quantify pulmonary nodule volume with similar performance to CT.

Can MRI contribute to pulmonary nodule analysis?

BACKGROUND

There is no accurate method distinguishing different types of pulmonary nodules.

PURPOSE

To investigate whether multiparametric 3T MRI biomarkers can distinguish malignant from benign pulmonary nodules, differentiate different types of neoplasms, and compare MRI-derived measurements with values from commonly used noninvasive imaging modalities.

STUDY TYPE

Prospective.

SUBJECTS

Sixty-eight adults with pulmonary nodules undergoing resection.

SEQUENCES

Respiratory triggered diffusion-weighted imaging (DWI), periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) fat saturated T₂ -weighted imaging, T₁ -weighted 3D volumetric interpolated breath-hold examination (VIBE) using CAIPIRINHA (controlled aliasing in parallel imaging results in a higher acceleration).

ASSESSMENT/STATISTICS

Apparent diffusion coefficient (ADC), T₁ , T₂ , T₁ and T₂ normalized to muscle (T₁ /M and T₂ /M), and dynamic contrast enhancement (DCE) values were compared with histology to determine whether they could distinguish malignant from benign nodules and discern primary from secondary malignancies using logistic regression. Predictability of primary neoplasm types was assessed using two-sample t-tests. MRI values were compared with positron emission tomography / computed tomography (PET/CT) to examine if they correlated with standardized uptake value (SUV) or CT Hounsfield unit (HU). Intra- and interreader agreements were assessed using intraclass correlations.

RESULTS

Forty-nine of 74 nodules were malignant. There was a significant association between ADC and malignancy (odds ratio 4.47, P < 0.05). ADC ≥1.3 μm² /ms predicted malignancy. ADC, T₁ , and T₂ together predicted malignancy (P = 0.003). No MRI parameter distinguished primary from metastatic neoplasms. T₂ predicted PET positivity (P = 0.016). T₂ and T₁ /M correlated with SUV (P < 0.05). Of 18 PET-negative malignant nodules, 12 (67%) had an ADC ≥1.3 μm² /ms. With the exception of T₂ , all noncontrast MRI parameters distinguished adenocarcinomas from carcinoid tumors (P < 0.05). T₁ , T₂ , T₁ /M, and T₂ /M correlated with HU and therefore can predict nodule density. Combined with ADC, washout enhancement, arrival time (AT), peak enhancement intensity (PEI), K^trans , K_ep , V_e collectively were predictive of malignancy (P = 0.012). Combined washin, washout, time to peak (TTP), AT, and PEI values predicted malignancy (P = 0.043). There was good observer agreement for most noncontrast MRI biomarkers.

DATA CONCLUSION

MRI can contribute to pulmonary nodule analysis. Multiparametric MRI might be better than individual MRI biomarkers in pulmonary nodule risk stratification.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018.