Value of diffusion-weighted MR imaging using various parameters for assessment and characterization of solitary pulmonary nodules

Monoexponential, biexponential, stretched exponential and diffusion kurtosis models of diffusion-weighted imaging: a quantitative differentiation of solitary pulmonary lesion

BACKGROUND

Diffusion-weighted imaging (DWI) can be used for quantitative tumor assessment. DWI with different models may show different aspects of tissue characteristics.

OBJECTIVE

To investigate the diagnostic performance of parameters derived from monoexponential, biexponential, stretched exponential magnetic resonance diffusion weighted imaging (DWI) and diffusion kurtosis imaging (DKI) in differentiating benign from malignant solitary pulmonary lesions (SPLs).

METHOD

Forty-four SPL subjects were selected according to the inclusion criteria. All patients underwent conventional and multi‑b DWI sequences. Monoexponential DWI and DKI model were fitted using least square method. Levenberg-Marquardt nonlinear fitting biexponential and stretched exponential DWI. Region of interests (ROIs) were described manually. Parameters between benign and malignant SPLs were compared using independent sample t test or the Mann-Whitney U test. Receiver operating characteristic (ROC) curves analysis was used to investigate the diagnostic performance of different DWI parameters. Correlation between all parameters were evaluated by using Spearman correlation.

RESULT

ADC, ADCslow, α, DDC and Dapp values were significantly lower in malignant SPL than in benign SPL (P < 0.001). Kapp was significantly higher in malignant SPL than in benign SPL (P < 0.001). Among all subjects, ADCslow was significantly lower than ADC (P < 0.05), while DDC and Dapp were significantly higher than ADC (P < 0.05). When observing the ROC curves for distinguishing benign and malignant SPL, the AUC values of ADC, ADCslow, DDC, Dapp, and Kapp were 0.904, 0.815, 0.942, 0.93, and 0.815, respectively. The DDC value has the highest area under ROC curve value. DeLong analysis showed no statistically significant difference in the area under ADC, DDC, and Dapp curves. There were strong correlations among ADC, ADCslow, ADCfast, f, α, DDC, Dapp, and Kapp (P < 0.001).

CONCLUSION

Multi‑b DWI is a promising method for differentiating benign from malignant SPLs with high diagnostic accuracy. In addition, the DDC derived from stretched‑exponential model is the most promising DWI parameter for the differentiation of benign and malignant SPLs.

TRAIL REGISTRATION

This study was a clinical trail study, with study protocol published at ClinicalTrails. Retrospectively registered number ChiCTR2300074258, date of registration 02/08/2023.

Diagnostic accuracy and image quality evaluation of ultrashort echo time MRI in the lungs

This study evaluates the diagnostic accuracy of ultrashort echo time (UTE)-MRI for detecting pulmonary nodules and image quality. A total of 46 patients at our hospital underwent unenhanced computed tomography (CT) and UTE-MRI. The image quality and number of nodules detected using CT were used as the gold standards. Three diagnostic radiologists independently recorded the image quality (visibility and sharpness of normal anatomical structures) of the CT and UTE images and the number of pulmonary nodules detected. The diagnostic accuracy, subjective image quality, and consistency between observations were statistically analyzed. Among 46 patients, 36 (78.2%) had pulmonary nodules on CT images, whereas 10 patients (21.7%) had no pulmonary nodules. A total of 48 lung nodules were detected, 3 of which were ground-glass opacities. UTE-MRI revealed 46 lung nodules. Compared with CT, the sensitivity of all MRI readers for detecting lung lesions was 95.8%, and the 3-observer agreement was nearly perfect (P < .001, Kendall Wa [Kender Harmonious Coefficient] = 0.913). The overall image quality score of the observers was high, ranging from good to excellent, and the consistency of the subjective UTE-MRI image quality was good (Kendall Wa = 0.877, P < .001). For tracheal display, the subsegment of the bronchus was displayed, and the wall of the tube was clearly displayed. The difference in the Wa values between the observers was 0.804 (P < .001), indicating strong consistency. For blood vessels, subsegment blood vessels could also be displayed with clear walls and uniform signals (Kendal Wa = 0.823, P < .001), indicating strong consistency. Compared to CT, UTE-MRI can detect pulmonary nodules with a high detection rate, relatively good image quality, and strong consistency between observers. The development of UTE-MRI can provide a novel imaging method for the detection and follow-up of pulmonary nodules and diagnosis of pneumonia by reducing ionizing radiation.

Cell-free DNA methylation in the clinical management of lung cancer

The clinical use of cell-free DNA (cfDNA) methylation in managing lung cancer depends on its ability to differentiate between malignant and healthy cells, assign methylation changes to specific tissue sources, and elucidate opportunities for targeted therapy. From a technical standpoint, cfDNA methylation analysis is primed as a potential clinical tool for lung cancer screening, early diagnosis, prognostication, and treatment, pending the outcome of elaborate validation studies. Here, we discuss the current state of the art in cfDNA methylation analysis, examine the unique features and limitations of these new methods in a clinical context, propose two models for applying cfDNA methylation data for lung cancer screening, and discuss future research directions.

A Prospective Observational Study of Diagnostic Reliability of Semiquantitative and Quantitative High b-Value Diffusion-Weighted MRI in Distinguishing between Benign and Malignant Lung Lesions at 3 Tesla

Aim  The aim of this study was to evaluate the usefulness of high b-value diffusion-weighted imaging (DWI) to differentiate benign and malignant lung lesions in 3 Tesla magnetic resonance imaging (MRI). Materials and Methods  Thirty-one patients with lung lesions underwent a high b-value (b= 1000 s/mm 2 ) DW MRI in 3 Tesla. Thirty lesions were biopsied, followed by histopathological analysis, and one was serially followed up for 2 years. Statistical analysis was done to calculate the sensitivity, specificity, and accuracy of different DWI parameters in distinguishing benign and malignant lesions. Receiver operating characteristic (ROC) curves were used to determine the cutoff values of different parameters. Results  The qualitative assessment of signal intensity on DWI based on a 5-point rank scale had a mean score of 2.71 ± 0.75 for benign and 3. 75 ± 0.60 for malignant lesions. With a cutoff of 3.5, the sensitivity, specificity, and accuracy were 75, 86, and 77.6%, respectively. The mean ADC min (minimum apparent diffusion coefficient) value of benign and malignant lesions was 1. 49 ± 0.38 × 10-3 mm 2 /s and 1.11 ± 0.20 ×10-3 mm 2 /s, respectively. ROC curve analysis showed a cutoff value of 1.03 × 10-3 mm 2 /s; the sensitivity, specificity, and accuracy were 87.5, 71.4, and 83.3%, respectively. For lesion to spinal cord ratio and lesion to spinal cord ADC ratio with a cutoff value of 1.08 and 1.38, the sensitivity, specificity, and accuracy were 83.3 and 87.5%, 71.4 and 71.4%, and 80.6 and 83.8%, respectively. The exponential ADC showed a low accuracy rate. Conclusion  The semiquantitative and quantitative parameters of high b-value DW 3 Tesla MRI can differentiate benign from malignant lesions with high accuracy and make it a reliable nonionizing modality for characterizing lung lesions.

Diffusion-weighted Imaging of the Chest: A Primer for Radiologists

Diffusion-weighted imaging (DWI) is a fundamental sequence not only in neuroimaging but also in oncologic imaging and has emerging applications for MRI evaluation of the chest. DWI can be used in clinical practice to enhance lesion conspicuity, tissue characterization, and treatment response. While the spatial resolution of DWI is in the order of millimeters, changes in diffusion can be measured on the micrometer scale. As such, DWI sequences can provide important functional information to MRI evaluation of the chest but require careful optimization of acquisition parameters, notably selection of b values, application of parallel imaging, fat saturation, and motion correction techniques. Along with assessment of morphologic and other functional features, evaluation of DWI signal attenuation and apparent diffusion coefficient maps can aid in tissue characterization. DWI is a noninvasive noncontrast acquisition with an inherent quantitative nature and excellent reproducibility. The outstanding contrast-to-noise ratio provided by DWI can be used to improve detection of pulmonary, mediastinal, and pleural lesions, to identify the benign nature of complex cysts, to characterize the solid portions of cystic lesions, and to classify chest lesions as benign or malignant. DWI has several advantages over fluorine 18 (18F)-fluorodeoxyglucose PET/CT in the assessment, TNM staging, and treatment monitoring of lung cancer and other thoracic neoplasms with conventional or more recently developed therapies. © RSNA, 2023 Quiz questions for this article are available in the supplemental material. Supplemental material and the slide presentation from the RSNA Annual Meeting are available for this article.

Suspicious lung lesions for malignancy: the lesion-to-spinal cord signal intensity ratio in T2WI and DWI–MRI versus PET/CT; a prospective pathologic correlated study with accuracy and ROC analyses

Background

The multi-detector computed tomography (MDCT) and tissue biopsy are the gold standards for the evaluation of lung malignancies. However, there is a wide range of pulmonary indeterminate lesions that could mimic lung cancer. Furthermore, the diagnosis of malignancy could be challenging if the lesion is small and early presenting by a part-solid or ground-glass nodule or if surrounded by parenchymal lung reaction with consolidation and atelectasis. The previous literature focused on the role of diffusion-weighted image–magnetic resonance imaging (DWI) and the apparent diffusion coefficient (ADC) mapping in the evaluation of lung malignancy. A novel quantitative T2 assessment is provided and tested in this study. Aim of the work: To evaluate the accuracy of specific non-invasive quantitative magnetic resonance imaging (MRI) parameters in the characterization of suspicious lung lesions and the discrimination between the malignant and benign nature. They included the lesion-to-spinal cord signal intensity ratio in T2-WI and DWI as well as the mean and minimum apparent diffusion coefficient (ADC) values. This is performed using a prospective pathologic correlated study with receiver-operating characteristics (ROC) analysis and comparison with positron emission tomography (PET-CT) accuracy results.

Results

This study was prospectively performed during the period between June/2021 and June/2022. It was conducted on 43 suspicious lung lesions detected by MDCT. MRI and PET/CT examinations were performed for all patients, and the results were compared to the final diagnosis obtained after biopsy and pathological assessment, using the statistical tests of significance and P-value. Cutoff values were automatically calculated, and then, accuracy tests and ROC analyses were performed. Five expert radiologists and a single consulting pulmonologist participated in this study. The inter-rater reliability ranges between good and excellent with the intra-class correlation coefficient (ICC) ranging between 0.85 and 0.94. In T2-WI: The lesion-to-spinal cord signal intensity ratio was higher in the malignant group (1.35 ± 0.29) than in the benign group (0.88 ± 0.40), (P < 0.001). At the estimated cutoff value (> 1), the sensitivity was 96.43%, the specificity was 80.00%, and AUC = 0.86. In b500-DWI: The lesion-to-spinal cord signal intensity ratio was higher in the malignant group (0.70–1.35) than in the benign group (0.20–0.70) (P < 0.001). At the estimated cutoff value (> 0.7), the sensitivity was 71.43%, the specificity was 86.67%, and AUC = 0.86. The mean and minimum ADC values were lower in the malignant group (0.6–1.3 and 0.3–1.1 × 10–3 mm2/s) than the benign group (1–1.6 and 0.7–1.4 × 10–3 mm2/s), (P < 0.01 and < 0.001, respectively). At their estimated cutoff values (≤ 1.2 and ≤ 0.9 × 10–3 mm2/s, respectively), the sensitivity was (71.4 and 85.7%), specificity was (83.3 and 66.7%), respectively, and AUC = 0.77 for both. PET/CT had 96.4% sensitivity, 92.3% specificity, and AUC = 0.94.

Conclusions

PET-CT remains the most specific and sensitive tool for the differentiation between benign and malignant lesions. The lesion-to-cord signal intensity ratios in T2WI and DWI-MRI and to a minor extent the mean and minimum ADC values are also considered good parameters for this differentiation based on their accurate statistical results, particularly if PET/CT was not available or feasible. The study added to the previous literature a novel quantitative T2WI assessment which proved a high sensitivity equal to PET/CT with a lower but a good specificity. The availability, expertise, time factor, and patients' tolerance remain challenging factors for MRI.

Correlation between PD-L1 Expression of Non-Small Cell Lung Cancer and Data from IVIM-DWI Acquired during Magnetic Resonance of the Thorax: Preliminary Results

This study aims to investigate the correlation between intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) parameters in magnetic resonance imaging (MRI) and programmed death-ligand 1 (PD-L1) expression in non-small cell lung cancer (NSCLC). Twenty-one patients diagnosed with stage III NSCLC from April 2021 to April 2022 were included. The tumors were distinguished into two groups: no PD-L1 expression (<1%), and positive PD-L1 expression (≥1%). Conventional MRI and IVIM-DWI sequences were acquired with a 1.5-T system. Both fixed-size ROIs and freehand segmentations of the tumors were evaluated, and the data were analyzed through a software using four different algorithms. The diffusion (D), pseudodiffusion (D*), and perfusion fraction (pf) were obtained. The correlation between IVIM parameters and PD-L1 expression was studied with Pearson correlation coefficient. The Wilcoxon−Mann−Whitney test was used to study IVIM parameter distributions in the two groups. Twelve patients (57%) had PD-L1 ≥1%, and 9 (43%) <1%. There was a statistically significant correlation between D* values and PD-L1 expression in images analyzed with algorithm 0, for fixed-size ROIs (189.2 ± 65.709 µm²/s × 104 in no PD-L1 expression vs. 122.0 ± 31.306 µm²/s × 104 in positive PD-L1 expression, p = 0.008). The values obtained with algorithms 1, 2, and 3 were not significantly different between the groups. The IVIM-DWI MRI parameter D* can reflect PD-L1 expression in NSCLC.

The value of diffusion kurtosis imaging, diffusion weighted imaging and 18F-FDG PET for differentiating benign and malignant solitary pulmonary lesions and predicting pathological grading

Objective

To explore the value of PET/MRI, including diffusion kurtosis imaging (DKI), diffusion weighted imaging (DWI) and positron emission tomography (PET), for distinguishing between benign and malignant solitary pulmonary lesions (SPLs) and predicting the histopathological grading of malignant SPLs.

Material and methods

Chest PET, DKI and DWI scans of 73 patients with SPL were performed by PET/MRI. The apparent diffusion coefficient (ADC), mean diffusivity (MD), mean kurtosis (MK), maximum standard uptake value (SUV_max), metabolic total volume (MTV) and total lesion glycolysis (TLG) were calculated. Student’s t test or the Mann–Whitney U test was used to analyze the differences in parameters between groups. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic efficacy. Logistic regression analysis was used to evaluate independent predictors.

Results

The MK and SUV_max were significantly higher, and the MD and ADC were significantly lower in the malignant group (0.59 ± 0.13, 10.25 ± 4.20, 2.27 ± 0.51[×10^-3 mm²/s] and 1.35 ± 0.33 [×10^-3 mm²/s]) compared to the benign group (0.47 ± 0.08, 5.49 ± 4.05, 2.85 ± 0.60 [×10^-3 mm²/s] and 1.67 ± 0.33 [×10^-3 mm²/s]). The MD and ADC were significantly lower, and the MTV and TLG were significantly higher in the high-grade malignant SPLs group (2.11 ± 0.51 [×10^-3 mm²/s], 1.35 ± 0.33 [×10^-3 mm²/s], 35.87 ± 42.24 and 119.58 ± 163.65) than in the non-high-grade malignant SPLs group (2.46 ± 0.46 [×10^-3 mm²/s], 1.67 ± 0.33[×10^-3 mm²/s], 20.17 ± 32.34 and 114.20 ± 178.68). In the identification of benign and malignant SPLs, the SUV_max and MK were independent predictors, the AUCs of the combination of SUV_max and MK, SUV_max, MK, MD, and ADC were 0.875, 0.787, 0.848, 0.769, and 0.822, respectively. In the identification of high-grade and non-high-grade malignant SPLs, the AUCs of MD, ADC, MTV, and TLG were 0.729, 0.680, 0.693, and 0.711, respectively.

Conclusion

DWI, DKI, and PET in PET/MRI are all effective methods to distinguish benign from malignant SPLs, and are also helpful in evaluating the pathological grading of malignant SPLs.

Value of IVIM in Differential Diagnoses between Benign and Malignant Solitary Lung Nodules and Masses: A Meta-analysis

Purpose

This study aims to evaluate the accuracy of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) in distinguishing malignant and benign solitary pulmonary nodules and masses.

Methods

Studies investigating the diagnostic accuracy of IVIM-DWI in lung lesions published through December 2020 were searched. The standardized mean differences (SMDs) of the apparent diffusion coefficient (ADC), tissue diffusivity (D), pseudo-diffusivity (D*), and perfusion fraction (f) were calculated. The sensitivity, specificity, area under the curve (AUC), publication bias, and heterogeneity were then summarized, and the source of heterogeneity and the reliability of combined results were explored by meta-regression and sensitivity analysis.

Results

A total of 16 studies including 714 malignant and 355 benign lesions were included. Significantly lower ADC, D, and f values were found in malignant pulmonary lesions compared to those in benign lesions. The D value showed the best diagnostic performance (sensitivity = 0.90, specificity = 0.71, AUC = 0.91), followed by ADC (sensitivity = 0.84, specificity = 0.75, AUC = 0.88), f (sensitivity = 0.70, specificity = 0.62, AUC = 0.71), and D^* (sensitivity = 0.67, specificity = 0.61, AUC = 0.67). There was an inconspicuous publication bias in ADC, D, D* and f values, moderate heterogeneity in ADC, and high heterogeneity in D, D*, and f values. Subgroup analysis suggested that both ADC and D values had a significant higher sensitivity in “nodules or masses” than that in “nodules.”

Conclusions

The parameters derived from IVIM-DWI, especially the D value, could further improve the differential diagnosis between malignant and benign solitary pulmonary nodules and masses.

Systematic Review Registration:https://www.crd.york.ac.uk/PROSPERO/#myprospero, identifier: CRD42021226664

Volumetric analysis of intravoxel incoherent motion diffusion-weighted imaging in preoperative assessment of non-small cell lung cancer

PURPOSE

To evaluate the potential of intravoxel incoherent motion (IVIM) and apparent diffusion coefficient (ADC) in the prediction of tumor grade, lymph node metastasis and pleural invasion of non-small cell lung cancer (NSCLC) before surgery.

MATERIALS AND METHODS

65 patients diagnosed with NSCLC by surgery were enrolled. IVIM-DWI (10 b-values, 0-1000 s/mm²) was performed before surgery. The mean and minimum ADC (ADC_mean, ADC_min) and IVIM parameters D, D* and f were independently measured and calculated by 2 radiologists by drawing regions of interest (ROIs) including the solid component of the whole tumor. Intraclass correlation coefficients (ICCs) were analysed. Spearman analysis was used to determine the correlation between IVIM parameters and tumor differentiation. Independent sample t-tests (normal distribution) or Mann-Whitney U tests (non-normal distribution) were used to compare the differences between the parameters in moderately-well and poorly differentiated groups, with and without lymph node metastasis and pleural invasion groups. Receiver operating characteristic (ROC) curves were generated.

RESULTS

The ADC_mean, ADC_min, D and f values were negatively correlated with the pathological grades of tumor (P < 0.05). The ADC_mean and D values of patients with poor differentiation and lymph node metastasis were significantly lower than that of patients with moderately-well differentiation and without lymph node metastasis (P < 0.001-0.012). The D value was significantly lower and f value was significantly higher among patients with pleural invasion than those without (P =   0.033 and < 0.001). ROC analysis showed that the area under the ROC curve (AUC) was larger for D in predicting the degree of differentiation (0.832) and lymph node metastasis (0.806), and higher for f in predicting pleural invasion (0.832).

CONCLUSIONS

IVIM is useful for predicting the tumor differentiation, lymph node metastasis and pleural invasion in NSCLC patients before surgery.

Values of Apparent Diffusion Coefficient and Lesion-to-Spinal Cord Signal Intensity in Diagnosing Solitary Pulmonary Lesions: Turbo Spin-Echo versus Echo-Planar Imaging Diffusion-Weighted Imaging

Objective

This study is aimed at comparing the image quality and diagnostic performance of mean apparent diffusion coefficient (ADC) and lesion-to-spinal cord signal intensity ratio (LSR) derived from turbo spin-echo diffusion-weighted imaging (TSE-DWI) and echo-planar imaging- (EPI-) DWI in patients with a solitary pulmonary lesion (SPL).

Methods

33 patients with SPL underwent chest imaging using EPI-DWI and TSE-DWI with b = 600 s/mm² in free breathing. A comparison of the distortion ratio (DR), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) was drawn between the two techniques using a Wilcoxon signed-rank test. The interprotocol reproducibility between quantitative parameters of EPI-DWI and TSE-DWI was evaluated using a Bland-Altman plot. ADCs and LSRs derived from EPI-DWI and TSE-DWI were calculated and compared between malignant and benign groups using the Mann-Whitney test.

Results

TSE-DWI had similar SNR and CNR compared with EPI-DWI. DR was significantly lower on TSE-DWI than EPI-DWI. ADC and LSR showed slightly higher values with TSE-DWI, while the Bland-Altman analysis showed unacceptable limits of agreement between the two sequences. ADC and LSR of both DWI techniques differed significantly between lung cancer and benign lesions (P < 0.05). The LSR_(EPI-DWI) showed the highest area under the curve (AUC = 0.818), followed by ADC_(EPI-DWI) (AUC = 0.789), ADC_(TSE-DWI) (AUC = 0.781), and LSR_(TSE-DWI) (AUC = 0.748), respectively. Among these parameters, the difference in diagnostic accuracy was not statistically significant.

Conclusions

TSE-DWI provides significantly improved image quality in patients with SPL as compared with EPI-DWI. However, there was no difference in diagnostic efficacy between these two techniques, according to ADC and LSR.

Value of radiomics model based on multi-parametric magnetic resonance imaging in predicting epidermal growth factor receptor mutation status in patients with lung adenocarcinoma

Background

The epidermal growth factor receptor (EGFR) is an important therapeutic target for patients with non-small-cell lung cancer (NSCLC). Radiomics and radiogenomics have emerged as attractive research topics aiming to extract mineable high-dimensional features from medical images and show potential to correlate with the gene mutation. Herein, we aim to develop a magnetic resonance imaging (MRI)-based radiomics model for pretreatment prediction of the EGFR status in patients with lung adenocarcinoma.

Methods

A total of 92 patients with pathologically confirmed lung adenocarcinoma were retrospectively enrolled in this study. EGFR genotype was analyzed by sequence testing. All patients were randomized into training and test group in a 7:3 ratio using the R software. Radiomics features were extracted from T2 weighted imaging (T2WI), diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC); radiomics signatures were built using the least absolute shrinkage and selection operator (LASSO) and logistic regression. Preoperative clinical factors and image features associated with EGFR were also evaluated. A nomogram including sex, smoking status, and radiomics signatures was constructed. A total of five radiomics models were built, and the area under the curve (AUC) was used to evaluate their performance of EGFR mutation prediction.

Results

Among the three single-sequence models, the ADC model showed the best prediction performance. The AUCs of the ADC, DWI, T2WI prediction model in the test cohort were 0.805 (95% CI: 0.610 to 1.000), 0.722 (95% CI: 0.519 to 0.924), and 0.655 (95% CI: 0.438 to 0.872), respectively. Compared with the single-sequence model, the multi-sequence prediction model showed better performed [AUC_test =0.838 (95% CI: 0.685 to 0.992)]. The AUC of the nomogram in the training group was 0.925 (95% CI: 0.855 to 0.994) and 0.727 (95% CI: 0.531 to 0.924) in the test group, respectively.

Conclusions

The radiomics model based on MRI might have the potential to predict EGFR mutation in patients with lung adenocarcinoma. The multi-sequence model had better performance than other models.

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.

A Noninvasive Assessment of Tumor Proliferation in Lung cancer Patients using Intravoxel Incoherent Motion Magnetic Resonance Imaging

Ki-67 is a nuclear antigen widely used in routine pathologic analyses as a tumor cell proliferation marker for lung cancer. However, Ki-67 expression analyses using immunohistochemistry (IHC) are invasive and frequently influenced by tissue sampling quality. In this study, we assessed the feasibility of noninvasive magnetic resonance imaging (MRI) in predicting the Ki-67 labeling indices (LIs). A total of 51 lung cancer patients, including 42 non-small cell lung cancer (NSCLC) cases and nine small cell lung cancer (SCLC) cases, were enrolled in this study. Quantitative MRI parameters from conventional diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI) were obtained, and their correlations with tumor tissue Ki-67 expression were analyzed. We found that the true diffusion coefficient (D value) from IVIM was negatively correlated with Ki-67 expression (Spearman r = -0.76, P < 0.001). The D values in the high Ki-67 group were significantly lower than those in the low Ki-67 group (0.90 ± 0.21 × 10^-3 mm²/s vs. 1.22 ± 0.30 × 10^-3 mm²/s). Among three MRI techniques used, D values from IVIM showed the best performance for distinguishing the high Ki-67 group from low Ki-67 group in receiver operating characteristic (ROC) analysis with an area under the ROC curve (AUROC) of 0.85 (95% CI: 0.73-0.97, P < 0.05). Moreover, D values performed well for differentiating SCLC from NSCLC with an AUROC of 0.82 (95% CI: 0.68-0.90), Youden index of 0.72, and F1 score of 0.81. In conclusion, D values were negatively correlated with Ki-67 expression in lung cancer tissues and can be used to distinguish high from low proliferation statuses, as well as SCLC from NSCLC.

Differentiating the lung lesions using Intravoxel incoherent motion diffusion-weighted imaging: a meta-analysis

Background and objectives

The diagnostic performance of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) in the differential diagnosis of pulmonary tumors remained debatable among published studies. This study aimed to pool and summary the relevant results to provide more robust evidence in this issue using a meta-analysis method.

Materials and methods

The researches regarding the differential diagnosis of lung lesions using IVIM-DWI were systemically searched in Pubmed, Embase, Web of science and Wangfang database without time limitation. Review Manager 5.3 was used to calculate the standardized mean difference (SMD) and 95% confidence intervals of apparent diffusion coefficient (ADC), tissue diffusivity (D), pseudo-diffusivity (D*), and perfusion fraction (f). Stata 12.0 was used to pool the sensitivity, specificity, and area under the curve (AUC), as well as publication bias and heterogeneity. Fagan’s nomogram was used to predict the post-test probabilities.

Results

Eleven studies with 481 malignant and 258 benign lung lesions were included. Most include studies showed a low to unclear risk of bias and low concerns regarding applicability. Lung cancer demonstrated a significant lower ADC (SMD = -1.17, P < 0.001), D (SMD = -1.02, P < 0.001) and f values (SMD = -0.43, P = 0.005) than benign lesions, except D* value (SMD = 0.01, P = 0.96). D value demonstrated the best diagnostic performance (sensitivity = 89%, specificity = 71%, AUC = 0.90) and highest post-test probability (57, 57, 43 and 43% for D, ADC, f and D* values) in the differential diagnosis of lung tumors, followed by ADC (sensitivity = 85%, specificity = 72%, AUC = 0.86), f (sensitivity = 71%, specificity = 61%, AUC = 0.71) and D* values (sensitivity = 70%, specificity = 60%, AUC = 0.66).

Conclusion

IVIM-DWI parameters show potentially strong diagnostic capabilities in the differential diagnosis of lung tumors based on the tumor cellularity and perfusion characteristics, and D value demonstrated better diagnostic performance compared to mono-exponential ADC.

The value of diffusion-weighted imaging based on monoexponential and biexponential models for the diagnosis of benign and malignant lung nodules and masses

OBJECTIVES

The objective is to compare the efficacy of diffusion-weighted imaging (DWI) parameters of mean and minimum apparent diffusion coefficient (ADCmean and ADCmin) and intravoxel incoherent motion (IVIM) in the differentiation of benign and malignant lung nodules and masses.

METHODS

Lung lesions measured larger than 1.5 cm on CT were included between August 2015 and September 2018. DWI (10 b-values, 0-1000 s/mm2) scans were performed, and the data were post-processed to derive the ADCmean, ADCmin and IVIM parameters of true diffusion coefficient (D), pseudodiffusion coefficient (D*) and perfusion fraction (f). An independent sample t-test or Mann-Whitney U test was used to compare benign and malignant parameters. Receiver operating characteristic curves were generated and a Z test was used.

RESULTS

121 patients were finally enrolled, each with one lesion. Examined 121 lesions were malignant in 88 (72.7%) and benign in 33 (27.3%). The ADCmean of malignant pulmonary nodules was significantly lower than that of benign pulmonary nodules (t = 3.156, p = 0.006), whereas the other parameters revealed no significant differences (p = 0.162-0.690). Receiver operating characteristic curve analysis revealed that an ADCmean threshold value of 1.43 × 10-3 mm2/s yielded 88.57% sensitivity and 64.29% specificity. While for lung masses, the ADCmean, ADCmin, D and D* values in malignant pulmonary masses were significantly lower (P﹤0.001-0.011). Among them, the D value exhibited the best diagnostic performance when the threshold of D was 1.23 × 10-3mm2/s, which yielded a sensitivity of 90.57% and a specificity of 89.47% (Z = 2.230, 3.958, 2.877 and p = 0.026, ﹤0.001 and 0.004, respectively).

CONCLUSION

ADC is the most robust parameter to differentiate benign and malignant lung nodules, whereas D is the most robust parameter to differentiate benign and malignant lung masses.

ADVANCES IN KNOWLEDGE

This is the first study to compare all the quantitative parameters of DWI and IVIM mentioned in the literatures for assessing lung lesions; Second, we divided the lesions into lung nodules and lung masses with the size of 3 cm as the boundary.

A pilot study of native T1-mapping for focal pulmonary lesions in 3.0 T magnetic resonance imaging: size estimation and differential diagnosis

Background

To investigate the accuracy of size estimation and potential diagnosis efficacy of native T1-mapping in focal pulmonary lesion, compared to T1-star 3D-volumetric interpolated breath-hold sequence (VIBE), T2-fBLADE turbo-spin echo (TSE), and computed tomography (CT).

Methods

Thirty-nine patients with CT-detected focal pulmonary lesions underwent thoracic 3.0-T magnetic resonance imaging (MRI) using axial free-breathing 3D T1-star VIBE, respiratory triggered T2-fBLADE TSE, breath-hold T1-Turbo fast low angle shot (FLASH) and T1-FLASH 3D. Native T1-mapping images were generated by T1-FLASH 3D with B1-filed correction by T1-Turbo FLASH. The intraclass correlation coefficient (ICC) and Bland-Altman plots were used to evaluate intra-observer agreement and inter-method reliability of diameter measurements. Native T1-values were measured and compared among the malignancy, tuberculosis, non-tuberculosis benign groups using Mann-Whitney U tests.

Results

Forty-five focal pulmonary lesions were displayed by CT, native T1-mapping, T1-star VIBE, and T2-fBLADE TSE. T1-mapping-based diameter measurements yielded an intra-observer ICC of 0.995. Additionally, inter-method measurements were highly consistent (T1-mapping & T1-star VIBE: ICC 0.982, T1-mapping & T2-fBLADE TSE: ICC 0.978, T1-mapping & CT: ICC 0.972). For lesions <3.00 cm, T1-mapping intra-observer (ICC 0.982) and inter-method diameter measurements were also highly consistent (T1-mapping & CT: ICC 0.823). Native T1-values of malignant tumors were lower than those of the non-tuberculosis benign lesions (P=0.003). Native T1-values of tuberculosis were lower than those of the non-tuberculosis benign lesions (P=0.002). Native T1-values showed no statistically significant differences between malignant tumors and tuberculosis (P=0.059).

Conclusions

Native T1-mapping enable accurate and reliable diameter measurement. Native T1-values potentially differentiate malignant tumors or tuberculosis from non-tuberculosis benign lesions.

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.

Diagnostic performance of diffusion-weighted magnetic resonance imaging in pulmonary malignant lesions: a meta-analysis

Background

Overuse or misuse of positron emission tomography/computed tomography (PET/CT) should be avoided for its ionizing-radiation. Diffusion-weighted magnetic resonance imaging (DW-MRI), characterized by no radiation, may be regarded as an alternative in differentiating pulmonary nodules. We aim to estimate the diagnostic accuracy of DW-MRI in diagnosing of pulmonary lesions.

Methods

Relevant studies were searched through PubMed and Embase with no language restriction from inception to March 8, 2019. We selected studies reporting sensitivity and specificity of DW-MRI for differentiating pulmonary nodules. A summary estimates of sensitivity, specificity and area under curve (AUC) of receiver operating characteristic (ROC) of DW-MRI were analyzed with a random effects model.

Results

We included data from 37 studies, which altogether included 2,311 pulmonary lesions. The pooled sensitivity and specificity were 0.86 (95% CI, 0.82-0.89) and 0.79 (95% CI, 0.72-0.85), and AUC was 0.90 (95% CI, 0.87-0.92). Subsequent subgroup analysis showed the higher sensitivity of DW-MRI in pulmonary lesion >2 cm in comparison to lesions ≤2 cm, however, higher specificity was observed in smaller lesions.

Conclusions

Radiation-free DW-MRI showed a favorable balance between sensitivity and specificity in diagnosing pulmonary malignancies especially in lesion size ≤2 cm. Existing evidence indicated that DW-MRI may be considered as an independent substitute in diagnosis of lung lesions, which might help to prevent long-term side-effects from radiographic diagnosing and evaluating procedures.

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.

MRI in Evaluation of Solitary Pulmonary Nodules

OBJECTIVES

The aim of this study is to assess magnetic resonance imaging (MRI), diffusion-weighted imaging (DWI), T2-weighted image (T2WI), and apparent diffusion coefficient (ADC) maps' threshold values before computed tomography (CT)-guided transthorasic biopsy in solitary pulmonary nodules (SPN) by describing tumoral cell density.

MATERIALS AND METHODS

Patients who had SPN were prospectively evaluated with MRI (T1WI, T2WI) and DWI (b=0, b=500, b=1000).The ADC maps were created for each patient. Before the biopsy, lesion muscle ratios (LMR) at T2WI, ADC value, and lesion spinal cord ratio at each b values were noted. The measurements were correlated with the histopathological results.

RESULTS

A total of 53 patients were included in the study: 30.2% (n=16) were female, and 69.8% (n=37) were male. Among them, 17 lesions (32.1%) were benign, and 36 lesions (67.9%) were malignant. The age varied between 40 and 82 years, with a mean of 61.7±9.1 years. The SPN diameters were between 10 and 30 mm, and the median was 24 mm. The LSR0 and LMR values were not statistically significant in detecting malignancy. LSR500 >0.53 value can predict malignancy with 100% sensitivity and 70.6% specificity. LSR1000 >0.53 can predict malignancy with 88.9% sensitivity and 88.2% specificity. Setting the cut-off value at 0.9×10^-3, the ADC values had a sensitivity of 72.2% and a specificity of 88.2% for predicting malignancy.

CONCLUSION

For SPN follow-up, a new following-up protocol can be safely established using DWI and ADC mapping. Using these MRI parameters might decrease unnecessary biopsy rates and complications of biopsies.

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.

Intravoxel incoherent motion and diffusion kurtosis imaging for discriminating soft tissue sarcoma from vascular anomalies

To investigate the feasibility of intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) and diffusion kurtosis imaging (DKI) in discriminating soft tissue sarcoma from vascular anomalies.Twenty-two patients with lower extremity soft tissue sarcoma and 15 patients with lower extremity vascular anomalies underwent IVIM-DWI and DKI. IVIM model generated true diffusion (D), perfusion fraction (f), and pseudo-diffusion coefficient (D). DKI model generated mean kurtosis (MK) and mean diffusion (MD). These parameters were measured by 2 radiologists separately through drawing region of interest. Intraclass correlation coefficient (ICC) was calculated to evaluate the inter-reader viability in measurement. The Mann-Whitney test was used to compare the parameters between vascular anomalies and soft tissue sarcoma. Receiver operating characteristic curves were constructed for assessing diagnostic accuracies.ICC was more than 0.8 for apparent diffusion coefficient (ADC), D, D, f, MK, and MD. Mean ADC, D, and MD were significantly lower in soft tissue sarcoma versus vascular anomalies (P < .05). Mean D and f were not significantly different (P > .05). Soft tissue sarcoma had significantly higher MK than vascular anomalies (P < .05). Areas under curve for ADC, D, MK, and MD were 0.876, 0.885, 0.894, and 0.812, respectively.IVIM and DKI are feasible in discriminating soft tissue sarcoma from vascular anomalies.

Fluorine 18-FDG PET/CT and Diffusion-weighted MRI for Malignant versus Benign Pulmonary Lesions: A Meta-Analysis

Purpose To perform a meta-analysis of the literature to compare the diagnostic performance of fluorine 18 fluorodeoxyglucose PET/CT and diffusion-weighted (DW) MRI in the differentiation of malignant and benign pulmonary nodules and masses. Materials and Methods Published English-language studies on the diagnostic accuracy of PET/CT and/or DW MRI in the characterization of pulmonary lesions were searched in relevant databases through December 2017. The primary focus was on studies in which joint DW MRI and PET/CT were performed in the entire study population, to reduce interstudy heterogeneity. For DW MRI, lesion-to-spinal cord signal intensity ratio and apparent diffusion coefficient were evaluated; for PET/CT, maximum standard uptake value was evaluated. The pooled sensitivities, specificities, diagnostic odds ratios, and areas under the receiver operating characteristic curve (AUCs) for PET/CT and DW MRI were determined along with 95% confidence intervals (CIs). Results Thirty-seven studies met the inclusion criteria, with a total of 4224 participants and 4463 lesions (3090 malignant lesions [69.2%]). In the primary analysis of joint DW MRI and PET/CT studies (n = 6), DW MRI had a pooled sensitivity and specificity of 83% (95% CI: 75%, 89%) and 91% (95% CI: 80%, 96%), respectively, compared with 78% (95% CI: 70%, 84%) (P = .01 vs DW MRI) and 81% (95% CI: 72%, 88%) (P = .056 vs DW MRI) for PET/CT. DW MRI yielded an AUC of 0.93 (95% CI: 0.90, 0.95), versus 0.86 (95% CI: 0.83, 0.89) for PET/CT (P = .001). The diagnostic odds ratio of DW MRI (50 [95% CI: 19, 132]) was superior to that of PET/CT (15 [95% CI: 7, 32]) (P = .006). Conclusion The diagnostic performance of diffusion-weighted MRI is comparable or superior to that of fluorine 18 fluorodeoxyglucose PET/CT in the differentiation of malignant and benign pulmonary lesions. © RSNA, 2018 Online supplemental material is available for this article. See also the editorial by Schiebler in this issue.

Comparison of Various Parameters of DWI in Distinguishing Solitary Pulmonary Nodules

In order to prospectively assess various parameters of diffusion weighted imaging (DWI) in differential diagnosis of benign and malignant solitary pulmonary nodules (SPNs), 58 patients (40 men and 18 women, and mean age of 48.1±10.4 years old) with SPNs undergoing conventional MR, DWI using b=500 s/mm² on a 1.5T MR scanner, were studied. Various DWI parameters [apparent diffusion coefficient (ADC), lesion-tospinal cord signal intensity ratio (LSR), signal intensity (SI) score] were calculated and compared between malignant and benign SPNs groups. A receiver operating characteristic (ROC) curve analysis was employed to compare the diagnostic capabilities of all the parameters for discrimination between benign and malignant SPNs. The results showed that there were 42 malignant and 16 benign SPNs. The ADC was significantly lower in malignant SPNs (1.40±0.44)×10^-3 mm²/s than in benign SPNs (1.81±0.58)×10^-3 mm²/s. The LSR and SI scores were significantly increased in malignant SPNs (0.90±0.37 and 2.8±1.2) as compared with those in benign SPNs (0.68±0.39 and 2.2±1.2). The area under the ROC curves (AUC) of all parameters was not significantly different between malignant SPNs and benign SPNs. It was suggested that as three reported parameters for DWI, ADC, LSR and SI scores are all feasible for discrimination of malignant and benign SPNs. The three parameters have equal diagnostic performance.

Differentiating between malignant and benign solid solitary pulmonary lesions: are intravoxel incoherent motion and diffusion kurtosis imaging superior to conventional diffusion-weighted imaging?

OBJECTIVE

To quantitatively compare the diagnostic values of various diffusion parameters obtained from mono- and biexponential diffusion-weighted imaging (DWI) models and diffusion kurtosis imaging (DKI) in differentiating between benign and malignant solitary pulmonary lesions (SPLs).

METHODS

Multiple b-value DWIs and DKIs were performed in 89 patients with SPL by using a 3-T magnetic resonance (MR) imaging unit. The apparent diffusion coefficient (ADC) of various b-value sets, true diffusivity (D), pseudo-diffusion coefficient (D*), perfusion fraction (f), apparent diffusional kurtosis (K_app), and kurtosis-corrected diffusion coefficient (D_app) were calculated and compared between the malignant and benign groups using a Mann-Whitney U test. Receiver-operating characteristic analysis was performed for all parameters.

RESULT

The ADC_{(0, 150)} values of malignant tumors were lower than those of the benign group (p = 0.01). The ADC_{(0, 300)}, ADC_{(0, 500)}, ADC_{(0, 600),} ADC_{(0, 800)}, ADC_{(0, 1000),} ADC_total, D, and D_app of malignant tumors were significantly lower than those of benign lesions (all p < 0.001). D*, f, and K_app showed no statistically significant differences between the two groups. ADC_total showed the highest area under the curve (AUC = 0.862), followed by ADC_{(0, 800)}(AUC = 0.844), ADC_{(0, 600)}(AUC = 0.843), D(AUC = 0.834), ADC_{(0, 1000)}(AUC = 0.834) and ADC_{(0, 500)}(AUC = 0.824), D_app(AUC = 0.796), and ADC_{(0, 300)} (AUC = 0.773). However, the difference in diagnostic efficacy among these parameters was not statistically significant (p > 0.05).

CONCLUSION

Intravoxel incoherent motion (IVIM) and DKI-derived parameters have similar performance compared with conventional ADC in differentiating SPLs.

KEY POINTS

• Mono- and biexponential DWI and DKI are feasible for differentiating SPLs. • ADC _{(0, ≥500)} has better performance than ADC _{(0, <500)} in assessing SPLs. • IVIM and DKI have similar performance compared with conventional DWI in differentiating SPLs.

Diffusion-weighted MRI in solitary pulmonary lesions: associations between apparent diffusion coefficient and multiple histopathological parameters

Apparent diffusion coefficient (ADC) from diffusion-weighted imaging (DWI) has gained wide attention as potential tool for differentiating between malignant and benign solitary pulmonary lesions (SPLs). The overall effects of multiple histopathological parameters on ADC have not been elucidated, which may help to explain the overlapping of ADC between malignant and benign SPLs. The study sought to explore associations between ADC and histopathological parameters in SPLs, and to compare diagnostic capability of ADC among different types of SPLs. Multiple histopathological parameters (cell density, nuclear-to-cytoplasm ratio, necrotic fraction, presence of mucus and grade of differentiation) were quantified in 52 malignant and 13 benign SPLs with surgical pathology available. Cell density (β = −0.40) and presence of mucus (β = 0.77) were independently correlated with ADC in malignant SPLs. The accurate diagnosis rate of squamous carcinomas, adenocarcinomas without mucus and malignant tumors with mucus was 100%, 82% and 0%, respectively. Our study suggested that cell density and presence of mucus are independently correlated with ADC in malignant SPLs. Squamous carcinoma maybe more accurately diagnosed as malignancy by ADC value. Malignant SPLs with mucus and adenocarcinomas with low cell density should be kept in mind in differentiating SPLs using ADC because of insufficient diagnostic capability.

Diagnostic performance of 18F-FDG PET/CT and whole-body diffusion-weighted imaging with background body suppression (DWIBS) in detection of lymph node and bone metastases from pediatric neuroblastoma

OBJECTIVE

Recent many studies have shown that whole body "diffusion-weighted imaging with background body signal suppression" (DWIBS) seems a beneficial tool having higher tumor detection sensitivity without ionizing radiation exposure for pediatric tumors. In this study, we evaluated the diagnostic performance of whole body DWIBS and ¹⁸F-FDG PET/CT for detecting lymph node and bone metastases in pediatric patients with neuroblastoma.

METHODS

Subjects in this retrospective study comprised 13 consecutive pediatric patients with neuroblastoma (7 males, 6 females; mean age, 2.9 ± 2.0 years old) who underwent both ¹⁸F-FDG PET/CT and whole-body DWIBS. All patients were diagnosed as neuroblastoma on the basis of pathological findings. Eight regions of lymph nodes and 17 segments of skeletons in all patients were evaluated. The images of ¹²³I-MIBG scintigraphy/SPECT-CT, bone scintigraphy/SPECT, and CT were used to confirm the presence of lymph node and bone metastases. Two radiologists trained in nuclear medicine evaluated independently the uptake of lesions in ¹⁸F-FDG PET/CT and the signal-intensity of lesions in whole-body DWIBS visually. Interobserver difference was overcome through discussion to reach a consensus. The sensitivities, specificities, and overall accuracies of ¹⁸F-FDG PET/CT and whole-body DWIBS were compared using McNemer's test. Positive predictive values (PPVs) and negative predictive values (NPVs) of both modalities were compared using Fisher's exact test.

RESULTS

The total numbers of lymph node regions and bone segments which were confirmed to have metastasis in the total 13 patients were 19 and 75, respectively. The sensitivity, specificity, overall accuracy, PPV, and NPV of ¹⁸F-FDG PET/CT for detecting lymph node metastasis from pediatric neuroblastoma were 100, 98.7, 98.9, 95.0, and 100%, respectively, and those for detecting bone metastasis were 90.7, 73.1, 80.3, 70.1, and 91.9%, respectively. In contrast, the sensitivity, specificity, overall accuracy, PPV, and NPV of whole-body DWIBS for detecting bone metastasis from pediatric neuroblastoma were 94.7, 24.0, 53.0, 46.4 and 86.7%, respectively, whereas those for detecting lymph node metastasis were 94.7, 85.3, 87.2, 62.1, and 98.5%, respectively. The low specificity, overall accuracy, and PPV of whole-body DWIBS for detecting bone metastasis were due to a high incidence of false-positive findings (82/108, 75.9%). The specificity, overall accuracy, and PPV of whole-body DWIBS for detecting lymph node metastasis were also significantly lower than those of ¹⁸F-FDG PET/CT for detecting lymph node metastasis, although the difference between these 2 modalities was less than that for detecting bone metastasis.

CONCLUSION

The specificity, overall accuracy, and PPV of whole-body DWIBS are significantly lower than those of ¹⁸F-FDG PET/CT because of a high incidence of false-positive findings particularly for detecting bone metastasis, whereas whole-body DWIBS shows a similar level of sensitivities for detecting lymph node and bone metastases to those of ¹⁸F-FDG PET/CT. DWIBS should be carefully used for cancer staging in children because of its high incidence of false-positive findings in skeletons.

MRI for solitary pulmonary nodule and mass assessment: Current state of the art

Since the clinical introduction of magnetic resonance imaging (MRI), the chest has been one of its most challenging applications, and many physicists and radiologists have tried since the 1980s to use MR for assessment of different lung diseases as well as mediastinal and pleural diseases. Since then, however, technical advances in sequencing, scanners, and coils, adaptation of parallel imaging techniques, utilization of contrast media, and development of postprocessing tools have been reported by many basic and clinical researchers. As a result, state-of-the-art thoracic MRI is now substituted for traditional imaging techniques and/or plays a complementary role in the management of patients with various chest diseases, and especially in the detection of pulmonary nodules and in thoracic oncology. In addition, MRI has continued to be developed to help overcome the limitations of computed tomography (CT) and nuclear medicine examinations. It can currently provide not only morphological, but also functional, physiological, pathophysiological, and molecular information at 1.5T with a gradual shift from 1.5T to 3T MR systems. In this review, we focus on these recent advances in MRI for pulmonary nodule detection and pulmonary nodule and mass evaluation by using noncontrast-enhanced and contrast-enhanced techniques as well as new molecular imaging methods such as chemical exchange saturation transfer imaging for a comparison with other modalities such as single or multidetector row CT, 18F-fluoro-2-deoxyglucose positron emission tomography (FDG-PET), and/or PET/CT.

LEVEL OF EVIDENCE

4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1437-1458.

3.0T MRI for long-term observation of lung nodules post cryoablation: a pilot study

BACKGROUND

The purpose of this study was to use serial magnetic resonance imaging (MRI) examinations to observe changes in malignant lung tumors over time post-cryoablation.

METHODS

The study protocol was approved by Institutional Review Board, and written informed consent was obtained from each participant in accordance with the Declaration of Helsinki. Patients with primary or metastatic lung tumors eligible for cryoablation were included in this prospective study. Cryoablation was performed according to standard procedures. Unenhanced and dynamic contrast-enhanced MRI scans were performed pre-cryoablation and at 1 day, 1 week, and 3-, 6-, and 12 months after cryoablation. At each time point, the signal intensity of the ablated zone on both T₁WI and T₂WI images, and volume and characteristics of the ablation zone were examined, and changes over time analyzed.

RESULTS

A total of 26 nodules in 23 patients were included in the study. The mean patient age was 53.7 ± 13.6 years, and 57.7% were males. Ablation zone volume increased to 1 week after the procedure, and then returned to baseline by 3 months. Cavitation post-cryoablation was found in 34.6% (9/26) of the nodules 1 month after treatment. Two types of time-signal intensity curves post-cryoablation were found: a straight line representing no definite enhancement from 1-day to 1-month, and an inflow curve representing mild delayed enhancement from month 3 to month 12. Local progression was associated with an incomplete hypointense rim around the ablation zone and absence of cavitation post-treatment.

CONCLUSIONS

Characteristic changes are present on MRI after cryoablation of lung tumors. A complete hypointense rim and cavitation may be signs of adequate treatment and that local tumor progression is less likely.

Volumetric analysis of intravoxel incoherent motion imaging for assessment of solitary pulmonary lesions

Background Differentiating between malignant and benign solitary pulmonary lesions (SPLs) is challenging. Purpose To determine diagnostic performance of intravoxel incoherent motion-based diffusion-weighted imaging (DW-IVIM) in distinguishing malignant from benign SPLs, using histogram analysis derived whole-tumor and single-section region of interest (ROI). Material and Methods This retrospective study received institutional review board approval. A total of 129 patients with diagnosed SPLs underwent DW-IVIM and apparent diffusion coefficient (ADC). ADC, slow diffusion coefficient (D), fast diffusion coefficient (D*), and perfusion fraction (f) were calculated separately by outlining whole-tumor and single-section ROI. Inter-observer reliability was assessed by inter-class correlation coefficient (ICC). ADC and DW-IVIM parameters were analyzed using independent-sample T-test. Receiver operating characteristic (ROC) analysis was constructed to determine diagnostic performance. Multiple logistic regression was performed to identify independent factors associated with malignant SPLs. Results There were 48 benign SPLs found in 35 patients and 94 patients with lung cancer (LC). ICC for whole-tumor ROI (range, 0.89-0.95) was higher than that for single-section ROI (range, 0.61-0.71). Mean ADC and D were significantly lower in the malignant group. ADC and D 10th showed significantly higher AUC values than did mean ADC and D. D showed significantly higher diagnostic accuracy in mean, 10th, and 25th percentiles than ADC values (all Ps < 0.05). D 10th was found to be an independent factor in discriminating LCs with an odds ratio of -1.217. Conclusion Volumetric analysis had higher reproducibility and diagnostic accuracy than did single-section. Further, compared to ADC, D value differentiated benign SPLs from LCs more accurately.

Intravoxel incoherent motion diffusion-weighted MR imaging in assessing and characterizing solitary pulmonary lesions

This study aimed to investigate the potential of intravoxel incoherent motion (IVIM) diffusion-weighted MR imaging in assessing solitary pulmonary lesions (SPLs). Sixty-two patients with pathologically confirmed SPLs, including 51 and 11 cases of malignant and benign lesions, respectively, were assessed. Diffusion weighted imaging (DWI) with 13 b values was used to derive apparent diffusion coefficient (ADC) and IVIM parameters, including true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f). Our results showed that, there was an excellent inter-observer agreement on the measurements of D and ADC between observers (inter-class correlation coefficient, ICC = 0.902 and 0.884, respectively). Meanwhile, f and D* showed good and substantial reproducibility (ICC = 0.787 and 0.623, respectively). D and ADC of malignant lesions were significantly lower than those of benign lesions (both P ≤ 0.001), while similar values were obtained in both groups for D* and f (both P > 0.05). In receiver operating characteristic (ROC) analysis, D showed the highest area under curve (AUC) for distinguishing malignant from benign lesions, followed by ADC. Accompanying signs of SPLs have specific features on IVIM maps. In conclusion, IVIM provides functional information in characterizing SPLs which is helpful to differential diagnosis. D and ADC have a significantly higher diagnostic value than f and D*.

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.

Pulmonary MRI at 3T: Non-enhanced pulmonary magnetic resonance Imaging Characterization Quotients for differentiation of infectious and malignant lesions

OBJECTIVE

To investigate 3T pulmonary magnetic resonance imaging (MRI) for characterization of solid pulmonary lesions in immunocompromised patients and to differentiate infectious from malignant lesions.

MATERIALS AND METHODS

Thirty-eight pulmonary lesions in 29 patients were evaluated. Seventeen patients were immunocompromised (11 infections and 6 lymphomas) and 12 served as controls (4 bacterial pneumonias, 8 solid tumors). Ten of the 15 infections were acute. Signal intensities (SI) were measured in the lesion, chest wall muscle, and subcutaneous fat. Scaled SIs as Non-enhanced Imaging Characterization Quotients ((SI_Lesion-SI_Muscle)/(SI_Fat-SI_Muscle)*100) were calculated from the T2-weighted images using the mean SI (T2-NICQ_mean) or the 90th percentile of SI (T2-NICQ_90th) of the lesion. Simple quotients were calculated by dividing the SI of the lesion by the SI of chest wall muscle (e.g. T1-Q_mean: SI_Lesion/SI_Muscle).

RESULTS

Infectious pulmonary lesions showed a higher T2-NICQ_mean (40.1 [14.6-56.0] vs. 20.9 [2.4-30.1], p<0.05) and T2-NICQ_90th (74.3 [43.8-91.6] vs. 38.5 [15.8-48.1], p<0.01) than malignant lesions. T1-Q_mean was higher in malignant lesions (0.85 [0.68-0.94] vs. 0.93 [0.87-1.09], p<0.05). Considering infections only, T2-NICQ_90th was lower when anti-infectious treatment was administered >24h prior to MRI (81.8 [71.8-97.6] vs. 41.4 [26.6-51.1], p<0.01). Using Youden's index (YI), the optimal cutoff to differentiate infectious from malignant lesions was 43.1 for T2-NICQ_mean (YI=0.42, 0.47 sensitivity, 0.95 specificity) and 55.5 for T2-NICQ_90th (YI=0.61, 0.71 sensitivity, 0.91 specificity). Combining T2-NICQ_90th and T1-Q_mean increased diagnostic performance (YI=0.72, 0.77 sensitivity, 0.95 specificity).

CONCLUSION

Considering each quotient alone, T2-NICQ_90th showed the best diagnostic performance and could allow differentiation of acute infectious from malignant pulmonary lesions with high specificity. Combining T2-NICQ_90th with T1-Q_mean increased overall performance, especially regarding sensitivity.

Non-Gaussian diffusion imaging for malignant and benign pulmonary nodule differentiation: a preliminary study

BACKGROUND

Diffusion-weighted imaging (DWI) derived apparent diffusion coefficient (ADC) has demonstrated inconsistent results in pulmonary nodule differentiation. Diffusion kurtosis imaging (DKI), which quantifies non-Gaussian diffusion, is believed to better characterize tissue micro-structure than conventional DWI.

PURPOSE

To assess the feasibility of DKI in human lungs and to compare its diagnostic value with standard DWI in differentiating malignancies from benign pulmonary nodules.

MATERIAL AND METHODS

Thirty-five pulmonary nodules in 32 consecutive patients were evaluated by DKI by using 3b-values of 0, 500, and 1000 s/mm² and conventional DWI with b values of 0 and 800 s/mm². Two observers independently evaluated and compared diagnostic accuracy of mean kurtosis (MK) and ADC values in differentiating malignancies from benign pulmonary nodules. The intra- and inter-observer repeatability (intra-class correlation coefficient [ICC]) were also assessed for each derived measures.

RESULTS

The diagnostic accuracy, and the area under curve (AUC) in differentiating malignancies from benign pulmonary nodule, were not significantly higher for MK (Obs. 1a: 85.70%, 0.87; Obs. 1b: 80.00%, 0.80; and Obs. 2: 82.80%, 0.91) as compared to ADC (Obs. 1a: 77.14%, 0.81; Obs. 1b: 80.00%, 0.85; and Obs. 2: 77.14%, 0.85 respectively). The intra- and inter-observer agreement (ICC) for malignant and benign lesions was substantial for each reading.

CONCLUSION

The initial results of this study indicate the feasibility of DKI in human lungs. However, there was no significant benefit of DKI derived MK values over ADC for malignant and benign pulmonary nodule differentiation.

Use of diffusion-weighted magnetic resonance imaging to distinguish between lung cancer and focal inflammatory lesions: a comparison of intravoxel incoherent motion derived parameters and apparent diffusion coefficient

Background Using imaging techniques to diagnose malignant and inflammatory lesions in the lung can be challenging. Purpose To compare intravoxel incoherent motion (IVIM) and apparent diffusion coefficient (ADC) magnetic resonance imaging (MRI) analysis in their ability to discriminate lung cancer from focal inflammatory lung lesions. Material and Methods Thirty-eight patients with lung masses were included: 30 lung cancers and eight inflammatory lesions. Patients were imaged with 3.0T MRI diffusion weighted imaging (DWI) using 10 b values (range, 0-1000 s/mm²). Tissue diffusivity ( D), pseudo-diffusion coefficient ( D*), and perfusion fraction ( f) were calculated using segmented biexponential analysis. ADC (total) was calculated with monoexponential fitting of the DWI data. D, D*, f, and ADC were compared between lung cancer and inflammatory lung lesions. Receiver operating characteristic analysis was performed for all DWI parameters. Results The ADC was significantly higher for inflammatory lesions than for lung cancer ([1.21 ± 0.20] × 10^-3 mm²/s vs. [0.97 ± 0.15] × 10^-3 mm²/s; P = 0.004). By IVIM, f was found to be significantly higher in inflammatory lesions than lung cancer ([46.10 ± 12.92] % vs. [29.29 ± 10.89] %; P = 0.005). There was no difference in D and D* between lung cancer and inflammatory lesions ( P = 0.747 and 0.124, respectively). f showed comparable diagnostic performance with ADC in differentiating lung cancer from inflammatory lung lesions, with areas under the curve of 0.833 and 0.826, sensitivity 80.0% and 73.3%, and specificity 75.0% and 87.5%, respectively. Conclusion The IVIM parameter f value provides comparable diagnostic performance with ADC and could be used as a surrogate marker for differentiating lung cancer from inflammatory lesions.

Potential Application of Radiomics for Differentiating Solitary Pulmonary Nodules

A solitary pulmonary nodule is defined as radiographic lesion with diameters no more than 3 cm and completely surrounded by normal lung tissue. It is commonly encountered in clinical practice and its diagnosis is a big challenge. Medical imaging, as a non-invasive approach, plays a crucial role in the diagnosis of solitary pulmonary nodules since the potential morbidity of surgery and the limits of biopsy. Advanced hardware, image acquisition and analysis technologies have led to the utilization of imaging towards quantitative imaging. With the aim of mining more useful information from image data, radiomics with high-throughput extraction can play a useful role. This article is to introduce the current state of radiomics studies and describe the general procedures. Another objective of this paper is to discover the feasibility and potential of radiomics methods on differentiating solitary pulmonary nodules and to look into the future direction of radiomics in this area.

Diffusion-weighted magnetic resonance imaging for the initial characterization of non-fatty soft tissue tumors: correlation between T2 signal intensity and ADC values

OBJECTIVE

To evaluate the performance of quantitative diffusion-weighted imaging (DWI) correlated with T2 signal in differentiating non-fatty benign from malignant tumors.

MATERIAL AND METHODS

A total of 76 patients with a histologically confirmed non-fatty soft tissue tumors (46 benign and 30 malignant) were prospectively included in this ethics committee approved study. All patients signed an informed consent and underwent MRI with DWI with two b values (0 and 600). ADC values from the solid components of these tumors were obtained and were correlated with the lesion's signal intensity on T2-weighted fat-saturated sequences. ADC values were obtained from adjacent normal muscle to allow calculation of tumor/muscle ADC ratios.

RESULTS

There were 58 hyperintense and 18 iso or hypointense lesions. All hypointense lesions were benign. The mean ADC values for benign and malignant tumors were 1.47 ± 0.54 × 10(-3) and 1.17 ± 0.38 × 10(-3) mm(2)/s respectively (p < 0.005). The mean ADC ratio in benign iso or hypointense tumors was significantly lower than that of hyperintense ones (0.76 ± 0.21 versus 1.58 ± 0.82 - p < 0.0001). An ADC ratio lower than 0.915 was highly specific for malignancy (96.4 %), whereas an ADC ratio higher than 1.32 was highly sensitive for benign lesions (90 %).

CONCLUSION

ADC analysis can be useful in the initial characterization of T2 hyperintense non-fatty soft tissue masses, although this technique alone is not likely to change patient management.