Usefulness of diffusion-weighted MR imaging in the evaluation of pulmonary lesions. Eur Radiol. 2010;20:807-815. [PMID: 19862533 DOI: 10.1007/s00330-009-1629-6]

Differential Diagnosis of Pathological Type of Peripheral Lung Cancer with Multimodal Contrast-Enhanced Ultrasound

OBJECTIVE

The goal of the work described here was to investigate the role of multimodal contrast-enhanced ultrasound in the differential diagnosis of peripheral lung cancer.

METHODS

From April 2017 to July 2021, 109 patients with confirmed pulmonary malignant lesions who underwent CEUS examination were involved in our study. Seven patients were excluded because of the short duration of CEUS video or unsatisfactory imaging. Finally,102 patients with peripheral lung cancer were enrolled in this study. The maximum diameter of the lesions ranged from 1.6 to 13.0 cm (mean 6.2 ± 2.3 cm). On the basis of the pathological results, the patients were divided into the small cell lung cancer (SCLC) group and non-small cell lung cancer (NSCLC) group (including adenocarcinoma, lung squamous cell carcinoma and large cell neuroendocrine carcinoma). A Logiq E9 ultrasonic machine equipped with a 3.5 to 5.0 MHz C5-1 probe was used. Patient clinical information, CEUS features, CPI patterns and TIC parameters were analyzed and compared between different groups. Statistical analyses were performed with SPSS software and MedCalc software. The receiver operating characteristic curve was plotted.

RESULTS

In the differential diagnosis of SCLC and NSCLC, color parametric imaging indicated great performance. NSCLC exhibited a centripetal enhancement pattern more frequently (72.7%), while SCLC exhibited an eccentric enhancement pattern more frequently (92.9%) (p < 0.001). In the differential diagnosis of adenocarcinoma and squamous cell carcinoma, logistic regression analysis revealed that patient age of onset ≤60 y, difference in arrival time between lung and tumor ≤3.8 s, drop time of the time-intensity curve >23.2 s and absence of internal necrosis on CEUS were independent predictors for adenocarcinoma (area under the curve = 0.861).

CONCLUSION

In our study, multimodal contrast-enhanced ultrasound provided useful information in the differential diagnosis between small cell lung cancer and non-small cell lung cancer, especially between adenocarcinoma and squamous cell carcinoma.

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

AIM

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSION

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

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.

Deep Learning With an Attention Mechanism for Differentiating the Origin of Brain Metastasis Using MR images

BACKGROUND

Brain metastasis (BM) is a serious neurological complication of cancer of different origins. The value of deep learning (DL) to identify multiple types of primary origins remains unclear.

PURPOSE

To distinguish primary site of BM and identify the best DL models.

STUDY TYPE

Retrospective.

POPULATION

A total of 449 BM derived from 214 patients (49.5% for female, mean age 58 years) (100 from small cell lung cancer [SCLC], 125 from non-small cell lung cancer [NSCLC], 116 from breast cancer [BC], and 108 from gastrointestinal cancer [GIC]) were included.

FIELD STRENGTH/SEQUENCE

A 3-T, T1 turbo spin echo (T1-TSE), T2-TSE, T2FLAIR-TSE, DWI echo-planar imaging (DWI-EPI) and contrast-enhanced T1-TSE (CE T1-TSE).

ASSESSMENT

Lesions were divided into training (n = 285, 153 patients), testing (n = 122, 93 patients), and independent testing cohorts (n = 42, 34 patients). Three-dimensional residual network (3D-ResNet), named 3D ResNet6 and 3D ResNet 18, was proposed for identifying the four origins based on single MRI and combined MRI (T1WI + T2-FLAIR + DWI, CE-T1WI + DWI, CE-T1WI + T2WI + DWI). DL model was used to distinguish lung cancer from non-lung cancer; then SCLC vs. NSCLC for lung cancer classification and BC vs. GIC for non-lung cancer classification was performed. A subjective visual analysis was implemented and compared with DL models. Gradient-weighted class activation mapping (Grad-CAM) was used to visualize the model by heatmaps.

STATISTICAL TESTS

The area under the receiver operating characteristics curve (AUC) assess each classification performance.

RESULTS

3D ResNet18 with Grad-CAM and AIC showed better performance than 3DResNet6, 3DResNet18 and the radiologist for distinguishing lung cancer from non-lung cancer, SCLC from NSCLC, and BC from GIC. For single MRI sequence, T1WI, DWI, and CE-T1WI performed best for lung cancer vs. non-lung cancer, SCLC vs. NSCLC, and BC vs. GIC classifications. The AUC ranged from 0.675 to 0.876 and from 0.684 to 0.800 regarding the testing and independent testing datasets, respectively. For combined MRI sequences, the combination of CE-T1WI + T2WI + DWI performed better for BC vs. GIC (AUCs of 0.788 and 0.848 on testing and independent testing datasets, respectively), while the combined MRI approach (T1WI + T2-FLAIR + DWI, CE-T1WI + DWI) could not achieve higher AUCs for lung cancer vs. non-lung cancer, SCLC vs. NSCLC. Grad-CAM helped for model visualization by heatmaps that focused on tumor regions.

DATA CONCLUSION

DL models may help to distinguish the origins of BM based on MRI data.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 2.

Quantitative analysis of chest MRI images for benign malignant diagnosis of pulmonary solid nodules

Background

In this study, we developed and validated machine learning (ML) models by combining radiomic features extracted from magnetic resonance imaging (MRI) with clinicopathological factors to assess pulmonary nodule classification for benign malignant diagnosis.

Methods

A total of 333 consecutive patients with pulmonary nodules (233 in the training cohort and 100 in the validation cohort) were enrolled. A total of 2,824 radiomic features were extracted from the MRI images (CE T1w and T2w). Logistic regression (LR), Naïve Bayes (NB), support vector machine (SVM), random forest (RF), and extreme gradient boosting (XGBoost) classifiers were used to build the predictive models, and a radiomics score (Rad-score) was obtained for each patient after applying the best prediction model. Clinical factors and Rad-scores were used jointly to build a nomogram model based on multivariate logistic regression analysis, and the diagnostic performance of the five prediction models was evaluated using the area under the receiver operating characteristic curve (AUC).

Results

A total of 161 women (48.35%) and 172 men (51.65%) with pulmonary nodules were enrolled. Six important features were selected from the 2,145 radiomic features extracted from CE T1w and T2w images. The XGBoost classifier model achieved the highest discrimination performance with AUCs of 0.901, 0.906, and 0.851 in the training, validation, and test cohorts, respectively. The nomogram model improved the performance with AUC values of 0.918, 0.912, and 0.877 in the training, validation, and test cohorts, respectively.

Conclusion

MRI radiomic ML models demonstrated good nodule classification performance with XGBoost, which was superior to that of the other four models. The nomogram model achieved higher performance with the addition of clinical information.

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.

The Efficiency of Diffusion-weighted Magnetic Resonance Imaging in the Differentiation of Malign and Benign Cavitary Lung Lesions

PURPOSE

The present study investigates the diagnostic efficiency of apparent diffusion coefficient (ADC) values in differentiating between malignant and benign cavitary lesions on diffusion-weighted magnetic resonance imaging (DWI).

MATERIALS AND METHODS

This prospective study included 45 consecutive patients identified with a cavitary lung lesion with a wall thickness of ≥5 mm on thoracic computed tomography in our clinic between 2020 and 2022, and who underwent thoracic DWI within 1 week of their original computed tomography. ADC measurements were made on DWI by drawing a region of interest manually from the cavity wall, away from the lung parenchyma in the axial section where the lesion was best demonstrated. The patients were then classified into benign and malignant groups based on the pathology or clinico-radiologic follow-up.

RESULTS

The sample included 29 (64.4%) male and 16 (35.6%) female patients, with a mean age of 59.06±17.3 years. Included in the study were 1 patient with 3 and 3 patients with 2 cavitary lesions each, with a total for the sample of 50 cavitary lesions. There were 23 (46%) malignant and 27 (54%) benign cavitary lung lesions. The mean ADC value (×10 -3  mm 2 /s) of the malignant and benign cavitary lesions was 0.977±0.522 (0.511 to 2.872) and 1.383±0.370 (0.930 to 2.213), respectively. The findings were statistically significant using an independent samples t test ( P =0.002). The mean wall thickness of the malignant and benign lesions was 12.47±5.51 mm (5 to 25 mm) and 10.11±4.65 mm (5 to 22 mm), respectively. Although malignant cavities had a higher mean wall thickness than benign cavities, the difference was statistically insignificant ( P =0.104).

CONCLUSION

A significant difference was identified between the ADC values measured in DWI of the malignant and benign cavitary lung lesions. DWI, a noninvasive and rapid imaging method, can provide useful information for the differential diagnosis of cavitary lesions and can minimize unnecessary biopsies.

Diffusion Weighted Imaging in Neuro-Oncology: Diagnosis, Post-Treatment Changes, and Advanced Sequences-An Updated Review

DWI is an imaging technique commonly used for the assessment of acute ischemia, inflammatory disorders, and CNS neoplasia. It has several benefits since it is a quick, easily replicable sequence that is widely used on many standard scanners. In addition to its normal clinical purpose, DWI offers crucial functional and physiological information regarding brain neoplasia and the surrounding milieu. A narrative review of the literature was conducted based on the PubMed database with the purpose of investigating the potential role of DWI in the neuro-oncology field. A total of 179 articles were included in the study.

Estimation of colon cancer grade and metastatic lymph node involvement using DWI/ADC sequences

BACKGROUND

The potential benefit of neoadjuvant chemotherapy (NAC) in colon cancer is under evaluation. There is a need to improve preoperative non-invasive diagnostics using techniques that provide more accurate staging information in assessing patient eligibility for NAC.

PURPOSE

To investigate the link between the tumor grade (pathohistological confirmed) and the N status (corresponding to lymph node involvement) with apparent diffusion coefficient (ADC) values.

MATERIAL AND METHODS

A total of 17 patients planned for surgical resection had a biopsy confirming colon carcinoma and participated in the study. Abdominal magnetic resonance imaging with diffusion-weighted imaging/ADC sequence was recorded before surgery. The tumor and all visible lymph nodes were manually delineated directly on a grayscale ADC map for every single slice and detected to access the total tumor and summarized lymph node volume. The mean ADC value was further calculated for the mean tumor and mean lymph node values.

RESULTS

Low-grade tumors had a mean ADC equivalent to 1225 ± 170×10^-6 mm²/s, and the coefficient of high-grade tumors was 1444 ± 69×10^-6 mm²/s. The group of patients with positive lymph nodes in operative tissue samples (N+) exhibited lower mean ADC values (1023 ± 142×10^-6 mm²/s) as opposed to the group without metastatic lymph nodes (N-) with ADC values of 1260 ± 231×10^-6 mm²/s.

CONCLUSION

The mean whole-tumor ADC is associated with the histological tumor grade, and the mean ADC value of whole-volume abdominal lymph nodes could assume real nodal infiltration.

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.

Early Effects of Elexacaftor-Tezacaftor-Ivacaftor Therapy on Magnetic Resonance Imaging in Patients with Cystic Fibrosis and Advanced Lung Disease

This is a prospective, observational study involving three Cystic Fibrosis (CF) adult patients, evaluating the changes in chest magnetic resonance imaging (MRI) three months after the start of elexacaftor/tezacaftor and ivacaftor therapy. MRI showed a drastic reduction in mucus plugging and bronchial wall thickening, with an improvement in the diffusion-weighted MRI score. Similarly, a marked improvement in spirometric parameters, nutritional status, and sweat chloride was observed. Our preliminary data confirm that chest MRI could be a useful tool to assess disease progression in CF patients on modulatory drug therapy.

Novel Insights of T2-Weighted Imaging: Significance for Discriminating Lung Cancer from Benign Pulmonary Nodules and Masses

Diffusion-weighted imaging is useful for discriminating lung cancer from benign pulmonary nodules and masses (BPNMs), however the diagnostic capability is not perfect. The aim of this research was to clarify whether T2-weighted imaging (T2WI) is efficient in discriminating lung cancer from BPNMs, especially from pulmonary abscesses. A T2 contrast ratio (T2 CR) for a pulmonary nodule is defined as the ratio of T2 signal intensity of a pulmonary nodule divided by the T2 signal intensity of the rhomboid muscle. There were 52 lung cancers and 40 inflammatory BPNMs (mycobacteria disease 12, pneumonia 13, pulmonary abscess 9, other 6) and seven non-inflammatory BPNMs. The T2 CR (2.14 ± 0.63) of lung cancers was significantly lower than that (2.68 ± 1.04) of BPNMs (p = 0.0021). The T2 CR of lung cancers was significantly lower than that (2.93 ± 0.26) of pulmonary abscesses (p = 0.011). When the optical cutoff value of T2 CR was set as 2.44, the sensitivity was 0.827 (43/52), the specificity 0.596 (28/47), the accuracy 0.717 (71/99), the positive predictive value 0.694 (43/62), and the negative predictive value 0.757 (28/37). T2 CR of T2WI is useful in discriminating lung cancer from BPNMs. Pulmonary abscesses, which show strong restricted diffusion in DWI, can be differentiated from lung cancers using T2WI.

Spin-echo and diffusion-weighted MRI in differentiation between progressive massive fibrosis and lung cancer

PURPOSE

We aimed to investigate the value of magnetic resonance imaging (MRI)-based parameters in differentiating between progressive massive fibrosis (PMF) and lung cancer.

METHODS

This retrospective study included 60 male patients (mean age, 67.0±9.0 years) with a history of more than 10 years working in underground coal mines who underwent 1.5 T MRI of thorax due to a lung nodule/mass suspicious for lung cancer on computed tomography. Thirty patients had PMF, and the remaining ones had lung cancer diagnosed histopathologically. The sequences were as follows: coronal single-shot turbo spin echo (SSH-TSE), axial T1- and T2-weighted spin-echo (SE), balanced turbo field echo, T1-weighted high-resolution isotropic volume excitation, free-breathing and respiratory triggered diffusion-weighted imaging (DWI). The patients' demographics, lesion sizes, and MRI-derived parameters were compared between the patients with PMF and lung cancer.

RESULTS

Apparent diffusion coefficient (ADC) values of DWI and respiratory triggered DWI, signal intensities on T1-weighted SE, T2-weighted SE, and SSH-TSE imaging were found to be significantly different between the groups (p < 0.001, for all comparisons). Median ADC values of free-breathing DWI in patients with PMF and cancer were 1.25 (0.93-2.60) and 0.76 (0.53-1.00) (× 10-3 mm2/s), respectively. Most PMF lesions were predominantly iso- or hypointense on T1-weighted SE, T2-weighted SE, and SSH-TSE, while most malignant ones predominantly showed high signal intensity on these sequences.

CONCLUSION

MRI study including SE imaging, specially T1-weighted SE imaging and ADC values of DWI can help to distinguish PMF from lung cancer.

How to Discriminate Lung Cancer From Benign Pulmonary Nodules and Masses? Usefulness of Diffusion-Weighted Magnetic Resonance Imaging With Apparent Diffusion Coefficient and Inside/Wall Apparent Diffusion Coefficient Ratio

Background:

Although diffusion-weighted imaging (DWI) is useful for differential diagnosis between lung cancers and benign pulmonary nodules and masses (BPNMs), it is difficult to differentiate pulmonary abscesses from lung cancers because pulmonary abscesses show restricted diffusion. With this research we will present how to assess the total apparent diffusion coefficient (ADC) and inside/wall ADC ratio for these pulmonary nodules and masses (PNMs).

Methods:

The pulmonary lesions were divided into next 3 groups. There were 40 lung cancers, 41 inflammatory benign PNMs (mycobacteria disease 13, pneumonia 12, pulmonary abscess 10, other 6) and 7 noninflammatory benign PNMs. Definitions were as follows: wall ADC = ADC value in outer one-third of the lesion; inside ADC = ADC value in central two-thirds of the lesion: inside/wall ADC ratio = ratio of inside ADC/wall ADC.

Results:

Mean total ADC (1.26 ± 0.32 × 10⁻³ mm²/s) of the lung cancers was remarkably lower than that (1.53 ± 0.53) of the BPNMs. The mean total ADC values were 1.26 ± 0.32 in lung cancer, 1.45 ± 0.47 in inflammatory BPNM and 2.04 ± 0.63 in noninflammatory BPNM, and there were significant differences among them. The mean inside ADC value (1.33 ± 0.32) of the lung cancers was remarkably higher than that (0.94 ± 0.42) of the pulmonary abscesses. The mean inside/wall ADC ratio (1.20 ± 0.28) of the lung cancers was remarkably higher than that (0.74 ± 0.14) of the pulmonary abscesses.

Conclusions:

Although ADC of DWI could differentiate lung cancer from BPNM, the inside/wall ADC ratio of DWI is efficient for differentiation between lung cancer and lung abscess. The inside/wall ADC ratio of DWI strengthens a weak point of DWI.

T2-weighted Lung Imaging Using a 0.55-T MRI System

Purpose

To assess a 0.55-T MRI system for imaging lung disease and to compare image quality with clinical CT scans.

Materials and Methods

In this prospective study conducted between November 2018 and December 2019, respiratory-triggered T2-weighted turbo spin-echo MRI at 0.55 T was compared with clinical CT scans in 24 participants (mean age, 59 years ± 16 [standard deviation]; 18 women) with common lung abnormalities. MR images were reviewed and scored by experienced readers. Abnormal findings identified with MRI and CT were compared using the Cohen κ statistic.

Results

High-quality structural pulmonary MR images were attained with an average acquisition time of 11 minutes ± 3. MRI generated sufficient image quality to robustly detect bronchiectasis (κ = 0.61), consolidative opacities (κ = 1.00), cavitary lesions (κ = 1.00), effusion (κ = 0.64), mucus plug (κ = 0.68), and solid scattered nodularity (κ = 0.82). Diffuse disease, including ground-glass opacities (κ = 0.57) and tree-in-bud nodules (κ = 0.48), were the findings that were most difficult to discern using MRI, with false readings in four of 18 patients for each feature. Nodule size, which was measured independently at CT and MRI, was strongly correlated (R ² = 0.99) for nodules with a measurement of 10 mm ± 5 (range, 5-23 mm).

Conclusion

This initial study indicates that high-performance 0.55-T MRI holds promise in the evaluation of common lung disease.Clinical trials registration no. NCT03331380Supplemental material is available for this article. Keywords: MRI, Pulmonary, Technology Assessment© RSNA, 2021.

Whole-Lesion Apparent Diffusion Coefficient Histogram Analysis: Significance for Discriminating Lung Cancer from Pulmonary Abscess and Mycobacterial Infection

Simple Summary

Diffusion-weighted magnetic resonance imaging (DWI) can differentiate malignant from benign pulmonary nodules and masses. However, it is difficult to differentiate pulmonary abscesses and mycobacterium infections (PAMIs) from lung cancers because PAMIs show restricted diffusion in DWI. The purpose of this study was to establish the role of ADC histogram for differentiating lung cancer from PAMI. There were 41 lung cancers and 19 PAMIs. Parameters more than 60% of AUC were ADC, maximal ADC, mean ADC, median ADC, most frequency ADC, kurtosis of ADC, and volume of lesion. There were significant differences between lung cancer and PAMI in ADC, mean ADC, median ADC, and most frequency ADC. ADC histogram has the potential to be a valuable tool to differentiate PAMI from lung cancer.

Abstract

Diffusion-weighted magnetic resonance imaging (DWI) can differentiate malignant from benign pulmonary nodules. However, it is difficult to differentiate pulmonary abscesses and mycobacterial infections (PAMIs) from lung cancers because PAMIs show restricted diffusion in DWI. The study purpose is to establish the role of ADC histogram for differentiating lung cancer from PAMI. There were 41 lung cancers (25 adenocarcinomas, 16 squamous cell carcinomas), and 19 PAMIs (9 pulmonary abscesses, 10 mycobacterial infections). Parameters more than 60% of the area under the ROC curve (AUC) were ADC, maximal ADC, mean ADC, median ADC, most frequency ADC, kurtosis of ADC, and volume of lesion. There were significant differences between lung cancer and PAMI in ADC, mean ADC, median ADC, and most frequency ADC. The ADC (1.19 ± 0.29 × 10⁻³ mm²/s) of lung cancer obtained from a single slice was significantly lower than that (1.44 ± 0.54) of PAMI (p = 0.0262). In contrast, mean, median, or most frequency ADC of lung cancer which was obtained in the ADC histogram was significantly higher than the value of each parameter of PAMI. ADC histogram could discriminate PAMIs from lung cancers by showing that AUCs of several parameters were more than 60%, and that several parameters of ADC of PAMI were significantly lower than those of lung cancer. ADC histogram has the potential to be a valuable tool to differentiate PAMI from lung cancer.

Combination Assessment of Diffusion-Weighted Imaging and T2-Weighted Imaging Is Acceptable for the Differential Diagnosis of Lung Cancer from Benign Pulmonary Nodules and Masses

Simple Summary

The purpose of this study is to determine whether the combination assessment of DWI and T2WI improves the diagnostic ability for differential diagnosis of lung cancer from benign pulmonary nodules and masses (BPNMs). As using the OCV (1.470 × 10⁻³ mm²/s) for ADC, the sensitivity was 83.9% (220/262), the specificity 63.4% (33/52), and the accuracy 80.6% (253/314). As using the OCV (2.45) for T2 CR, the sensitivity was 89.7% (235/262), the specificity 61.5% (32/52), and the accuracy 85.0% (267/314). In 212 PNMs which were judged to be malignant by both DWI and T2WI, 203 PNMs (95.8%) were lung cancers. In 33 PNMs which were judged to be benign by both DWI and T2WI, 23 PNMs (69.7%) were BPNMs. The combined assessment of DWI and T2WI could judge PNMs more precisely and would be acceptable for differential diagnosis of PNMs.

Abstract

The purpose of this study is to determine whether the combination assessment of DWI and T2-weighted imaging (T2WI) improves the diagnostic ability for differential diagnosis of lung cancer from benign pulmonary nodules and masses (BPNMs). The optimal cut-off value (OCV) for differential diagnosis was set at 1.470 × 10⁻³ mm²/s for apparent diffusion coefficient (ADC), and at 2.45 for T2 contrast ratio (T2 CR). The ADC (1.24 ± 0.29 × 10⁻³ mm²/s) of lung cancer was significantly lower than that (1.69 ± 0.58 × 10⁻³ mm²/s) of BPNM. The T2 CR (2.01 ± 0.52) of lung cancer was significantly lower than that (2.74 ± 1.02) of BPNM. As using the OCV for ADC, the sensitivity was 83.9% (220/262), the specificity 63.4% (33/52), and the accuracy 80.6% (253/314). As using the OCV for T2 CR, the sensitivity was 89.7% (235/262), the specificity 61.5% (32/52), and the accuracy 85.0% (267/314). In 212 PNMs which were judged to be malignant by both DWI and T2WI, 203 PNMs (95.8%) were lung cancers. In 33 PNMs which were judged to be benign by both DWI and T2WI, 23 PNMs (69.7%) were BPNMs. The combined assessment of DWI and T2WI could judge PNMs more precisely and would be acceptable for differential diagnosis of PNMs.

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.

Correlation of the apparent diffusion coefficient (ADC) and standardized uptake values (SUV) with overall survival in patients with primary non-small cell lung cancer (NSCLC) using 18F-FDG PET/MRI

OBJECTIVES

To investigate if the combined analysis of the apparent diffusion coefficient (ADC) and standardized uptake values (SUV) measured in ¹⁸F-fluoro-deoxy-glucose-positron emission tomography/magnetic resonance imaging (¹⁸F-FDG PET/MRI) examinations correlates with overall survival in non-small cell lung cancer (NSCLC).

MATERIAL AND METHODS

A total of 92 patients with newly diagnosed, histopathologically proven NSCLC (44 women and 48 men, mean age 63.1 ± 9.9y) underwent a dedicated thoracic ¹⁸F-FDG PET/MRI examination. A manually drawn polygonal region of interest (ROI), encompassing the entire primary tumor mass, was placed over the primary tumor on fused PET/MR images to determine the maximum and mean standardized uptake values (SUV_max; SUV_mean) as well as on the ADC maps to quantify the mean and minimum ADC values (ADC_mean, ADC_min). The impact of these parameters to predict patient's overall survival was tested using hazard ratios (HR). Pearson's correlation coefficients were calculated to assess dependencies between the different values. A p-value < 0.05 indicated statistical significance.

RESULTS

In all 92 patients (n = 59 dead at time of retrospective data collection, mean time till death: 19 ± 16 month, n = 33 alive, mean time to last follow-up: 56 ± 22 month) the Hazard ratios (HR) as independent predictors for overall survival (OS) of SUV_max were 2.37 (95 % CI: 1.23-4.59, p = 0.008) and for SUV_mean 1.85 (95 % CI: 1.05-3.26, p = 0.03) while ADC_min showed a HR of 0.95 (95 % CI: 0.57-1.59, p = 0.842) and ADC_mean a HR of 2.01 (95 % CI: 1.2-3.38, p = 0.007). Furthermore, a combined analysis for SUV_max/ADC_mean, SUV_max / ADC_min and SUV_mean/ADC_mean revealed a HR of 2.01 (95 % CI: 1.10-3.67, p = 0.02), 1.75 (95 % CI: 0.97-3.15, p = 0.058) and 1.78 (95 % CI: 1.02-3.10, p = 0.04).

CONCLUSION

SUV_max and SUV_mean of the primary tumor are predictors for OS in therapy-naive NSCLC patients, whereas the combined analysis of SUV and ADC values does not improve these results. Therefore, ADC values do not further enhance the diagnostic value of SUV as a prognostic biomarker in NSCLC.

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

Purpose

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

Material and methods

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

Results

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

Conclusions

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

3T magnetic resonance for evaluation of adult pulmonary tuberculosis

OBJECTIVES

To evaluate image quality and detection rate of four 3T magnetic resonance imaging (MRI) sequences and MRI performances in pulmonary tuberculosis (TB) when compared to computed tomography (CT).

METHODS

Forty patients with pulmonary tuberculosis separately underwent CT and 3T-MRI with T1-weighted free-breathing star-volumetric interpolated breath-hold examination (Star-VIBE) and standard VIBE, T2-weighted two-dimensional fast BLADE turbo spin-echo (2D-fBLADE TSE) and three-dimensional isotropic turbo spin-echo (3D-SPACE). Four MRI sequences were compared in terms of detection rate and image quality, which consisted of signal to noise ratio (SNR), contrast to noise ratio (CNR) and 5-point scoring scale. The total sensitivity was also compared between CT and MRI. Inter-observer agreement on 5-point scoring scale was calculated by Cohen's kappa (k). SNR, CNR and 5-point scoring scale were compared using two-tailed pared t-test. Using CT as a reference, the MRI detection rate of pulmonary abnormality was evaluated by Pearson's Chi-square test. Furthermore, the sizes of the nodules (≥5 mm) were compared using intraclass correlation coefficient.

RESULTS

In this study, Free-breathing Star-VIBE had significantly better SNR and identical CNR compared with standard VIBE. 2D-fBLADE TSE had statistically higher SNR but uniform or inferior CNR compared with 3D-SPACE. Inter-observers showed excellent agreement on 5-point scoring scale. The average score of Star-VIBE and VIBE had no difference. The average score of 2D-fBLADE TSE was higher than 3D-SPACE. There were no statistical differences in the detection rates of non-calcified parenchymal lesions between Star-VIBE and standard VIBE, 2D-fBALDE TSE and 3D-SPACE. MRI is comparable to CT in detecting consolidation, cavity, non-calcified nodules of ≥5 mm and tree-in-bud signs compared to CT. MRI detected non-calcified nodules of ＜5 mm, 5-10 mm, ≥10 mm and calcified nodules with sensitivity of 69.6%, 90.6%, 100% and 89.5% respectively. In addition, the sizes of the nodules (≥5 mm) had statistical consistency. MRI is more sensitive in detecting caseous necrosis, liquefaction, active cavity, abnormalities of lymph nodes and pleura.

CONCLUSIONS

T1-weighted free-breathing Star-VIBE and T2-weighted 2D-fBLADE TSE, both with satisfactory image quality, are suitable for patients with pulmonary TB who need long-term follow-ups in clinical routine, especially for children, young women and pregnant women.

The ability and utility of diffusion-weighted magnetic resonance imaging with different 'b' values in the differentiation of benign from malignant lung lesions

Purpose

To evaluate the ability and the utility of diffusion-weighted magnetic resonance imaging (MRI) with different ‘b’ values to visualise benign and malignant lung lesions, and to determine which ‘b’ value (b = 300, 500, or 1000 s/mm²) was most useful in differentiating benign from malignant lung lesions.

Material and methods

A total of 100 patients (28 women, 72 men; mean age = 57.19 ± 13.44 years; age range = 20-83 years). Diffusion-weighted imaging (DWI) was obtained with ‘b’ values of 300, 500, and 1000 s/mm². The signal intensity of lesions on DWI images was analysed, and the apparent diffusion coefficient (ADC) values of the lesions were calculated. MRI was performed in all patients after having presented at our department for thoracic computed tomography for various reasons.

Results

A statistically significant difference in DWI signal scores was detected between benign and malignant lesions for all ‘b’ factors (p < 0.0001 for each). The sensitivity and specificity were 95% and 64%, respectively, when a score of 3 for β = 300 s/mm²; 90% and 69%, respectively, when a score of 3 for β = 500 s/mm²; and 84% and 74%, respectively, when a score of 3 for β = 1000 s/mm². ADC values showed significant differences between benign and malignant lesions for all ‘b’ factors (p < 0.0001 for each).

Conclusions

Using ‘b’ values of 300, 500, and 1000 s/mm², DWI signal intensity scores and ADC values are effective methods for the differential diagnosis of malignant and benign pulmonary lesions.

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.

Evaluation of the components of mediastinal cystic lesions using imaging techniques

OBJECTIVE

To identify and differentiate patients with mediastinal cysts from those with cystic tumors requiring surgery.

METHODS

A total of 36 patients with mediastinal cystic lesions were enrolled. The patients were separated into two groups based on pathological findings : those with mediastinal cysts (n=23) and those with mediastinal tumors (n=13). The cystic components were measured using imaging parameters including mean computed tomography (CT) value, apparent diffusion coefficient (ADC), T1 signal intensity ratio (T1SIratio), and T2 signal intensity ratio (T2SI-ratio), acquired from magnetic resonance imaging (MRI) ; and standardized maximum uptake value (SUVmax) from¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT). Both groups were statistically compared.

RESULTS

Comparative parameters between the cysts and tumors revealed the following ratios : CT value, 40.9?21.2 versus (vs) 24.8?12.9 (p = 0.019) ;SUVmax, 1.18?0.50 vs 4.32?3.52 (p = 0.003) ; ADC, 3.46?0.96 vs 2.68?0.74 (p = 0.022) ; T1SI-ratio, 1.06?0.60 vs 1.35? 0.92 (p = 0.648) ; T2SI-ratio, 5.40?1.80 vs 4.33?1.58 (p = 0.194). However, there was no correlation between FDG uptake and ADC value.

CONCLUSIONS

SUVmax from¹⁸F-FDG PET/CT and ADC derived from MRI were effective in facilitating preoperative diagnosis to differentiate mediastinal cysts from tumors. However, these examinations may be complementary to one another, not dominant. J. Med. Invest. 66 : 106-111, February, 2019.

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.

Role of diffusion-weighted magnetic resonance imaging in the differentiation of benign and malignant pulmonary lesions

Purpose

To evaluate the role of magnetic resonance (MRI) diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) measurement of solid and cystic pulmonary masses in differentiating benign from malignant lesions.

Material and methods

The study included 41 patients with pulmonary masses, who underwent conventional MRI and DWI (b value 0, 500, and 1000 s/mm²) examinations with 1.5-T MRI. The diffusion signal and the mean ADC values of the solid and cystic lesions were obtained. Statistical analyses were performed with the Mann-Whitney U test (z), Pearson’s chi-square test, and receiver operating characteristic (ROC) analysis.

Results

Thirty-three lesions were malignant, and eight lesions were benign. The malignant masses showed significantly higher signal intensity on DWI than benign masses (p = 0.006), and the mean ADC value of malignant solid lesions was significantly lower than that of benign lesions (p = 0.02). By ROC analysis, an ADC cut-off value of 1.4 × 10^–3 mm²/s was considered the threshold value, and the sensitivity and specificity were 93.8% and 75%, respectively. There was no significant difference between the ADC value of the cystic parts inside the benign and the malignant lesions.

Conclusions

Diffusion-weighted MRI and measurement of ADC value can significantly differentiate between solid benign and malignant pulmonary masses.

Combination of free-breathing radial 3D fat-suppressed T1-weighted gradient-echo sequence with diffusion weighted images: Potential for differentiating malignant from benign peripheral solid pulmonary masses

OBJECTIVES

High resolution CT is the most commonly used radiological method for differentiating benign from malignant peripheral solid pulmonary masses, however, some of them are not easily diagnosed by morphology alone. Furthermore, due to the radiation dose, it is unsuitable for patients with disorders requiring repeated examinations over prolonged periods. The aims of this study were to evaluate whether a combination of diffusion-weighted images (DWI) and free-breathing radial 3D fat-suppressed T1-weighted gradient echo (radial volumetric interpolated breath-hold examination, radial VIBE) sequence can enable discrimination between benign from malignant peripheral solid pulmonary masses.

MATERIALS AND METHODS

Both chest CT scan and MR imaging with radial VIBE and DWI were obtained from 47 patients; 30 males and 17 females (mean age 64 years old; age range 48-83 years old). Benign and malignant peripheral solid pulmonary masses were conclusively identified by pathology results. Two radiologists independently reviewed all the images and record radiological features including morphological signs on radial VIBE, CT images, and ADC value. Receiver operating characteristic (ROC) was used to analyze the capability of radial VIBE as well as DWI to distinguish malignant from benign peripheral solid pulmonary masses.

RESULTS

In 77% of patients, malignant peripheral solid pulmonary masses were found. Morphological signs of mediastinal lymph node enlargement and lobulation were more easily found in malignant masses in both radial VIBE (mediastinal lymph node enlargement: p = 0.033, lobulation: p = 0.039) and CT (mediastinal lymph node enlargement: p = 0.004, lobulation: p = 0.012). The ADC value were also significant difference between benign and malignant groups (p = 0.001). Combined ADC value with radial VIBE was a most specific test than routine-dose CT (86.1% vs 75%, p < 0.001), but less sensitive than routine-dose CT (81.8% vs 90.9%; p < 0.001) for malignant peripheral solid pulmonary masses detection. Diagnostic accuracy was 89% for combining ADC value with radial VIBE, and 85% for routine-dose CT.

CONCLUSIONS

Combination of morphological signs and ADC value seems to improve differentiating malignant from benign peripheral solid pulmonary masses. Especially in patients unable to endure radiation exposure, suspend respiration, radial VIBE provides similar morphological signs displaying to those on routine-dose CT.

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.

Diffusion-weighted MRI of the lung at 3T evaluated using echo-planar-based and single-shot turbo spin-echo-based acquisition techniques for radiotherapy applications

Purpose

To compare single‐shot echo‐planar (SS‐EPI)‐based and turbo spin‐echo (SS‐TSE)‐based diffusion‐weighted imaging (DWI) in Non‐Small Cell Lung Cancer (NSCLC) patients and to characterize the distributions of apparent diffusion coefficient (ADC) values generated by the two techniques.

Methods

Ten NSCLC patients were enrolled in a prospective IRB‐approved study to compare and optimize DWI using EPI and TSE‐based techniques for radiotherapy planning. The imaging protocol included axial T2w, EPI‐based DWI and TSE‐based DWI on a 3 T Philips scanner. Both EPI‐based and TSE‐based DWI sequences used three b values (0, 400, and 800 s/mm²). The acquisition times for EPI‐based and TSE‐based DWI were 5 and 8 min, respectively. DW‐MR images were manually coregistered with axial T2w images, and tumor volume contoured on T2w images were mapped onto the DWI scans. A pixel‐by‐pixel fit of tumor ADC was calculated based on monoexponential signal behavior. Tumor ADC mean, standard deviation, kurtosis, and skewness were calculated and compared between EPI and TSE‐based DWI. Image distortion and ADC values between the two techniques were also quantified using fieldmap analysis and a NIST traceable ice‐water diffusion phantom, respectively.

Results

The mean ADC for EPI and TSE‐based DWI were 1.282 ± 0.42 × 10⁻³ and 1.211 ± 0.31 × 10⁻³ mm²/s. The average skewness and kurtosis were 0.14 ± 0.4 and 2.43 ± 0.40 for DWI‐EPI and −0.06 ± 0.69 and 2.89 ± 0.62 for DWI‐TSE. Fieldmap analysis showed a mean distortion of 13.72 ± 8.12 mm for GTV for DWI‐EPI and 0.61 ± 0.4 mm for DWI‐TSE. ADC values obtained using the diffusion phantom for the two techniques were within 0.03 × 10⁻³ mm²/s with respect to each other as well as the established values.

Conclusions

Diffusion‐weighted turbo spin‐echo shows better geometrical accuracy compared to DWI‐EPI. Mean ADC values were similar with both acquisitions but the shape of the histograms was different based on the skewness and kurtosis values. The impact of differences in respiratory technique on ADC values requires further investigation.

Optimizing diffusion-weighted magnetic resonance imaging for evaluation of lung tumors: A comparison of respiratory triggered and free breathing techniques

Purpose

The aim of this study was to compare respiratory-triggered (RT) and free breathing (FB) diffusion weighted imaging (DWI) techniques regarding apparent diffusion coefficient (ADC) measurements and repeatability in non-squamous non-small cell lung cancer (NSCLC) measuring the total tumor volume.

Material and Methods

A total of 57 magnetic resonance imaging (MRI) examinations were analyzed. DWI was obtained by a single-shot spin-echo echo-planar imaging sequence, and for each MRI examination 2 consecutive RT and 2 consecutive FB DWI sequences were performed. Two radiologists independently read the images and made measurements. For each tumor the mean ADC value of the whole tumor volume was calculated. The difference in mean ADCs between FB and RT DWI was evaluated using the paired-sample t-test. The repeatability of ADC measurements related to imaging method was evaluated by intra class correlations (ICC) for each of the FB and RT DWI pairs.

Results

There were no significant differences in mean ADCs between FB and RT (Reader 1 p = 0.346, Reader 2 p = 0.583). The overall repeatability of ADC measurement was good for both acquisition methods, with ICCs > 0.9. Subgroup analysis showed somewhat poorer repeatability in small tumors (50 ml or less) and tumors in the lower lung zones for the RT acquisition, with ICC as low as 0.72.

Conclusions

No difference in ADC measurement or repeatability between FB and RT DWI in whole lesion ADC measurements of adenocarcinomas in the lung was demonstrated. The results imply that in this setting the FB acquisition method is accurate and possibly more robust than the RT acquisition technique.

Diffusion-weighted imaging in evaluating the efficacy of concurrent chemoradiotherapy in the treatment of non-small cell lung cancer

Objective:

To explore the predictive value of diffusion-weighted imaging (DWI) in evaluating the short-term efficacy of concurrent chemoradiotherapy (CCRT) in the treatment of patients with non-small cell lung cancer (NSCLC).

Methods:

A total of 192 patients with NSCLC were selected and treated with CCRT. Dynamic contrast-enhanced magnetic resonance imaging combined with DWI was performed on all patients before and after CCRT treatment. Correspondingly, apparent diffusion coefficient (ADC) values were recorded before treatment (ADCpre), during treatment (ADCmid), and after treatment (ADCpost). Tumor response was evaluated as complete response (CR), partial response (PR), stable disease (SD), or progressive disease (PD). Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic power of quantitative DWI parameters in predicting the short-term efficacy of CCRT for patients with NSCLC.

Results:

There were 21 patients with CR, 82 with PR, 77 with SD, and 12 with PD. The ADCpre was negatively correlated with tumor regression rate, whereas ADCmid, ADCpost, and their respective change rates ∆ADCmid and ∆ADCpost were positively related to tumor regression rate. The ROC curve analysis suggested ADCpre = 1.38 × 10−3 mm2/s, ∆ADCmid = 14.14%, and ∆ADCpost = 20.39% as thresholds to predict the short-term efficacy of CCRT, with corresponding areas under the curve of 0.637, 0.743, and 0.752, respectively.

Conclusions:

These findings indicate that DWI provides promising predictive value in evaluating the short-term efficacy of CCRT in the treatment of patients with NSCLC.

Detection and monitoring of lung inflammation in cystic fibrosis during respiratory tract exacerbation using diffusion-weighted magnetic resonance imaging

The aim was to investigate whether diffusion-weighted magnetic resonance imaging (DWI) detects and monitors inflammatory and lung function changes during respiratory tract exacerbations (RTE) treatment in patients with cystic fibrosis (CF).29 patients with RTE underwent DWI pre- and post-antibiotic treatment. A control group of 27 stable patients, matched for age and sex, underwent DWI with the same time gap as those undergoing RTE treatment. Clinical status and lung function were assessed at each DWI time point. The CF-MRI scoring system was used to assess structural lung changes in both CF groups.Significant reduction in the DWI score over the course of antibiotic treatment (p<0.0001) was observed in patients with RTE, but not in the control group. DWI score had a strong inverse correlation with clinical status (r=-0.504, p<0.0001) and lung function (r=-0.635, p<0.0001) in patients with RTE. Interestingly, there were persistent significant differences in the CF-MRI score between the RTE and control group at both baseline and follow-up (p<0.001), while the differences in DWI score were only observed at baseline (p<0.001).DWI is a promising imaging method for noninvasive detection of pulmonary inflammation during RTE, and may be used to monitor treatment efficacy of anti-inflammatory treatment.

Diffusion-weighted magnetic resonance imaging for the detection of metastatic lymph nodes in patients with lung cancer: A meta-analysis

The aim of the present meta-analysis was to evaluate the diagnostic value of diffusion-weighted imaging (DWI) in differentiating metastatic from non-metastatic lymph nodes in patients with lung cancer. A systematic literature search was performed to identify eligible original studies. The quality of included studies was assessed using ‘quality assessment of diagnostic accuracy studies’ (QUADAS-2). Meta-analysis was performed to pool sensitivity and specificity, to calculate the positive likelihood ratio (PLR), the negative likelihood ratio (NLR) and the diagnostic odds ratio (DOR), and to construct the summary receiver operating characteristic (SROC) curve. The homogeneity, threshold effect and publication bias were also investigated. Meta-regression analysis was performed to identify the sources of heterogeneity. A total of 10 studies with 11 datasets met the inclusion criteria, which comprised 796 patients with a total of 2,433 lymph nodes. The pooled diagnostic sensitivity was 0.78 [95% confidence interval (CI): 0.74–0.81] and the pooled diagnostic specificity was 0.88 (95% CI: 0.86–0.89). The PLR, NLR, and DOR were 7.11 (95% CI: 4.39–11.52), 0.24 (95% CI: 0.18–0.33), and 31.14 (95% CI: 17.32–55.98), respectively. The area under the SROC curve was 0.90. No publication bias was found (bias=−0.15, P=0.887). Notable heterogeneity was, however, observed, and patient selection, type of lung cancer, number of enrolled lymph nodes, reference standard, B-value and the type of scanner were the sources of heterogeneity (P<0.05). No significant threshold effect was identified (P=0.537). In conclusion, DWI has been revealed to be a valuable magnetic resonance imaging (MRI) modality, with good diagnostic performance for distinguishing metastatic from non-metastatic lymph nodes in patients with lung cancer. Therefore, DWI may be a useful supplement to conventional MRI techniques.

Is it better to include necrosis in apparent diffusion coefficient (ADC) measurements? The necrosis/wall ADC ratio to differentiate malignant and benign necrotic lung lesions: Preliminary results

PURPOSE

To determine whether the use of necrosis/wall apparent diffusion coefficient (ADC) ratios in the differentiation of necrotic lung lesions is more reliable than measuring the wall alone.

MATERIALS AND METHODS

In this retrospective study, a total of 76 patients (54 males and 22 females, 71% vs. 29%, with a mean age of 53 ± 18 years, range, 18-84) were enrolled, 33 of whom had lung carcinoma and 43 had a benign necrotic lung lesion. A 3T scanner was used. The calculation of the necrosis/wall ADC ratio was based on ADC values measured from necrosis and the wall of the lesions by diffusion-weighted imaging (DWI). Statistical analyses were performed with the independent samples t-test and receiver operating characteristic analysis. Intraobserver and interobserver reliability were calculated for ADC values of wall and necrosis.

RESULTS

The mean necrosis/wall ADC ratio was 1.67 ± 0.23 for malignant lesions and 0.75 ± 0.19 for benign lung lesions (P < 0.001). To estimate malignancy the area under the curve (AUC) values for necrosis ADC, wall ADC, and the necrosis/wall ADC ratio were 0.720, 0.073, and 0.997, respectively. A wall/necrosis ADC ratio cutoff value of 1.12 demonstrated a 100% sensitivity and 98% specificity in the estimation of malignancy. Positive predictive value was 100%, and negative predictive value 98% and diagnostic accuracy 99%. There was a good intraobserver and interobserver reliability for wall and necrosis.

CONCLUSION

The necrosis/wall ADC ratio appears to be a reliable and promising tool for discriminating lung carcinoma from benign necrotic lung lesions than measuring the wall alone.

LEVEL OF EVIDENCE

4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2017;46:1001-1006.

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.

Initial Experience of 18F-FDG PET/MRI in Thymic Epithelial Tumors: Morphologic, Functional, and Metabolic Biomarkers

PURPOSE

The aim of this study was to investigate the value of morphologic, functional, and metabolic biomarkers acquired concurrently at PET/MRI in patients with thymic epithelial tumors.

PATIENTS AND METHODS

During 1 year, 9 patients with suspected thymic epithelial tumors at contrast-enhanced chest CT were prospectively enrolled and underwent preoperative 18F-FDG PET/MRI. Two chest radiologists prospectively reviewed the CT and MRI scans of PET/MRI in consensus, and 2 nuclear physicians reviewed the PET images. Visual assessment of the tumor morphology, functional biomarkers such as apparent diffusion coefficient from diffusion-weighted images, and metabolic biomarkers (including SUVmax, metabolic tumor volume, total lesion glycolysis, and heterogeneity index) were recorded. All patients underwent operation, and their pathologic reports served as the reference standard.

RESULTS

Thymic epithelial tumors were demonstrated in all 9 patients at pathologic examination. Tumor contour (P = 0.012) and shape (P = 0.033) had an association with the World Health Organization subtype, and the presence of septum (P = 0.048) on MRI scans had an association with the Masaoka stage. In terms of functional and metabolic biomarkers, SUVmax (ρ = 0.683, P = 0.042) and SUV/apparent diffusion coefficient (ρ = 0.703, P = 0.035) correlated with the Masaoka stage. Metabolic tumor volume (P = 0.024), heterogeneity index (P = 0.024), and total lesion glycolysis (P = 0.048) were useful for classification between low- and high-risk thymic epithelial tumors.

CONCLUSIONS

Although limited by the small number of patients enrolled, morphologic, functional, and metabolic biomarkers derived from PET/MRI scans were useful for the stratification of thymic epithelial tumors.

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.

MR imaging features and staging of neuroendocrine carcinomas of the uterine cervix with pathological correlations

OBJECTIVE

To determine MR imaging features and staging accuracy of neuroendocrine carcinomas (NECs) of the uterine cervix with pathological correlations.

METHODS

Twenty-six patients with histologically proven NECs, 60 patients with squamous cell carcinomas (SCCs), and 30 patients with adenocarcinomas of the uterine cervix were included. The clinical data, pathological findings, and MRI findings were reviewed retrospectively. MRI features of cervical NECs, SCCs, and adenocarcinomas were compared, and MRI staging of cervical NECs was compared with the pathological staging.

RESULTS

Cervical NECs showed a higher tendency toward a homogeneous signal intensity on T2-weighted imaging and a homogeneous enhancement pattern, as well as a lower ADC value of tumour and a higher incidence of lymphadenopathy, compared with SCCs and adenocarcinomas (P < 0.05). An ADC value cutoff of 0.90 × 10^-3 mm²/s was robust for differentiation between cervical NECs and other cervical cancers, with a sensitivity of 63.3 % and a specificity of 95 %. In 21 patients who underwent radical hysterectomy and lymphadenectomy, the overall accuracy of tumour staging by MR imaging was 85.7 % with reference to pathology staging.

CONCLUSION

Homogeneous lesion texture and low ADC value are likely suggestive features of cervical NECs and MR imaging is reliable for the staging of cervical NECs.

KEY POINTS

• Cervical NECs show a tendency of lesion homogeneity and lymphadenopathy • Low ADC values are found in cervical NECs • MRI is an accurate imaging modality for the cervical NEC staging.

Diffusion weighted imaging in cystic fibrosis disease: beyond morphological imaging

OBJECTIVES

To explore the feasibility of diffusion-weighted imaging (DWI) to assess inflammatory lung changes in patients with Cystic Fibrosis (CF) METHODS: CF patients referred for their annual check-up had spirometry, chest-CT and MRI on the same day. MRI was performed in a 1.5 T scanner with BLADE and EPI-DWI sequences (b = 0-600 s/mm²). End-inspiratory and end-expiratory scans were acquired in multi-row scanners. DWI was scored with an established semi-quantitative scoring system. DWI score was correlated to CT sub-scores for bronchiectasis (CF-CT_BE), mucus (CF-CT_mucus), total score (CF-CT_total-score), FEV₁, and BMI. T-test was used to assess differences between patients with and without DWI-hotspots.

RESULTS

Thirty-three CF patients were enrolled (mean 21 years, range 6-51, 19 female). 4 % (SD 2.6, range 1.5-12.9) of total CF-CT alterations presented DWI-hotspots. DWI-hotspots coincided with mucus plugging (60 %), consolidation (30 %) and bronchiectasis (10 %). DWI_total-score correlated (all p < 0.0001) positively to CF-CT_BE (r = 0.757), CF-CT_mucus (r = 0.759) and CF-CT_total-score (r = 0.79); and negatively to FEV₁ (r = 0.688). FEV₁ was significantly higher (p < 0.0001) in patients without DWI-hotspots.

CONCLUSIONS

DWI-hotspots strongly correlated with radiological and clinical parameters of lung disease severity. Future validation studies are needed to establish the exact nature of DWI-hotspots in CF patients.

KEY POINTS

• DWI hotspots only partly overlapped structural abnormalities on morphological imaging • DWI strongly correlated with radiological and clinical indicators of CF-disease severity • Patients with more DWI hotspots had lower lung function values • Mucus score best predicted the presence of DWI-hotspots with restricted diffusion.

Improvement in imaging diagnosis technique and modalities for solitary pulmonary nodules: from ground-glass opacity nodules to part-solid and solid nodules

With advances in CT technology and the popularity of low-dose CT as a device for lung cancer screening, the detection rate of sub-solid pulmonary nodules as well as solid nodules has been increased. Distinguishing solid from sub-solid features is an essential step in the CT evaluation of solitary pulmonary nodules (SPNs) because strategies for nodule characterization and guidelines for management are different for each category. In addition to conventional CT parameters, numerous novel concepts and modalities have been developed. Although there is currently no single effective method for differentiating malignant from benign nodules, growth rate measurement using volumetry, evaluation of tumor vascularity on dynamic helical CT, dual-energy CT and MRI and physiologic evaluation with PET/CT can all be useful for nodule characterization. New techniques such as tomosynthesis can improve detection over radiography alone. The purpose of this article is to enhance our understanding of the evidence-based strategies involved in diagnosing SPNs.