Apparent diffusion coefficient values of diffusion-weighted imaging for distinguishing focal pulmonary lesions and characterizing the subtype of lung cancer: a meta-analysis

Evaluating Mediastinal Lymph Node Metastasis of Non-Small Cell Lung Cancer Using Mono-exponential, Bi-exponential, and Stretched-exponential Models of Diffusion-weighted Imaging

PURPOSE

To explore and compare the diagnostic values of mono-exponential, bi-exponential, and stretched-exponential diffusion-weighted imaging (DWI) parameters of primary lesions and lymph nodes (LNs) to predict mediastinal LN metastasis in patients with non-small cell lung cancer.

PATIENTS AND METHODS

Sixty-one patients with non-small cell lung cancer underwent preoperative magnetic resonance imaging, including multiple b -value DWI. The DWI parameters, including apparent diffusion coefficient (ADC) from a mono-exponential model, true diffusion (D) coefficient, pseudo-diffusion (D*) coefficient, and perfusion fraction (f) from a bi-exponential model, distributed diffusion coefficient (DDC) and intravoxel diffusion heterogeneity index (α) from a stretched-exponential model of primary tumors and LNs and the size characteristics of LNs, were measured and compared. Multivariate logistic regression analysis was used to establish models for predicting mediastinal LN metastasis. Receiver operating characteristic analysis was applied to evaluate diagnostic performances.

RESULTS

The DWI parameters of primary tumors showed no statistical significance between LN metastasis-positive and LN metastasis-negative groups. Nonmetastatic LNs had significantly higher ADC, D, DDC, and α values compared with metastatic LNs (all P < 0.05). The short-dimension, long-dimension, and short-long dimension ratio of metastatic LNs was significantly larger than those of nonmetastatic ones (all P < 0.05). The D value showed the best diagnostic performance among all DWI-derived single parameters, and the short dimension of LNs performed the same among all the size variables. Furthermore, the combination of DWI parameters (ADC and D) and the short dimension of LNs can significantly improve diagnostic efficiency.

CONCLUSIONS

The ADC, D, DDC, and α from the mono-exponential, bi-exponential, and stretched-exponential models were demonstrated efficient in differentiating benign from metastatic LNs, and the combination of ADC, D, and short dimension of LNs may have a better diagnostic performance than DWI or size-derived parameters either in combination or individually.

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.

Predictors of lung cancer subtypes and lymph node status in non-small-cell lung cancer: intravoxel incoherent motion parameters and extracellular volume fraction

OBJECTIVE

To determine the performance of intravoxel incoherent motion (IVIM) parameters and the extracellular volume fraction (ECV) in distinguishing between different subtypes of lung cancer and predicting lymph node metastasis (LNM) status in patients with non-small-cell lung cancer (NSCLC).

METHODS

One hundred sixteen patients with lung cancer were prospectively recruited. IVIM, native, and postcontrast T1 mapping examinations were performed, and the T1 values were measured to calculate the ECV. The differences in IVIM parameters and ECV were compared between NSCLC and small-cell lung cancer (SCLC), adenocarcinoma (Adeno-Ca) and squamous cell carcinoma (SCC), and NSCLC without and with LNM. The assessment of each parameter's diagnostic performance was based on the area under the receiver operating characteristic curve (AUC).

RESULTS

The apparent diffusion coefficient (ADC), true diffusion coefficient (D), and ECV values in SCLC were considerably lower compared with NSCLC (all p < 0.001, AUC > 0.887). The D value in SCC was substantially lower compared with Adeno-Ca (p < 0.001, AUC = 0.735). The perfusion fraction (f) and ECV values in LNM patients were markedly higher compared with those without LNM patients (p < 0.01, < 0.001, AUC > 0.708).

CONCLUSION

IVIM parameters and ECV can serve as non-invasive biomarkers for assisting in the pathological classification and LNM status assessment of lung cancer patients.

CRITICAL RELEVANCE STATEMENT

IVIM parameters and ECV demonstrated remarkable potential in distinguishing pulmonary carcinoma subtypes and predicting LNM status in NSCLC.

KEY POINTS

Lung cancer is prevalent and differentiating subtype and invasiveness determine the treatment course. True diffusion coefficient and ECV showed promise for subtyping and determining lymph node status. These parameters could serve as non-invasive biomarkers to help determine personalized treatment strategies.

Tri-Compartmental Restriction Spectrum Imaging Based on 18F-FDG PET/MR for Identification of Primary Benign and Malignant Lung Lesions

BACKGROUND

Restriction spectrum imaging (RSI), as an advanced quantitative diffusion-weighted magnetic resonance imaging technique, has the potential to distinguish primary benign and malignant lung lesions.

OBJECTIVE

To explore how well the tri-compartmental RSI performs in distinguishing primary benign from malignant lung lesions compared with diffusion-weighted imaging (DWI), and to further explore whether positron emission tomography/magnetic resonance imaging (PET/MRI) can improve diagnostic efficacy.

STUDY TYPE

Prospective.

POPULATION

137 patients, including 108 malignant and 29 benign lesions (85 males, 52 females; average age = 60.0 ± 10.0 years).

FIELD STRENGTH/SEQUENCE

T2WI, T1WI, multi-b value DWI, MR-based attenuation correction, and PET imaging on a 3.0 T whole-body PET/MR system.

ASSESSMENT

The apparent diffusion coefficient (ADC), RSI-derived parameters (restricted diffusionf 1 $$ {f}_1 $$ , hindered diffusionf 2 $$ {f}_2 $$ , and free diffusionf 3 $$ {f}_3 $$ ) and the maximum standardized uptake value (SUVmax) were calculated and analyzed for diagnostic efficacy individually or in combination.

STATISTICAL TESTS

Student's t-test, Mann-Whitney U test, receiver operating characteristic (ROC) curves, Delong test, Spearman's correlation analysis. P < 0.05 was considered statistically significant.

RESULTS

Thef 1 $$ {f}_1 $$ , SUVmax were significantly higher, andf 3 $$ {f}_3 $$ , ADC were significantly lower in the malignant group [0.717 ± 0.131, 9.125 (5.753, 13.058), 0.194 ± 0.099, 1.240 (0.972, 1.407)] compared to the benign group [0.504 ± 0.236, 3.390 (1.673, 6.030), 0.398 ± 0.195, 1.485 ± 0.382]. The area under the ROC curve (AUC) values ranked from highest to lowest as follows: AUC (SUVmax) > AUC (f 3 $$ {f}_3 $$ ) > AUC (f 1 $$ {f}_1 $$ ) > AUC (ADC) > AUC (f 2 $$ {f}_2 $$ ) (AUC = 0.819, 0.811, 0.770, 0.745, 0549). The AUC (AUC = 0.900) of the combined model of RSI with PET was significantly higher than that of either single-modality imaging.

CONCLUSION

RSI-derived parameters (f 1 $$ {f}_1 $$ ,f 3 $$ {f}_3 $$ ) might help to distinguish primary benign and malignant lung lesions and the discriminatory utility off 2 $$ {f}_2 $$ was not observed. The RSI exhibits comparable or potentially enhanced performance compared with DWI, and the combined RSI and PET model might improve diagnostic efficacy.

LEVEL OF EVIDENCE: 2

TECHNICAL EFFICACY

Stage 2.

Accurate diagnosis of pulmonary inflammatory myofibroblastic tumor by imaging technology before operation: A case report

RATIONALE

Pulmonary inflammatory myofibroblastic tumor (IMT) is a rare borderline tumor, which has the potential of malignant including invasion of surrounding tissues, distant metastasis and recurrence. However, the preoperative diagnosis is difficult and it can also be difficult to distinguish from malignancy in small tissue samples. Preoperative accurate diagnosis has important clinical significance for patients to choose treatment measures and improve the quality of rehabilitation. We was examined by computed tomography (CT) plain scan plus enhanced scan, magnetic resonance diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) imaging technology in an adult female, compared with lung cancer and pulmonary cryptococcus infection for diagnosis of pulmonary IMT.

PATIENT CONCERNS

A 32-year-old female patient was admitted to the hospital "physical examination revealed nodules in the right upper lung for 1 week".

DIAGNOSES

The patient was diagnosed with Pulmonary inflammatory myofibroblastic tumor.

INTERVENTIONS

Single-port thoracoscopic lobectomy was performed after multidisciplinary consultation.

OUTCOMES

DWI and ADC improves the accuracy of preoperative diagnosis and well guides the formulation of treatment measures. The combined CT, DWI, and ADC magnetic resonance imaging technology has more important significance in the diagnosis and differential diagnosis of IMT and lung malignant tumors.

LESSONS

Although accurate preoperative diagnosis of pulmonary IMT is difficult. Chest CT examination combined with DWI and ADC imaging technology has high clinical significance for the diagnosis of IMT.

Observational Study of the Natural Growth History of Peripheral Small-Cell Lung Cancer on CT Imaging

BACKGROUND

This study aimed to investigate the natural growth history of peripheral small-cell lung cancer (SCLC) using CT imaging.

METHODS

A retrospective study was conducted on 27 patients with peripheral SCLC who underwent at least two CT scans. Two methods were used: Method 1 involved direct measurement of nodule dimensions using a calliper, while Method 2 involved tumour lesion segmentation and voxel volume calculation using the "py-radiomics" package in Python. Agreement between the two methods was assessed using the intraclass correlation coefficient (ICC). Volume doubling time (VDT) and growth rate (GR) were used as evaluation indices for SCLC growth, and growth distribution based on GR and volume measurements were depicted. We collected potential factors related to imaging VDT and performed a differential analysis. Patients were classified into slow-growing and fast-growing groups based on a VDT cut-off point of 60 days, and univariate analysis was used to identify factors influencing VDT.

RESULTS

Median VDT calculated by the two methods were 61 days and 71 days, respectively, with strong agreement. All patients had continuously growing tumours, and none had tumours that decreased in size or remained unchanged. Eight patients showed possible growth patterns, with six possibly exhibiting exponential growth and two possibly showing Gompertzian growth. Tumours deeper in the lung grew faster than those adjacent to the pleura.

CONCLUSIONS

Peripheral SCLC tumours grow rapidly and continuously without periods of nongrowth or regression. Tumours located deeper in the lung tend to grow faster, but further research is needed to confirm this finding.

Pseudotumor Sarcoidosis: The Contribution of Thoracic MRI to the Presumption of Benignity of a Pulmonary Lesion Process

Sarcoidosis is a benign systemic disease; its diagnosis is based on a suggestive radiological presentation, and the isolation of an epithelioid and gigantocellular granuloma (EGGC) without caseous necrosis with the elimination of other causes of granuloma. However, sometimes the radiological presentation is atypical and misleading, posing problems in terms of differential diagnosis. In this report, we present a case of pseudotumor sarcoidosis, in which MRI played an essential role in characterizing the lesion and suggesting its benignity. We also discuss the role of MRI in evaluating atypical forms of sarcoidosis.

Whole-lesion histogram analysis of multiple diffusion metrics for differentiating lung cancer from inflammatory lesions

Background

Whole-lesion histogram analysis can provide comprehensive assessment of tissues by calculating additional quantitative metrics such as skewness and kurtosis; however, few studies have evaluated its value in the differential diagnosis of lung lesions.

Purpose

To compare the diagnostic performance of conventional diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) and diffusion kurtosis imaging (DKI) in differentiating lung cancer from focal inflammatory lesions, based on whole-lesion volume histogram analysis.

Methods

Fifty-nine patients with solitary pulmonary lesions underwent multiple b-values DWIs, which were then postprocessed using mono-exponential, bi-exponential and DKI models. Histogram parameters of the apparent diffusion coefficient (ADC), true diffusivity (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f), apparent diffusional kurtosis (K_app) and kurtosis-corrected diffusion coefficient (D_app) were calculated and compared between the lung cancer and inflammatory lesion groups. Receiver operating characteristic (ROC) curves were constructed to evaluate the diagnostic performance.

Results

The ADC^mean, ADC^median, D ^mean and D ^median values of lung cancer were significantly lower than those of inflammatory lesions, while the ADC^skewness, K_app ^mean, K_app ^median, K_app ^SD, K_app ^kurtosis and D_app ^skewness values of lung cancer were significantly higher than those of inflammatory lesions (all p < 0.05). ADC^skewness (p = 0.019) and D ^median (p = 0.031) were identified as independent predictors of lung cancer. D ^median showed the best performance for differentiating lung cancer from inflammatory lesions, with an area under the ROC curve of 0.777. Using a D ^median of 1.091 × 10^-3 mm²/s as the optimal cut-off value, the sensitivity, specificity, positive predictive value and negative predictive value were 69.23%, 85.00%, 90.00% and 58.62%, respectively.

Conclusions

Whole-lesion histogram analysis of DWI, IVIM and DKI parameters is a promising approach for differentiating lung cancer from inflammatory lesions, and D ^median shows the best performance in the differential diagnosis of solitary pulmonary lesions.

Artificial intelligence in musculoskeletal oncology imaging: A critical review of current applications

Artificial intelligence (AI) is increasingly being studied in musculoskeletal oncology imaging. AI has been applied to both primary and secondary bone tumors and assessed for various predictive tasks that include detection, segmentation, classification, and prognosis. Still, in the field of clinical research, further efforts are needed to improve AI reproducibility and reach an acceptable level of evidence in musculoskeletal oncology. This review describes the basic principles of the most common AI techniques, including machine learning, deep learning and radiomics. Then, recent developments and current results of AI in the field of musculoskeletal oncology are presented. Finally, limitations and future perspectives of AI in this field are discussed.

A comparison study of monoexponential and fractional order calculus diffusion models and 18F-FDG PET in differentiating benign and malignant solitary pulmonary lesions and their pathological types

Objective

To evaluate the application value of monoexponential, fractional order calculus (FROC) diffusion models and PET imaging to distinguish between benign and malignant solitary pulmonary lesions (SPLs) and malignant SPLs with different pathological types and explore the correlation between each parameter and Ki67 expression.

Methods

A total of 112 patients were enrolled in this study. Prior to treatment, all patients underwent a dedicated thoracic ¹⁸F-FDG PET/MR examination. Five parameters [including apparent diffusion coefficient (ADC) derived from the monoexponential model; diffusion coefficient (D), a microstructural quantity (μ), and fractional order parameter (β) derived from the FROC model and maximum standardized uptake value (SUVmax) derived from PET] were compared between benign and malignant SPLs and different pathological types of malignant SPLs. Independent sample t test, Mann-Whitney U test, DeLong test and receiver operating characteristic (ROC) curve analysis were used for statistical evaluation. Pearson correlation analysis was used to calculate the correlations between Ki-67 and ADC, D, μ, β, and SUVmax.

Results

The ADC and D values were significantly higher and the μ and SUVmax values were significantly lower in the benign group [1.57 (1.37, 2.05) μm²/ms, 1.59 (1.52, 1.72) μm²/ms, 5.06 (3.76, 5.66) μm, 5.15 ± 2.60] than in the malignant group [1.32 (1.03, 1.51) μm²/ms, 1.43 (1.29, 1.52) μm²/ms, 7.06 (5.87, 9.45) μm, 9.85 ± 4.95]. The ADC, D and β values were significantly lower and the μ and SUVmax values were significantly higher in the squamous cell carcinoma (SCC) group [1.29 (0.66, 1.42) μm²/ms, 1.32 (1.02, 1.42) μm²/ms, 0.63 ± 0.10, 9.40 (7.76, 15.38) μm, 11.70 ± 5.98] than in the adenocarcinoma (AC) group [1.40 (1.28, 1.67) μm²/ms, 1.52 (1.44, 1.64) μm²/ms, 0.70 ± 0.10, 5.99 (4.54, 6.87) μm, 8.76 ± 4.18]. ROC curve analysis showed that for a single parameter, μ exhibited the best AUC value in discriminating between benign and malignant SPLs groups and AC and SCC groups (AUC = 0.824 and 0.911, respectively). Importantly, the combination of monoexponential, FROC models and PET imaging can further improve diagnostic performance (AUC = 0.872 and 0.922, respectively). The Pearson correlation analysis showed that Ki67 was positively correlated with μ value and negatively correlated with ADC and D values (r = 0.402, -0.346, -0.450, respectively).

Conclusion

The parameters D and μ derived from the FROC model were superior to ADC and SUVmax in distinguishing benign from malignant SPLs and adenocarcinoma from squamous cell carcinoma, in addition, the combination of multiple parameters can further improve diagnostic performance. The non-Gaussian FROC diffusion model is expected to become a noninvasive quantitative imaging technique for identifying 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.

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

RATIONALE AND OBJECTIVES

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSION

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

Comparison of Conventional DWI, Intravoxel Incoherent Motion Imaging, and Diffusion Kurtosis Imaging in Differentiating Lung Lesions

Purpose

To compare conventional diffusion weighted imaging (DWI), intravoxel incoherent motion imaging (IVIM) and diffusion kurtosis imaging (DKI) in differentiating malignant and benign lung lesions.

Method

Fifty-five consecutive patients with lung lesions underwent multiple b-value DWI. The apparent diffusion coefficient (ADC), IVIM and DKI parameters were calculated using postprocessing software and compared between the malignant and benign groups. Receiver operating characteristic (ROC) analysis was performed for all parameters.

Results

ADC and D were lower in malignant lesions than in benign lesions, while Kapp was higher (P < 0.05). The differences in D*, f, and Dapp between the two groups were not significant (P > 0.05). The areas under the curves (AUCs) of ADC, D, and Kapp were 0.816, 0.864, and 0.822. The combination of all the significant parameters yielded an AUC of 0.880. There were no significant differences in diagnostic efficacy among ADC, D, Kapp and the predictor factor (PRE).

Conclusions

In this study, traditional DWI (ADC), IVIM (D), and DKI (Kapp) all had good diagnostic performance in differentiating malignant lung lesions from benign lesions, but the combination of ADC, D, and Kapp value had better diagnostic efficacy than these parameters alone.

A Comparative Study of Amide Proton Transfer Weighted Imaging and Intravoxel Incoherent Motion MRI Techniques Versus (18) F-FDG PET to Distinguish Solitary Pulmonary Lesions and Their Subtypes

BACKGROUND

Amide proton transfer weighted imaging (APTw), intravoxel incoherent motion (IVIM), and positron emission tomography (PET) imaging all have the potential to characterize solitary pulmonary lesions (SPLs).

PURPOSE

To compare APTw and IVIM with PET imaging for distinguishing between benign and malignant SPLs and their subtypes.

STUDY TYPE

Prospective.

POPULATION

Ninety-five patients, 78 with malignant SPLs (including 48 with adenocarcinoma [AC] and 17 with squamous cell carcinoma [SCC]), and 17 with benign SPLs.

FIELD STRENGTH/SEQUENCE

Fast spin-echo (FSE) T2WI, FSE APTw and echo-planar imaging IVIM, MR-base attenuation correction (MRAC), and PET imaging on a 3-T whole-body PET/MR system.

ASSESSMENT

The magnetization transfer ratio asymmetry (MTRasym) at 3.5 ppm, diffusion coefficient (D), pseudo diffusion coefficient (D*), perfusion fraction (f), and the maximum standardized uptake value (SUVmax) were analyzed.

STATISTICAL TESTS

Individual sample t-test, Delong test, Pearson's correlation analysis, and area under the receiver operating characteristic curve (AUC). P < 0.05 indicated statistical significance.

RESULTS

The MTRasym and SUVmax were significantly higher, and D was significantly lower in the malignant group (3.3 ± 2.6 [%], 7.8 ± 5, and 1.2 ± 0.3 [×10^-3  mm² /second]) compared to the benign group (-0.3 ± 1.6 [%], 3.1 ± 3.8, and 1.6 ± 0.3 [×10^-3  mm² /second]). The MTRasym and D were significantly lower, and SUVmax was significantly higher in the SCC group (0.8 ± 1.0 [%], 1.0 ± 0.2 [×10^-3  mm² /second] than in the AC group (4.1 ± 2.6 [%], 1.3 ± 0.3 [×10^-3  mm² /second], 6.7 ± 4.6). Besides, the combination (AUC = 0.964) of these three methods showed higher diagnostic efficacy than any individual method (AUC = 0.917, 0.851, 0.82, respectively) in identifying malignant and benign SPLs. However, APTw showed better diagnostic efficacy than the combination of three methods or PET imaging alone in distinguishing SCC and AC groups (AUC = 0.934, 0.781, 0.725, respectively).

DATA CONCLUSION

APTw, IVIM, and PET imaging are all effective methods to distinguish benign and malignant SPLs and their subtypes. APTw is potentially more capable than PET imaging of distinguishing lung SCC from AC.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 2.

Pulmonary Nodule and Mass: Superiority of MRI of Diffusion-Weighted Imaging and T2-Weighted Imaging to FDG-PET/CT

Simple Summary

Although diffusion-weighted imaging (DWI) can be valuable for differential diagnosis of lung cancer from benign pulmonary nodules and masses (PNMs), the diagnostic capability may not be perfect. This study’s purpose was to compare the diagnostic efficacy of 18-fluoro-2-deoxy-glucose positron emission tomography–computed tomography (FDG-PET/CT) and magnetic resonance imaging (MRI) of DWI and T2-weighted imaging (T2WI) in PNMs. There were 278 lung cancers and 50 benign PNMs that were examined by FDG-PET/CT and MRI. The sensitivity of the maximum standardized uptake value (SUVmax) was significantly lower than that of the apparent diffusion coefficient (ADC) and the T2 contrast ratio (T2 CR). The accuracy of SUVmax was significantly lower than that of ADC and that of T2 CR. The sensitivity and accuracy of MRI were significantly higher than those of FDG-PET/CT. MRI can replace FDG-PET/CT for differential diagnosis of PNMs.

Abstract

The purpose of this retrospective study was to compare the diagnostic efficacy of FDG-PET/CT and MRI in discriminating malignant from benign pulmonary nodules and masses (PNMs). There were 278 lung cancers and 50 benign PNMs that were examined by FDG-PET/CT and MRI. The T2 contrast ratio (T2 CR) was designated as the ratio of T2 signal intensity of PNM divided by T2 signal intensity of the rhomboid muscle. The optimal cut-off values (OCVs) for differential diagnosis were 3.605 for maximum standardized uptake value (SUVmax), 1.459 × 10⁻³ mm²/s for apparent diffusion coefficient (ADC), and 2.46 for T2 CR. Areas under the receiver operating characteristics curves were 67.5% for SUVmax, 74.3% for ADC, and 72.4% for T2 CR, respectively. The sensitivity (0.658) of SUVmax was significantly lower than that (0.838) of ADC (p < 0.001) and that (0.871) of T2 CR (p < 0.001). The specificity (0.620) of SUVmax was that the same as (0.640) ADC and (0.640) of T2 CR. The accuracy (0.652) of SUVmax was significantly lower than that (0.808) of ADC (p < 0.001) and that (0.835) of T2 CR (p < 0.001). The sensitivity and accuracy of DWI and T2WI in MRI were significantly higher than those of FDG-PET/CT. Ultimately, MRI can replace FDG PET/CT for differential diagnosis of PNMs saving healthcare systems money while not sacrificing the quality of care.

Discrimination between malignant and benign thyroid tumors by diffusion-weighted imaging - A systematic review and meta analysis

PURPOSE

Magnetic resonance imaging is used to stage thyroid tumors. Diffusion weighted imaging (DWI) and apparent diffusion coefficient (ADC) can be used to reflect tumor microstructure. Our aim was to compare ADC values of malignant and benign thyroid lesions based on a large sample.

METHODS

MEDLINE library, EMBASE and SCOPUS databases were screened for the associations between ADC values and thyroid lesions up to August 2021. The primary endpoint of the systematic review were ADC values of benign and malignant thyroid lesions. In total, 29 studies were suitable for the analysis and were included into the present study.

RESULTS

The included studies comprised a total of 2137 lesions, 1118 (52.3%) benign and 1019 (47.7%) malignant lesions. The pooled mean ADC value of the benign thyroid lesions was 1.88 × 10^-3 mm²/s [95% CI 1.77-2.0] and the pooled mean ADC value of malignant thyroid lesions was 1.15 × 10^-3 mm²/s [95% CI 1.04-1.25].

CONCLUSIONS

ADC can well discriminate benign and malignant thyroid tumors. Therefore, DWI should be implemented into the presurgical diagnostic work-up in clinical routine.

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.

Whole-lesion histogram analysis of mono-exponential and bi-exponential diffusion-weighted imaging in differentiating lung cancer from benign pulmonary lesions using 3 T MRI

AIM

To investigate whether whole-lesion histogram analysis of apparent diffusion coefficient (ADC) values derived from mono-exponential and bi-exponential diffusion-weighted imaging (DWI) can differentiate lung cancer from benign pulmonary lesions.

MATERIALS AND METHODS

Thirty-two patients with lung cancer and 17 patients with benign pulmonary lesions were included retrospectively. All patients underwent DWI before surgery or biopsy. ADC histogram parameters, including mean, percentile values (10^th and 90^th), kurtosis, and skewness, were calculated independently by two radiologists. The histogram parameters were compared between patients with lung cancer and benign lesions. Receiver operating characteristic curves were constructed to evaluate the diagnostic performance.

RESULTS

The ADC_Mean, ADC_10th, D_Mean, D_10th were significantly lower in lung cancer (1.187 ± 0.144 × 10^-3; 0.440 ± 0.062 × 10^-3; 1.068 ± 0.108 × 10^-3; and 0.422 ± 0.049 × 10^-3 mm/s) compared to benign lesions (1.418 ± 0.274 × 10^-3; 0.555 ± 0.113 × 10^-3; 1.216 ± 0.149 × 10^-3; and 0.490 ± 0.044 × 10^-3 mm/s; p<0.05). The ADC_Skewness and D_Skewness were significantly different between lung cancer (2.35 ± 0.72; 2.58 ± 1.14) and benign lesions (1.85 ± 0.54; 1.59 ± 1.47; p<0.05). D_10th was robust in differentiating lung cancer from benign lesions. Using 0.453 × 10^-3 mm/s as the optimal threshold, the sensitivity, specificity, and accuracy of D_10th were 78.12%, 82.35%, and 79.6%, respectively.

CONCLUSION

Whole-lesion histogram analysis of ADC values derived by mono-exponential and bi-exponential DWI using 3 T magnetic resonance imaging helps distinguish lung cancer from benign pulmonary lesions.

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.

B1 -Corrected T1 Mapping in Lung Cancer: Repeatability, Reproducibility, and Identification of Histological Types

BACKGROUND

T1 mapping can potentially quantitatively assess the intrinsic properties of tumors. B₁ correction can reduce the magnetic field inhomogeneity.

PURPOSE

To assess the repeatability and reproducibility of B₁ -corrected T1 mapping for lung cancer and the ability to identify pathological types.

STUDY TYPE

Prospective reproducibility study.

POPULATION

Sixty lung cancer patients (22 with emphysema) with a total of 60 lesions (adenocarcinoma [n = 23], squamous cell carcinoma [n = 19], and small-cell lung cancer [SCLC] [n = 18]).

FIELD STRENGTH/SEQUENCE

A 3 T/B₁ -corrected 3D variable flip angle T1 mapping and free-breathing diffusion-weighted imaging.

ASSESSMENT

Intraobserver, interobserver, and test-retest reproducibility of minimum, maximum, mean, and SD of lung tumor T1 values were assessed. The correlation between mean T1 and apparent diffusion coefficient (ADC) and differences between different histological types of lung cancer were evaluated.

STATISTICAL TESTS

Intraclass correlation coefficients (ICCs), within-subject coefficients of variation (WCVs), Bland-Altman plots, Pearson's correlation coefficient (r), and analysis of variance (ANOVA). A P value <0.05 was considered to be statistically significant.

RESULTS

No significant differences were found in minimum, maximum, mean, and SD T1 values for repeated measurements (intraobserver and interobserver) and repeated examinations (P = 0.103-0.979). All parameters showed good intraobserver, interobserver and test-retest reproducibility (ICC, 0.780-0.978), except the maximum T1 value (ICC, 0.645-0.922). The mean T1 exhibited the best reproducibility and repeatability, with an average difference <6% for repeated measurements, <8% for repeated scans in lung cancer patients, and<10% for repeated scans in those with emphysema. The mean T1 correlated moderately with ADC (r = -0.580, -0.516, and -0.511 for observers A, B, and C). Both mean T1 and mean ADC were significantly different in SCLC patients compared with those in adenocarcinoma and squamous cell carcinoma patients.

DATA CONCLUSION

The mean T1 from B₁ -corrected T1 mapping is a repeatable parameter with the potential to identify histological types of lung cancer and thus may be a promising imaging biomarker for characterizing lung cancer.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 2.

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.

Diagnostic Performance of Diffusion-Weighted Imaging for Differentiating Malignant From Benign Intraductal Papillary Mucinous Neoplasms of the Pancreas: A Systematic Review and Meta-Analysis

Objectives

To assess the diagnostic accuracy of diffusion-weighted imaging (DWI) in predicting the malignant potential in patients with intraductal papillary mucinous neoplasms (IPMNs) of the pancreas.

Methods

A systematic search of articles investigating the diagnostic performance of DWI for prediction of malignant potential in IPMNs was conducted from PubMed, Embase, and Web of Science from January 1997 to 10 February 2020. QUADAS-2 tool was used to evaluate the study quality. Pooled sensitivity, specificity, diagnostic odds ratio (DOR), positive likelihood ratios (PLR), negative likelihood ratios (NLR), and their 95% confidence intervals (CIs) were calculated. The summary receiver operating characteristic (SROC) curve was then plotted, and meta-regression was also performed to explore the heterogeneity.

Results

Five articles with 307 patients were included. The pooled sensitivity and specificity of DWI were 0.74 (95% CI: 0.65, 0.82) and 0.94 (95% CI: 0.78, 0.99), in evaluating the malignant potential of IPMNs. The PLR was 13.5 (95% CI: 3.1, 58.7), the NLR was 0.27 (95% CI: 0.20, 0.37), and DOR was 50.0 (95% CI: 11.0, 224.0). The area under the curve (AUC) of SROC curve was 0.84 (95% CI: 0.80, 0.87). The meta-regression showed that the slice thickness of DWI (p = 0.02) and DWI parameter (p= 0.01) were significant factors affecting the heterogeneity.

Conclusions

DWI is an effective modality for the differential diagnosis between benign and malignant IPMNs. The slice thickness of DWI and DWI parameter were the main factors influencing diagnostic specificity.

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.

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

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

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.

Diagnostic performance of apparent diffusion coefficient (ADC) for differentiating endometrial carcinoma from benign lesions: a systematic review and meta-analysis

To determine the diagnostic performance of mean ADC values in the characterization of endometrial carcinoma (EC) from benign lesions by systematic review of the literature and performing meta-analysis. A systematic search of major electronic bibliographic databases was performed to find studies that used ADC values for differentiating EC from benign lesions. Two reviewers independently screened the titles and abstracts of the search results and then by reading the full texts selected the pertinent studies for final analyses. A bivariate random-effects model with pooled sensitivity and specificity values with 95% CI (confidence interval) was used. Summary receiver operating characteristic (SROC) curve and area under curve (AUC) were created. Between-study heterogeneity was measured using I squared (I2) index. Eleven studies including 269 ECs and 208 benign lesions were analyzed. Pooled average (95% CI) ADC in EC and benign lesions groups were, respectively, 0.82 (0.77-0.87) × 10-3 mm2/s and 1.41 (1.29-1.52) × 10-3 mm2/s. The combined (95% CI) sensitivity and specificity of mean ADC values for differentiating EC from benign lesions were 93% (87-96%; I2 = 41.19%) and 94% (88-97%; I2 = 46.91%), respectively. The AUC (95% CI) of the SROC curve was 98% (96-99%). ADC values had good diagnostic accuracy for differentiating EC from benign lesions. In order to recommend ADC measurement for detecting endometrial lesions in routine clinical practice, more primary studies, especially trials and comparative studies including hysteroscopically-guided biopsy method, with larger sample sizes are still required.

Evaluation of DWI and ADC Sequences' Diagnostic Values in Benign and Malignant Pulmonary Lesions

OBJECTIVE

The gold standard for the diagnosis of lung cancer is conducting a histopathologic study. It is also diagnosed based on some features of a computed tomography (CT) scan. Imposed radiation is a prominent side effect of a CT scan. Diffusion-weighted imaging (DWI) apparent diffusion coefficient (ADC) images have currently been used in the diagnosis of different lesions, including those of the brain and breast, and their uses in lung lesions are being evaluated. In this study, to find a safe, sensitive, and specific method, we aimed to assess DWI imaging to replace the CT scan and the positron emission tomography scan.

MATERIAL AND METHODS

A total of 29 patients were enrolled in the study. In b800 images in DWI, spinal cord and lesion signals were measured, and the lesion-to-cord-signal ratio (LCR) was calculated. The ADC value was measured in a quantitative way. Lesions were also graded qualitatively in b800 DWI sequences.

RESULTS

There was a significant difference between malignant and benign lesions in terms of DWI grading in b800 images (p<0.001). There was a significant difference between ADC means of a malignant and benign lesion (p=0.003). The mean LCR for malignant lung lesions was significantly higher than that of the benign ones (p<0.001). Considering Grade 3 as the cutoff in DWI grading results in sensitivity, specificity, and accuracy of 89%, 90%, and 89.6%, respectively. For ADC values, sensitivity, specificity, and accuracy of 79%, 80%, and 79.3%, respectively, were obtained when the cutoff was 1.027×10^-3 sec/mm². The sensitivity of 84%, the specificity of 90%, and the accuracy of 86.2% were calculated for the LCR in a cutoff of 0.983. In this study, all three parameters had an area under the curve of ≥0.8, meaning that these variables were valuable for the differentiation of benign and malignant lesions.

CONCLUSION

Diffusion-weighted magnetic resonance imaging is a noninvasive tool, with no contrast agent and requiring ionizing radiations, which could be used for the qualitative, quantitative, and semiquantitative assessment of pulmonary lesions.

Free-breathing radial volumetric interpolated breath-hold examination sequence and dynamic contrast-enhanced MRI combined with diffusion-weighted imaging for assessment of solitary pulmonary nodules

OBJECTIVE

To test the performance of free-breathing Dynamic Contrast-Enhanced MRI (DCE-MRI) using a radial volumetric interpolated breath-hold examination (VIBE) sequence combined with diffusion-weighted imaging (DWI) for quantitative solitary pulmonary nodule (SPN) assessment.

METHODS

A total of 67 SPN cases receiving routine MRI routine scans, DWI, and dynamic-enhanced MRI in our hospital from May 2017 to November 2018 were collected. These cases were divided into a malignant group and a benign group according to the characteristics of the SPNs. The quantitative DCE-MRI parameters (K^trans, K_ep, V_e) and apparent diffusion coefficient (ADC) values of the nodules were measured.

RESULTS

The K^trans and K_ep values in the malignant group were higher than those in the benign group, while the ADC values in the malignant group were lower than those in the benign group. Furthermore, the K^trans value of adenocarcinoma was higher than that of squamous cell carcinoma and small cell carcinoma (P < 0.05). The V_e value was significantly different between non-small cell carcinoma and small cell carcinoma (P < 0.05). With an ADC value of 0.98 × 10^-3 mm²/s as the threshold, the specificity and sensitivity to diagnose benign and malignant nodules was 90.6% and 80%, respectively.

CONCLUSION

High-temporal-resolution DCE-MRI using the r-VIBE technique in combination with DWI could contribute to pulmonary nodule analysis and possibly serve as a potential alternative to distinguish malignant from benign nodules as well as differentiate different types of malignancies.

Histogram Analysis of ADC Maps for Differentiating Brain Metastases From Different Histological Types of Lung Cancers

PURPOSE

Our study aimed to investigate the role of histogram analysis derived from apparent diffusion coefficient (ADC) maps in brain metastases (BMs) from lung cancer for differentiating histological subtype.

METHODS

A total of 61 BMs (45 non-small cell lung cancer [NSCLC] comprising 32 adenocarcinoma [AC], 13 squamous cell carcinoma [SCC], and 16 small-cell lung cancer [SCLC]) in 50 patients with histopathologically confirmed lung cancer were retrospectively included in this study. Pretreatment cranial diffusion-weighted imaging was performed, and the corresponding ADC maps were generated. Regions of interest were drawn on solid components of the BM on all slices of the ADC maps to obtain parameters, including ADC_max, ADC_mean, ADC_min, ADC_median, ADC_range, skewness, kurtosis, entropy, ADC₁₀, ADC₂₅, ADC₇₅, and ADC₉₀. Apparent diffusion coefficient histogram parameters were compared among histological type groups. Kruskal-Wallis, Mann-Whitney U, chi-square tests, and receiver-operating characteristic (ROC) curve were used for statistical assessment.

RESULTS

ADC_min, ADC₁₀, and ADC₂₅ were found to be significantly different among AC, SCC, and SCLC groups; these parameters were higher for AC group, moderate for SCC group, and significantly lower for SCLC group. Skewness and kurtosis were not significantly different among all groups. The ROC analysis for differentiating BMs of NSCLC from SCLC showed that ADC₂₅ achieved the highest area under the curve at 0.922 with 93.02% sensitivity and 81.25% specificity.

CONCLUSION

Apparent diffusion coefficient histogram analysis of BMs from lung cancer has significant prognostic value in differentiating histological subtypes of lung cancer.

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.

Relationships and Qualitative Evaluation Between Diffusion-Weighted Imaging and Pathologic Findings of Resected Lung Cancers

For detecting malignant tumors, diffusion-weighted magnetic resonance imaging (DWI) as well as fluoro-2-deoxy-glucose positron emission tomography/computed tomography (FDG-PET/CT) are available. It is not definitive how DWI correlates the pathological findings of lung cancer. The aim of this study is to evaluate the relationships between DWI findings and pathologic findings. In this study, 226 patients with resected lung cancers were enrolled. DWI was performed on each patient before surgery. There were 167 patients with adenocarcinoma, 44 patients with squamous cell carcinoma, and 15 patients with other cell types. Relationships between the apparent diffusion coefficient (ADC) of DWI and the pathology were analyzed. When the optimal cutoff value (OCV) of ADC for diagnosing malignancy was 1.70 × 10⁻³ mm²/s, the sensitivity of DWI was 92.0% (208/226). The sensitivity was 33.3% (3/9) in mucinous adenocarcinoma. The ADC value (1.31 ± 0.32 × 10⁻³ mm²/s) of adenocarcinoma was significantly higher than that (1.17 ± 0.29 × 10⁻³ mm²/s) of squamous cell carcinoma (p = 0.012), or (0.93 ± 0.14 × 10⁻³ mm²/s) of small cell carcinoma (p = 0.0095). The ADC value (1.91 ± 0.36 × 10⁻³ mm²/s) of mucinous adenocarcinoma was significantly higher than that (1.25 ± 0.25 × 10⁻³ mm²/s) of adenocarcinoma with mucin and that (1.24 ± 0.30 × 10⁻³ mm²/s) of other cell types. The ADC (1.11 ± 0.26 × 10⁻³ mm²/s) of lung cancer with necrosis was significantly lower than that (1.32 ± 0.33 × 10⁻³ mm²/s) of lung cancer without necrosis. The ADC of mucinous adenocarcinoma was significantly higher than those of adenocarcinoma of other cell types. The ADC of lung cancer was likely to decrease according to cell differentiation decreasing. The sensitivity of DWI for lung cancer was 92% and this result shows that DWI is valuable for the evaluation of lung cancer. Lung cancer could be evaluated qualitatively using DWI.

Intravoxel Incoherent Motion Diffusion-Weighted Imaging of Lung Cancer: Comparison Between Turbo Spin-Echo and Echo-Planar Imaging

OBJECTIVE

The aim of the study was to compare intravoxel incoherent motion diffusion-weighted imaging (DWI) for evaluating lung cancer using single-shot turbo spin-echo (TSE) and single-shot echo-planar imaging (EPI) in a 3T MR system.

METHODS

Both single-shot TSE-DWI and single-shot EPI-DWI were scanned twice respectively for 15 patients with lung cancer. Distortion ratio, signal-to-noise ratio, and contrast-to-noise ratio were compared between the 2 techniques. The Bland-Altman analysis was performed to analyze reproducibility between the parameters of TSE-DWI and EPI-DWI. Short-term test-retest repeatability, as well as interobserver agreement, was evaluated using the coefficient of variation (CV) and the intraclass correlation coefficient (ICC).

RESULT

Turbo spin-echo DWI has lower signal-to-noise ratio and similar contrast-to-noise ratio compared with EPI-DWI. Distortion ratio of TSE-DWI was significantly smaller than that of EPI-DWI. The apparent diffusion coefficient (ADC) and true diffusivity (D) of TSE-DWI showed higher values than those of EPI-DWI. The Bland-Altman analysis showed unacceptable limits of agreement between these 2 sequences. Test-retest repeatability was good for ADC and D of EPI-DWI (CV, 14.11%-16.60% and 17.08%-19.53%) and excellent for ADC and D of TSE-DWI (CV, 4.8%-6.19% and 6.05%-8.71%), but relatively poor for perfusion fraction (f) and pseudo-diffusion coefficient (D*) (CV, 25.95%-27.70% and 56.92%-71.84% for EPI, 23.67%-28.67% and 60.85%-70.17% for TSE). For interobserver agreement, both techniques were good to excellent in ADC and D (The lower limit of 95% confidence interval for ICC was almost all greater than 0.75), whereas D* and f had higher interobserver variabilities with D* of TSE-DWI showing poorest reproducibility (ICC, -0.27 to 0.12).

CONCLUSIONS

Lung DWI or IVIM using TSE could provide distortion-free images and improve the test-retest robustness of ADC and D as compared with EPI-DWI; however, it might exert a negative effect on perfusion parameter D*.

Classification of pulmonary lesion based on multiparametric MRI: utility of radiomics and comparison of machine learning methods

OBJECTIVES

We develop and validate a radiomics model based on multiparametric magnetic resonance imaging (MRI) in the classification of the pulmonary lesion and identify optimal machine learning methods.

MATERIALS AND METHODS

This retrospective analysis included 201 patients (143 malignancies, 58 benign lesions). Radiomics features were extracted from multiparametric MRI, including T2-weighted imaging (T2WI), T1-weighted imaging (TIWI), and apparent diffusion coefficient (ADC) map. Three feature selection methods, including recursive feature elimination (RFE), t test, and least absolute shrinkage and selection operator (LASSO), and three classification methods, including linear discriminate analysis (LDA), support vector machine (SVM), and random forest (RF) were used to distinguish benign and malignant pulmonary lesions. Performance was compared by AUC, sensitivity, accuracy, precision, and specificity. Analysis of performance differences in three randomly drawn cross-validation sets verified the stability of the results.

RESULTS

For most single MR sequences or combinations of multiple MR sequences, RFE feature selection method with SVM classifier had the best performance, followed by RFE with RF. The radiomics model based on multiple sequences showed a higher diagnostic accuracy than single sequence for every machine learning method. Using RFE with SVM, the joint model of T1WI, T2WI, and ADC showed the highest performance with AUC = 0.88 ± 0.02 (sensitivity 83%; accuracy 82%; precision 91%; specificity 79%) in test set.

CONCLUSION

Quantitative radiomics features based on multiparametric MRI have good performance in differentiating lung malignancies and benign lesions. The machine learning method of RFE with SVM is superior to the combination of other feature selection and classifier methods.

KEY POINTS

• Radiomics approach has the potential to distinguish between benign and malignant pulmonary lesions. • Radiomics model based on multiparametric MRI has better performance than single-sequence models. • The machine learning methods RFE with SVM perform best in the current cohort.

Role of diffusion weighted MR-imaging in the evaluation of malignant mediastinal lesions

Background

Conducted studies showed that the ADC (apparent diffusion coefficient) values of malignant mediastinal lesions are significantly lower than those of benign lesions. Investigators determined cut-off ADC values to differentiate the two; concluding that ADC value is a promising noninvasive, imaging parameter that helps assess and characterize mediastinal tumors.

Taking this a step forward, the primary objective of our prospective study was to investigate the potential of DW-MRI (diffusion-weighted magnetic resonance imaging) to characterize malignant mediastinal lesions using their ADC values.

Thirty-three patients that underwent MRI of the chest with DWI and latter pathologically diagnosed with a malignant mediastinal lesion were included in this study. Lesions’ ADC values were measured and correlated with the histopathological results. The statistical significance of differences between measurements was tested using the one-way ANOVA (analysis of variance) test; p values equal to or less than 0.05 were considered significant.

Results

There was no statistically significant difference between the ADCmean values of the histopathological groups of lesions assessed with the overlap of their ADCmean values. The average ADCmean value of NHL (non-Hodgkin lymphoma) was evidently lower than that of HD (Hodgkin disease) with no overlap between their ADCmean values. DWI failed at characterizing one lesion in this study as a malignant tumor, namely an immature teratoma (germ-cell tumor). Again DWI could not be used to evaluate a mass, latter pathologically diagnosed as an angiosarcoma, because of its overall hemorrhagic nature showing no definite non-hemorrhagic soft tissue components. The aforementioned results did not differ considerably when minimum ADC was used instead of mean ADC.

Conclusion

There was no statistically significant difference between the ADC values of the malignant mediastinal lesions evaluated. However, regarding lymphoma subtypes, our limited sample study of lymphoma suggested a considerable difference between the ADC values of Hodgkin disease and non-Hodgkin lymphoma.

Correction for Magnetic Field Inhomogeneities and Normalization of Voxel Values Are Needed to Better Reveal the Potential of MR Radiomic Features in Lung Cancer

Purpose: To design and validate a preprocessing procedure dedicated to T2-weighted MR images of lung cancers so as to improve the ability of radiomic features to distinguish between adenocarcinoma and other histological types.

Materials and Methods: A discovery set of 52 patients with advanced lung cancer who underwent T2-weighted MR imaging at 3 Tesla in a single center study from August 2017 to May 2019 was used. Findings were then validated using a validation set of 19 additional patients included from May to October 2019. Tumor type was obtained from the pathology report after trans-thoracic needle biopsy, metastatic lymph node or metastasis samples, or surgical excisions. MR images were preprocessed using N4ITK bias field correction and by normalizing voxel intensities with fat as a reference region. Segmentation and extraction of radiomic features were performed with LIFEx software on the raw images, on the N4ITK-corrected images and on the fully preprocessed images. Two analyses were conducted where radiomic features were extracted: (1) from the whole tumor volume (3D analysis); (2) from all slices encompassing the tumor (2D analysis). Receiver operating characteristic (ROC) analysis was used to identify features that could distinguish between adenocarcinoma and other histological types. Sham experiments were also designed to control the number of false positive findings.

Results: There were 31 (12) adenocarcinomas and 21 (7) other histological types in the discovery (validation) set. In 2D, preprocessing increased the number of discriminant radiomic features from 8 without preprocessing to 22 with preprocessing. 2D analysis yielded more features able to identify adenocarcinoma than 3D analysis (12 discriminant radiomic features after preprocessing in 3D). Preprocessing did not increase false positive findings as no discriminant features were identified in any of the sham experiments. The greatest sensitivity of the 2D analysis applied to preprocessed data was confirmed in the validation set.

Conclusion: Correction for magnetic field inhomogeneities and normalization of voxel values are essential to reveal the full potential of radiomic features to identify the tumor histological type from MR T2-weighted images, with classification performance similar to those reported in PET/CT and in multiphase CT in lung cancers.

18F-fluorothymidine (FLT)-PET and diffusion-weighted MRI for early response evaluation in patients with small cell lung cancer: a pilot study

Background

Small cell lung cancer (SCLC) is an aggressive cancer often presenting in an advanced stage and prognosis is poor. Early response evaluation may have impact on the treatment strategy.

Aim

We evaluated ¹⁸F-fluorothymidine-(FLT)-PET/diffusion-weighted-(DW)-MRI early after treatment start to describe biological changes during therapy, the potential of early response evaluation, and the added value of FLT-PET/DW-MRI.

Methods

Patients with SCLC referred for standard chemotherapy were eligible. FLT-PET/DW-MRI of the chest and brain was acquired within 14 days after treatment start. FLT-PET/DW-MRI was compared with pretreatment FDG-PET/CT. Standardized uptake value (SUV), apparent diffusion coefficient (ADC), and functional tumor volumes were measured. FDG-SUV_peak, FLT-SUV_peak, and ADC_median; spatial distribution of aggressive areas; and voxel-by-voxel analyses were evaluated to compare the biological information derived from the three functional imaging modalities. FDG-SUV_peak, FLT-SUV_peak, and ADC_median were also analyzed for ability to predict final treatment response.

Results

Twelve patients with SCLC completed FLT-PET/MRI 1–9 days after treatment start. In nine patients, pretreatment FDG-PET/CT was available for comparison. A total of 16 T-sites and 12 N-sites were identified. No brain metastases were detected. FDG-SUV_peak was 2.0–22.7 in T-sites and 5.5–17.3 in N-sites. FLT-SUV_peak was 0.6–11.5 in T-sites and 1.2–2.4 in N-sites. ADC_median was 0.76–1.74 × 10^− 3 mm²/s in T-sites and 0.88–2.09 × 10⁻³ mm²/s in N-sites. FLT-SUV_peak correlated with FDG-SUV_peak, and voxel-by-voxel correlation was positive, though the hottest regions were dissimilarly distributed in FLT-PET compared to FDG-PET. FLT-SUV_peak was not correlated with ADC_median, and voxel-by-voxel analyses and spatial distribution of aggressive areas varied with no systematic relation. LT-SUV_peak was significantly lower in responding lesions than non-responding lesions (mean FLT-SUV_peak in T-sites: 1.5 vs. 5.7; p = 0.007, mean FLT-SUV_peak in N-sites: 1.6 vs. 2.2; p = 0.013).

Conclusions

FLT-PET and DW-MRI performed early after treatment start may add biological information in patients with SCLC. Proliferation early after treatment start measured by FLT-PET is a promising predictor for final treatment response that warrants further investigation.

Trial registration

Clinicaltrials.gov, NCT02995902. Registered 11 December 2014 - Retrospectively registered.

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.

Diffusion-Weighted Imaging Can Differentiate between Malignant and Benign Pleural Diseases

It is not clear whether magnetic resonance imaging (MRI) is useful for the assessment of pleural diseases. The aim of this study is to determine whether diffusion-weighted magnetic resonance imaging (DWI) can differentiate malignant pleural mesothelioma (MPM) from pleural dissemination of lung cancer, empyema or pleural effusion. The DWI was calibrated with the b value of 0 and 800 s/mm². There were 11 MPMs (8 epithelioid and 3 biphasic), 10 pleural disseminations of lung cancer, 10 empyemas, and 12 pleural effusions. The apparent diffusion coefficient (ADC) of the pleural diseases was 1.22 ± 0.25 × 10⁻³ mm²/s in the MPMs, 1.31 ± 0.49 × 10⁻³ mm²/s in the pleural disseminations, 2.01 ± 0.45 × 10⁻³ mm²/s in the empyemas and 3.76 ± 0.62 × 10⁻³ mm²/s in the pleural effusions. The ADC of the MPMs and the pleural disseminations were significantly lower than the ADC of the empyemas and the pleural effusions. Concerning the diffusion pattern of DWI, all 11 MPMs showed strong continuous diffusion, 9 of 10 pleural disseminations showed strong scattered diffusion and 1 pleural dissemination showed strong continuous diffusion, all 10 empyemas showed weak continuous diffusion, and all 12 pleural effusions showed no decreased diffusion. DWI can evaluate pleural diseases morphologically and qualitatively, and thus differentiate between malignant and benign pleural diseases.

Diffusion-weighted magnetic resonance imaging is useful for the response evaluation of chemotherapy and/or radiotherapy to recurrent lesions of lung cancer

Diffusion-weighted magnetic resonance imaging (DWI) has been reported to be useful for the assessment of lung cancer staging. It is uncertain whether DWI is more accurate for the response evaluation of chemotherapy and/or radiotherapy compared to computed tomography (CT). The purpose of this study is to compare the response evaluation of DWI for chemotherapy and/or radiotherapy to recurrent tumors of lung cancer with that of CT which is a standard tool in RECIST (Response Evaluation Criteria in Solid Tumours). Forty-one patients who agreed to this project and had CT scan and DWI examinations within a month of each other every six months for at least 2 years after pulmonary resection of primary lung cancer were enrolled in this study. Of the patients, 24 patients had metastases or recurrences, and CT and DWI were performed for assessment of the response evaluation of chemotherapy and/or radiotherapy to recurrent lesions. They were followed up for at least two years after the relapse. The response evaluation by CT using RECIST were PR in five patients, SD in two, and PD in the remaining 17 patients. On the other hand, the response evaluation by DWI were CR in four patients, PR in two patients, SD in one, and PD in the remaining 17 patients. Follow-up studies revealed the response evaluation by DWI were correct. Functional evaluation of DWI is better than that of CT for the response evaluation of chemotherapy and/or radiotherapy to recurrent tumors of lung cancer.

A Radiomics Signature in Preoperative Predicting Degree of Tumor Differentiation in Patients with Non-small Cell Lung Cancer

RATIONALE AND OBJECTIVES

Poorly differentiated non-small cell lung cancer (NSCLC) indicated a poor prognosis and well-differentiated NSCLC indicates a noninvasive nature and good prognosis. The purpose of this study was to build and validate a radiomics signature to predict the degree of tumor differentiation (DTD) for patients with NSCLC.

MATERIALS AND METHODS

A total of 487 patients with pathologically diagnosed NSCLC were retrospectively included in our study. Five hundred ninety-one radiomics features were extracted from each tumor from the contrast-enhanced computed tomography images. A minimum redundancy maximum relevance algorithm and a logistic regression model were used for dimension reduction, feature selection, and radiomics signature building. The performance of the radiomics signature was assessed using receiver operating characteristic analysis, and the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy were calculated to quantify the association between a signature and DTD. An independent validation set contained 184 consecutive patients with NSCLC.

RESULTS

A nine-radiomics-feature-based signature was built and it could differentiate low and high DTDs in the training set (AUC = 0.763, sensitivity = 0.750, specificity = 0.665, and accuracy = 0.687), and the radiomics signature had good discrimination performance in the validation set (AUC = 0.782, sensitivity = 0.608, specificity = 0.752, and accuracy = 0.712).

CONCLUSIONS

A radiomics signature based on contrast-enhanced computed tomography imaging is a potentially useful imaging biomarker for differentiating low from high DTD in patients with NSCLC.

Conventional MRI to detect the differences between mass-like tuberculosis and lung cancer

Background

The aim of this study was to investigate differences in the imaging features of mass-like tuberculosis and lung cancer on conventional MR sequences to improve the diagnostic ability for pulmonary masses.

Methods

Thirty patients with suspicious pulmonary lesions were enrolled and diagnosed with tuberculosis by pathology or comprehensive clinical diagnoses. Twenty-six cases of lung cancer were retrospectively analyzed. Transverse fat-suppressed T2-weighted (T2W) imaging and T1-weighted (T1W) imaging were obtained at 1.5 Tesla. The imaging characteristics of lesions on the T2W and T1W images were compared between the two groups. The imaging features of enlarged mediastinal lymph nodes on T2W images were studied and compared.

Results

On T2W images, there was a higher percentage of lesions containing hypointensity in the tuberculosis group (GTB) than in the lung cancer group (GLC) (P=0.004).The incidence of lesions demonstrating heterogeneous intensity was significantly greater in the GTB than in the GLC (70.0% vs. 7.7%, P=0.001). Approximately 92.3% of the lung cancer cases showed hyperintensity, a proportion substantially greater than that in the GTB (6.7%). On T1W images, more cases showed hyperintensity in the GTB than in the GLC (43.3% vs. 7.7%, P=0.003). The signal intensity ratios (SIRs) of the lesion to rhomboid muscle on T2W and T1W images were significantly different between the two groups. The mean intrasubject standard deviation (SD) of lesions in the GTB was markedly greater than that in the GLC on both T2W and T1W images. Benign mediastinal lymph nodes in the GTB showed a variety of signals on T2W images, whereas 80% of metastatic mediastinal lymph nodes displayed slight homogeneous hyperintensity, and this difference between the two groups was statistically significant.

Conclusions

Conventional MR sequences can reveal the essential differences between mass-like tuberculosis and lung cancer and may be helpful for discriminating pulmonary masses.

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.

Correlation of the apparent diffusion coefficient and the standardized uptake value in neoplastic lesions: a meta-analysis

OBJECTIVE

Diffusion-weighted imaging and fluorine-18-fluorodeoxyglucose PET are increasingly being recognized as feasible oncological techniques. The apparent diffusion coefficient (ADC) measured by diffusion-weighted imaging and the standardized uptake value (SUV) from fluorine-18-fluorodeoxyglucose PET have similar clinical applications. The aim of this study was to assess the correlation between these two parameters in various cancers.

MATERIALS AND METHODS

Several major databases were searched for eligible studies. The correlation coefficient (ρ) values were pooled in a random-effects model. Begg's test was used to analyze the existence of publication bias and the sources of heterogeneity were explored in subgroup analyses on the basis of study design, diagnostic method, scanning modality, and tumor type.

RESULTS

Thirty-five articles were accepted. The pooled ρ value of all of the accepted studies was -0.30 (95% confidence interval: -0.33 to -0.27), and notable heterogeneity was present (I=69.4%, P<0.001), which indicated a relatively weak negative correlation. The pooled ρ values were -0.26, -0.33, -0.32, and -0.33 for the SUVmax/ADCmean, SUVmax/ADCmin, SUVmean/ADCmean, and SUVmean/ADCmin relationships, respectively. The study design and diagnostic method were potential sources of heterogeneity. Lung cancer showed a stronger correlation (ρ=-0.42) than head and neck cancer (ρ=-0.27), cervical cancer (ρ=-0.21), and breast cancer (ρ=-0.23). A Begg's test indicated no significant publication bias among the accepted studies (P>0.05).

CONCLUSION

The two functional parameters of ADC and SUV showed a very weak inverse correlation, which may contribute toward a sophisticated characterization of tumor biology. However, the findings require further validation with trials with large samples and different tumor types.