Biexponential apparent diffusion coefficients values in the prostate: comparison among normal tissue, prostate cancer, benign prostatic hyperplasia and prostatitis

Improved effects of the b-value for 2000 sec/mm2 DWI on an accurate qualitative and quantitative assessment of rectal cancer

BACKGROUND AND STUDY OBJECTIVES

A higher b-value Diffusion-weighted imaging (DWI) would improve the contrast between cancerous and noncancerous tissue. Apparent diffusion coefficient (ADC)-histogram analysis is a method that can provide statistical data and quantitative information on tumor heterogeneity. This study aimed to compare two high b-values (1000 and 2000 sec/mm2) DWI in tumor detection and diagnostic performance in identifying early-stage tumor rectal cancer.

PATIENTS AND METHODS

This blinded and blinded retrospective study involved 56 patients with rectal cancer and 45 patients. Two radiologists evaluated the qualitative detection parameters and quantitative parameters of the ADC evaluated histogram and compared them between two DWI sequences (b-value for 1000 sec/mm2 and 2000 sec/mm2). The characteristic curves were used to assess diagnostic administration for the ADC histogram in discriminating early-stage tumors.

RESULTS

The b-value for 2000 sec/mm2 DWI significantly improved AUCs, sensitivity, specificity, and precision and decreased false-positive rate for detection compared to the b-value for 1000 sec/mm2 (p < 0.05). The mean and fifth percentile ADC value for stage I using the b-value for 1000 sec/mm2 DWI was significantly higher than stage ≥ II (p = 0.036II and 0.016 respectively), as the well as fifth, 10th, mean ADC of the fifth, 10th, and 25th ADC percentile at b-value for 2000 sec/mm2 (p = 0.031, 0.014, 0.035 and 0.025 respectively). The AUCs of the fifth percentile ADC at b-value for 2000 sec/mm2 DWI in both readers in differentiating the stage Ⅰ tumor were the highest (0.732 and 0.751).

CONCLUSION

The b-value for 2000 sec/mm2 DWI could improve the accurate detection of rectal cancer. The fifth percentile ADC at b-value for 2000 sec/mm2 sec/mm2 DWI was more useful for discriminating early stage than the b-value for 1000 sec/mm2 DWI.

Automatic detection of prostate cancer grades and chronic prostatitis in biparametric MRI

BACKGROUND AND OBJECTIVE

With emerging evidence to improve prostate cancer (PCa) screening, multiparametric magnetic prostate imaging is becoming an essential noninvasive component of the diagnostic routine. Computer-aided diagnostic (CAD) tools powered by deep learning can help radiologists interpret multiple volumetric images. In this work, our objective was to examine promising methods recently proposed in the multigrade prostate cancer detection task and to suggest practical considerations regarding model training in this context.

METHODS

We collected 1647 fine-grained biopsy-confirmed findings, including Gleason scores and prostatitis, to form a training dataset. In our experimental framework for lesion detection, all models utilized 3D nnU-Net architecture that accounts for anisotropy in the MRI data. First, we explore an optimal range of b-values for diffusion-weighted imaging (DWI) modality and its effect on the detection of clinically significant prostate cancer (csPCa) and prostatitis using deep learning, as the optimal range is not yet clearly defined in this domain. Next, we propose a simulated multimodal shift as a data augmentation technique to compensate for the multimodal shift present in the data. Third, we study the effect of incorporating the prostatitis class alongside cancer-related findings at three different granularities of the prostate cancer class (coarse, medium, and fine) and its impact on the detection rate of the target csPCa. Furthermore, ordinal and one-hot encoded (OHE) output formulations were tested.

RESULTS

An optimal model configuration with fine class granularity (prostatitis included) and OHE has scored the lesion-wise partial Free-Response Receiver Operating Characteristic (FROC) area under the curve (AUC) of 1.94 (CI 95%: 1.76-2.11) and patient-wise ROC AUC of 0.874 (CI 95%: 0.793-0.938) in the detection of csPCa. Inclusion of the auxiliary prostatitis class has demonstrated a stable relative improvement in specificity at a false positive rate (FPR) of 1.0 per patient, with an increase of 3%, 7%, and 4% for coarse, medium, and fine class granularities.

CONCLUSIONS

This paper examines several configurations for model training in the biparametric MRI setup and proposes optimal value ranges. It also shows that the fine-grained class configuration, including prostatitis, is beneficial for detecting csPCa. The ability to detect prostatitis in all low-risk cancer lesions suggests the potential to improve the quality of the early diagnosis of prostate diseases. It also implies an improved interpretability of the results by the radiologist.

Differential diagnosis of prostate cancer and benign prostatic hyperplasia based on DCE-MRI using bi-directional CLSTM deep learning and radiomics

Dynamic contrast-enhanced MRI (DCE-MRI) is routinely included in the prostate MRI protocol for a long time; its role has been questioned. It provides rich spatial and temporal information. However, the contained information cannot be fully extracted in radiologists' visual evaluation. More sophisticated computer algorithms are needed to extract the higher-order information. The purpose of this study was to apply a new deep learning algorithm, the bi-directional convolutional long short-term memory (CLSTM) network, and the radiomics analysis for differential diagnosis of PCa and benign prostatic hyperplasia (BPH). To systematically investigate the optimal amount of peritumoral tissue for improving diagnosis, a total of 9 ROIs were delineated by using 3 different methods. The results showed that bi-directional CLSTM with ± 20% region growing peritumoral ROI achieved the mean AUC of 0.89, better than the mean AUC of 0.84 by using the tumor alone without any peritumoral tissue (p = 0.25, not significant). For all 9 ROIs, deep learning had higher AUC than radiomics, but only reaching the significant difference for ± 20% region growing peritumoral ROI (0.89 vs. 0.79, p = 0.04). In conclusion, the kinetic information extracted from DCE-MRI using bi-directional CLSTM may provide helpful supplementary information for diagnosis of PCa.

Lymph Nodes Evaluation in Rectal Cancer: Where Do We Stand and Future Perspective

The assessment of nodal involvement in patients with rectal cancer (RC) is fundamental in disease management. Magnetic Resonance Imaging (MRI) is routinely used for local and nodal staging of RC by using morphological criteria. The actual dimensional and morphological criteria for nodal assessment present several limitations in terms of sensitivity and specificity. For these reasons, several different techniques, such as Diffusion Weighted Imaging (DWI), Intravoxel Incoherent Motion (IVIM), Diffusion Kurtosis Imaging (DKI), and Dynamic Contrast Enhancement (DCE) in MRI have been introduced but still not fully validated. Positron Emission Tomography (PET)/CT plays a pivotal role in the assessment of LNs; more recently PET/MRI has been introduced. The advantages and limitations of these imaging modalities will be provided in this narrative review. The second part of the review includes experimental techniques, such as iron-oxide particles (SPIO), and dual-energy CT (DECT). Radiomics analysis is an active field of research, and the evidence about LNs in RC will be discussed. The review also discusses the different recommendations between the European and North American guidelines for the evaluation of LNs in RC, from anatomical considerations to structured reporting.

Use of diffusion-weighted magnetic resonance imaging (DW-MRI) to predict early response to anti-tumor therapy in advanced non-small cell lung cancer (NSCLC): a comparison of intravoxel incoherent motion-derived parameters and apparent diffusion coefficient

Background

The intravoxel incoherent motion (IVIM) method of magnetic resonance imaging (MRI) analysis can provide information regarding many physiological and pathological processes. This study aimed to investigate whether IVIM-derived parameters and the apparent diffusion coefficient (ADC) can act as imaging biomarkers for predicting non-small cell lung cancer (NSCLC) response to anti-tumor therapy and compare their performances.

Methods

This prospective study included 45 patients with NSCLC treated with chemotherapy (29 men and 16 women, mean age 57.9±9.7 years). Diffusion-weighted imaging was performed with 13 b-values before and 2–4 weeks after treatment. The IVIM parameter pseudo-diffusion coefficient (D*), perfusion fraction (f), diffusion coefficient (D), and ADC from a mono-exponential model were obtained. Responses 2 months after chemotherapy were assessed. The diagnostic performance was evaluated, and optimal cut-off values were determined by receiver operating characteristic (ROC) curve analysis, and the differences of progression-free survival (PFS) in groups of responders and non-responders were tested by Cox regression and Kaplan-Meier survival analyses.

Results

Of 45 patients, 30 (66.7%) were categorized as responders, and 15 as non-responders. Differences in the diffusion coefficient D and ADC between responders and non-responders were statistically significant (all P<0.05). Conversely, differences in f and D* between responders and non-responders were both not statistically significance (all P>0.05). The ROC analyses showed the change in D value (ΔD) was the best predictor of early response to anti-tumor therapy [area under the ROC curve (AUC), 0.764]. The Cox-regression model showed that all ADC and D parameters were independent predictors of PFS, with a range of reduction in risk from 56.2% to 82.7%, and ΔD criteria responders had the highest reduction (82.7%).

Conclusions

ADC and D derived from IVIM are potentially useful for the prediction of NSCLC treatment response to anti-tumor therapy. Although ΔD is best at predicting response to treatment, ΔADC measurement may simplify manual efforts and reduce the workload.

Diagnostic accuracy of multiparametric magnetic resonance imaging combined with clinical parameters in the detection of clinically significant prostate cancer: A novel diagnostic model

OBJECTIVES

To evaluate the diagnostic accuracy of multiparametric magnetic resonance imaging in the detection of prostate cancer, according to Prostate Imaging Reporting and Data System, and the usefulness of combining clinical parameters to improve patients' risk assessment.

METHODS

Overall, 201 patients underwent multiparametric magnetic resonance imaging investigation with a 3-T magnet and a 32-channel body coil based on triplanar high-resolution T2-weighted, diffusion-weighted and T1-weighted dynamic contrast-enhanced imaging before, during and after intravenous administration of paramagnetic contrast agent. Random transrectal ultrasound-guided biopsy was carried out for all eligible patients. If a Prostate Imaging Reporting and Data System ≥3 lesion was present, a targeted biopsy with magnetic resonance imaging-transrectal ultrasound fusion-guided system was carried out.

RESULTS

Sensitivity, specificity, positive predictive value and negative predictive value of Prostate Imaging Reporting and Data System ≥3 lesions for the detection of prostate cancer were 65.1%, 54.9%, 43.1% and 75.0% respectively, with an accuracy of 64.2% (55.1-72.7%). At uni- and multivariate analysis, age ≥70 years and prostate-specific antigen density ≥0.15 ng/mL/mL were significantly associated with prostate cancer. A new risk model named "modified Prostate Imaging Reporting and Data System" was created considering age and prostate-specific antigen density in addition to the Prostate Imaging Reporting and Data System score showing an improved correlation with prostate cancer compared with the Prostate Imaging Reporting and Data System alone (area under curve 71.4%, 95% confidence interval 62.2-80.5 vs area under curve 62.6%, 95% confidence interval 52.1-73; P ≤ 0.0001).

CONCLUSIONS

The accuracy of Prostate Imaging Reporting and Data System alone in the diagnosis of prostate cancer might be suboptimal, whereas a novel risk model based on the combination of multiparametric magnetic resonance imaging data with clinical parameters could offer higher discrimination and improve the ability of diagnosing clinically significant disease.

Application of hierarchical clustering to multi-parametric MR in prostate: Differentiation of tumor and normal tissue with high accuracy

PURPOSE

Hierarchical clustering (HC), an unsupervised machine learning (ML) technique, was applied to multi-parametric MR (mp-MR) for prostate cancer (PCa). The aim of this study is to demonstrate HC can diagnose PCa in a straightforward interpretable way, in contrast to deep learning (DL) techniques.

METHODS

HC was constructed using mp-MR including intravoxel incoherent motion, diffusion kurtosis imaging, and dynamic contrast-enhanced MRI from 40 tumor and normal tissues in peripheral zone (PZ) and 23 tumor and normal tissues in transition zone (TZ). HC model was optimized by assessing the combinations of several dissimilarity and linkage methods. Goodness of HC model was validated by internal methods.

RESULTS

Accuracy for differentiating tumor and normal tissue by optimal HC model was 96.3% in PZ and 97.8% in TZ, comparable to current clinical standards. Relationship between input (DWI and permeability parameters) and output (tumor and normal tissue cluster) was shown by heat maps, consistent with literature.

CONCLUSION

HC can accurately differentiate PCa and normal tissue, comparable to state-of-the-art diffusion based parameters. Contrary to DL techniques, HC is an operator-independent ML technique producing results that can be interpreted such that the results can be knowledgeably judged.

Prostatitis, the Great Mimicker of Prostate Cancer: Can We Differentiate Them Quantitatively With Multiparametric MRI?

OBJECTIVE. The purpose of this study was to investigate the diagnostic performance of semiquantitative and quantitative pharmacokinetic parameters and quantitative apparent diffusion coefficient (ADC) values obtained from prostate multiparametric MRI (mpMRI) to differentiate prostate cancer (PCa) and prostatitis objectively. MATERIALS AND METHODS. We conducted a retrospective review of patients with biopsy-proven PCa or prostatitis who underwent mpMRI study between January 2015 and February 2018. Mean ADC, forward volume transfer constant (K^trans), reverse volume transfer constant (k_ep), plasma volume fraction (V_p), extravascular extracellular space volume fraction (V_e), and time to peak (TTP) values were calculated for both lesions and contralateral normal prostate tissue. Signal intensity-time curves were analyzed. Lesion-to-normal prostate tissue ratios of pharmacokinetic parameters were also calculated. The diagnostic accuracy and cutoff points of all parameters were analyzed to differentiate PCa from prostatitis. RESULTS. A total of 138 patients (94 with PCa and 44 with prostatitis) were included in the study. Statistically, ADC, quantitative pharmacokinetic parameters (K^trans, k_ep, V_e, and V_p), their lesion-to-normal prostate tissue ratios, and TTP values successfully differentiated PCa and prostatitis. Surprisingly, we found that V_e values were significantly higher in prostatitis lesions. The combination of these parameters had 92.7% overall diagnostic accuracy. ADC, k_ep, and TTP made up the most successful combination for differential diagnosis. Analysis of the signal intensity-time curves showed mostly type 2 and type 3 enhancement curve patterns for patients with PCa. Type 3 curves were not seen in any prostatitis cases. CONCLUSION. Quantitative analysis of mpMRI differentiates PCa from prostatitis with high sensitivity and specificity, appears to have significant potential, and may improve diagnostic accuracy. In addition, evaluating these parameters does not cause any extra burden to the patients.

Investigating the value of arterial spin labeling and intravoxel incoherent motion imaging on diagnosing nasopharyngeal carcinoma in T1 stage

BACKGROUND

To investigate the diagnostic value of arterial spin labeling (ASL) and intravoxel incoherent motion (IVIM) imaging in distinguishing nasopharyngeal carcinoma (NPC) in T1 stage from healthy controls (HC).

METHODS

Forty-five newly diagnosed NPC patients in the T1 stage and thirty-one healthy volunteers who underwent MR examinations for both 3D pseudo-continuous ASL (pCASL) and IVIM were enrolled in this study. The Mann-Whitney test was used to compare the mean values of blood flow (BF) derived from pCASL and IVIM derived parameters, including apparent diffusion coefficient (ADC), pure molecular diffusion (D), pseudo-diffusion coefficient (D*) and perfusion fraction (f) between NPC tumor and benign nasopharyngeal mucosa of HC. Receiver Operating Characteristic (ROC) was performed to determine diagnostic cutoff and efficiency. The correlation coefficients among parameters were investigated using Spearman's test.

RESULTS

The NPC in the T1 stage showed higher mean BF, lower ADC, D, and f compared to benign nasopharyngeal mucosa (P < 0.001) with the area under curve of ROC of 0.742-0.996 (highest by BF). BF cutoff was set at > 36 mL/100 g/min; the corresponding sensitivity, specificity, and accuracy in differentiating NPC stage T1 from benign nasopharyngeal mucosa were 95.56% (43/45), 100% (31/31) and 97.37% (74/76), respectively. BF demonstrated moderate negative correlation with D* on HC (ρ [Spearman correlation coefficients] = - 0.426, P = 0.017).

CONCLUSIONS

ASL and IVIM could reflect the difference in perfusion and diffusion between tumor and benign nasopharyngeal mucosa, indicating a potential for accessing early diagnosis of NPC. Notably, BF, with a specificity of 100%, demonstrated better performance compared to IVIM in distinguishing malignant lesions from healthy tissue.

Prostate magnetic resonance imaging technique

Multiparametric magnetic resonance (MR) imaging of the prostate is an excellent tool to detect clinically significant prostate cancer, and it has widely been incorporated into clinical practice due to its excellent tissue contrast and image resolution. The aims of this article are to describe the prostate MR imaging technique for detection of clinically significant prostate cancer according to PI-RADS v2.1, as well as alternative sequences and basic aspects of patient preparation and MR imaging artifact avoidance.

Non-Gaussian models of diffusion weighted imaging for detection and characterization of prostate cancer: a systematic review and meta-analysis

The importance of Diffusion Weighted Imaging (DWI) in prostate cancer (PCa) diagnosis have been widely handled in literature. In the last decade, due to the mono-exponential model limitations, several studies investigated non-Gaussian DWI models and their utility in PCa diagnosis. Since their results were often inconsistent and conflicting, we performed a systematic review of studies from 2012 examining the most commonly used Non-Gaussian DWI models for PCa detection and characterization. A meta-analysis was conducted to assess the ability of each Non-Gaussian model to detect PCa lesions and distinguish between low and intermediate/high grade lesions. Weighted mean differences and 95% confidence intervals were calculated and the heterogeneity was estimated using the I² statistic. 29 studies were selected for the systematic review, whose results showed inconsistence and an unclear idea about the actual usefulness and the added value of the Non-Gaussian model parameters. 12 studies were considered in the meta-analyses, which showed statistical significance for several non-Gaussian parameters for PCa detection, and to a lesser extent for PCa characterization. Our findings showed that Non-Gaussian model parameters may potentially play a role in the detection and characterization of PCa but further studies are required to identify a standardized DWI acquisition protocol for PCa diagnosis.

Preoperative PI-RADS Version 2 scores helps improve accuracy of clinical nomograms for predicting pelvic lymph node metastasis at radical prostatectomy

BACKGROUND

Lymph node invasion (LNI) is a strong adverse prognostic factor in prostate cancer (PCa). The purpose of this study was to evaluate the role of Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) scores for estimating the risk of LN metastasis. The study also aimed to investigate the additional value of PI-RADSv2 scores when used in combination with clinical nomograms for the prediction of LNI in patients with PCa.

METHODS

We retrospectively identified 308 patients who underwent multiparametric magnetic resonance imaging (mpMRI) and RP with pelvic lymph node dissection (PLND). Clinicopathological parameters and PI-RADSv2 scores were assessed. Univariate and multivariate logistic analyses were performed. The area under the receiver operating characteristic curves (AUCs) and decision curve analysis (DCA) were generated for assessing the incremental value of PI-RADSv2 scores combined with the Briganti and Memorial Sloan Kettering Cancer Center (MSKCC) nomograms.

RESULTS

Overall, 20 (6.5%) patients had LNI. At univariate analysis, all clinicopathological characteristics and PI-RADSv2 scores were significantly associated to LNI (p < 0.04). However, multivariate analysis revealed that only PI-RADSv2 scores and percentage of positive cores were independently significant (p ≤ 0.006). The PI-RADSv2 score was the most accurate predictor (AUC, 80.2%). The threshold of PI-RADSv2 score was 5, which provided high sensitivity (18/20, 90.0%) and negative predictive value (203/205, 99.0%). When PI-RADSv2 scores were combined with Briganti and MSKCC nomograms, the AUC value increased from 75.1 to 86.3% and from 79.2 to 87.9%, respectively (p ≤ 0.001). The DCA also demonstrated that the two nomograms plus PI-RADSv2 scores improved clinical risk prediction of LNI.

CONCLUSIONS

The patients with a PI-RADSv2 score <5 were associated with a very low risk of LNI in PCa. Preoperative PI-RADSv2 scores could help improve the accuracy of clinical nomograms for predicting pelvic LN metastasis at radical prostatectomy.

Selection and Reporting of Statistical Methods to Assess Reliability of a Diagnostic Test: Conformity to Recommended Methods in a Peer-Reviewed Journal

Objective

To evaluate the frequency and adequacy of statistical analyses in a general radiology journal when reporting a reliability analysis for a diagnostic test.

Materials and Methods

Sixty-three studies of diagnostic test accuracy (DTA) and 36 studies reporting reliability analyses published in the Korean Journal of Radiology between 2012 and 2016 were analyzed. Studies were judged using the methodological guidelines of the Radiological Society of North America-Quantitative Imaging Biomarkers Alliance (RSNA-QIBA), and COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) initiative. DTA studies were evaluated by nine editorial board members of the journal. Reliability studies were evaluated by study reviewers experienced with reliability analysis.

Results

Thirty-one (49.2%) of the 63 DTA studies did not include a reliability analysis when deemed necessary. Among the 36 reliability studies, proper statistical methods were used in all (5/5) studies dealing with dichotomous/nominal data, 46.7% (7/15) of studies dealing with ordinal data, and 95.2% (20/21) of studies dealing with continuous data. Statistical methods were described in sufficient detail regarding weighted kappa in 28.6% (2/7) of studies and regarding the model and assumptions of intraclass correlation coefficient in 35.3% (6/17) and 29.4% (5/17) of studies, respectively. Reliability parameters were used as if they were agreement parameters in 23.1% (3/13) of studies. Reproducibility and repeatability were used incorrectly in 20% (3/15) of studies.

Conclusion

Greater attention to the importance of reporting reliability, thorough description of the related statistical methods, efforts not to neglect agreement parameters, and better use of relevant terminology is necessary.

Comparison of biexponential and monoexponential DWI in evaluation of Fuhrman grading of clear cell renal cell carcinoma

PURPOSE

Clear cell renal cell carcinoma (ccRCC) is the most common primary malignant urologic tumor. The Fuhrman grading system is an independent indicator for aggressiveness and prognosis of ccRCC. We aimed to assess the possible diagnostic role of biexponentially and monoexponentially fitted signal attenuation for the Fuhrman grading.

METHODS

A total of 33 patients with ccRCC underwent multiple b values (0, 20, 50, 100, 150, 250, 400, 600, 800, 1000 s/mm2) diffusion-weighted imaging (DWI). Biexponential parameters (fast ADC [ADCf], slow ADC [ADCs], and fraction of ADCf [f]) and monoexponential apparent diffusion coefficient were calculated, and correlated with the Fuhrman grade of ccRCC respectively. The performance of biexponential parameters in differentiating Fuhrman low- and high-grade tumors was assessed and compared with ADC value by receiver operating characteristic analysis.

RESULTS

Qualified images and diffusion-weighted parameters were obtained for all patients. The ADCf and f value were positively correlated, whereas ADCs and ADC value were negatively correlated with Fuhrman grade. Significant differences were observed in ADCf (P < 0.001), ADCs (P = 0.005), and f values (P < 0.001) of high- and low-grade ccRCCs. When differentiating Fuhrman low-grade tumors from high-grade, the ADCf revealed an area under receiver operating characteristic curve of 0.959, which was higher than the ADC value (0.789; P = 0.046), while ADCs (0.807) and f (0.833) showed no significant difference from ADC (P = 0.85 for ADCs, P = 0.73 for f).

CONCLUSION

Biexponential DWI provides additional parameters for ccRCC. ADCf is more accurate compared with the ADC value in characterizing Fuhrman grade of ccRCC.

A preliminary exploration of the intravoxel incoherent motion applied in the preoperative evaluation of mediastinal lymph node metastasis of lung cancer

BACKGROUND

The aim of this study was to investigate the diagnostic value of the intravoxel incoherent motion (IVIM) for distinguishing non-metastatic from metastatic mediastinal lymph nodes in lung cancer.

METHODS

IVIM-diffusion weighted imaging (DWI) exams were performed preoperatively on 66 patients with lung cancer from October 2015 to June 2016 in Beijing Chao-Yang Hospital, Capital Medical University. Fifty patients underwent enhanced chest computed tomography (CT) in our hospital, while the other 16 patients already had enhanced chest CT images when they were admitted. The patients' complete preoperative examination included chest magnetic resonance imaging (MRI), enhanced chest CT, head MRI, bone scanning and cardiopulmonary function testing. None of the patients were receiving any treatment for their cancer prior to their evaluation and surgery, including neoadjuvant chemotherapy, radiation therapy, immunotherapy or gene targeted therapy. The following IVIM parameters of the mediastinal lymph nodes were measured: the short axis diameter, apparent diffusion coefficient (ADC), diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f). All of the patients underwent lobectomy and lymph node dissection. We compared the CT and MRI results and analysed the IVIM parameters of the pathologically determined non-metastatic and metastatic mediastinal lymph nodes in our 50 patients to generate the ROC curves and determine the best cut-off value for diagnosis. The remaining 16 patients' IVIM parameters were used to verify the diagnostic cut-off value. This study was approved by the institutional research ethics committee of Beijing Chao-Yang Hospital (2014-S-166), and all the patients signed the MRI informed consent.

RESULTS

In this study, MRI was used to measure 140 groups of mediastinal lymph nodes in 50 cases, and the results showed that 19 groups of mediastinal lymph nodes were metastatic, while 121 groups of mediastinal lymph nodes were non-metastatic. The pathological analysis showed that 20 groups of mediastinal lymph nodes were metastatic and 120 groups of mediastinal lymph nodes were non-metastatic. CT was used to measure 273 groups of mediastinal lymph nodes, and the result showed that 34 groups of mediastinal lymph nodes were metastatic, while 239 groups of mediastinal lymph nodes were non-metastatic. The pathological analysis showed that 20 groups of mediastinal lymph nodes were metastatic and 253 groups of mediastinal lymph nodes were non-metastatic. The ADC, D, D*, f values and the short axis diameters of the non-metastatic lymph nodes (n=121) were 2.9370±0.743×10^-3, 0.533±0.175×10^-3, 0.384±0.121×10^-3 mm²/s, 0.426±0.120, 6.903±1.831 mm, respectively, and 1.863±0.691×10^-3, 0.454±0.204×10^-3, 0.358±0.106×10^-3 mm²/s, 0.413±0.085, 7.705±2.213 mm, respectively, for the metastatic lymph nodes (n=19). The ADC and D values of the non-metastatic lymph nodes were significantly higher than the values for the metastatic lymph nodes (P<0.01); the other parameters (D*, f, and short axis diameter) did not show significantly different results between the two groups. The optimal cut-off values [area under the curve (AUC), sensitivity, and specificity] for distinguishing metastatic from non-metastatic lymph nodes were as follows: ADC =1.890×10^-3 mm²/s (0.897, 93.3%, 80.0%), Youden index 0.733; and D =0.344×10^-3 mm²/s (0.651, 90.8%, 50.0%), Youden index 0.651. When these cut-off values were applied as the diagnostic criteria in the remaining cases and compared with the pathology results, the diagnostic performance was good.

CONCLUSIONS

IVIM is useful to distinguish metastatic from non-metastatic lymph nodes in lung cancer. The ADC and the D values are significantly lower in metastatic lymph nodes, making these parameters more sensitive than the other parameters (D*, f, and short axis diameter). As a result, IVIM can be used in the N-stage diagnosis of lung cancer.

Ultrahigh b-values MRI in normal human prostate: Initial research on reproducibility and age-related differences

PURPOSE

To investigate the reproducibility of diffusion-weighted imaging (DWI) with ultrahigh b-values, and analyze the age-related differences in normal prostates.

MATERIALS AND METHODS

In all, 67 healthy participants were divided into three age groups (group A, 15-30 years; group B, 31-50 years; group C, ≥51 years), and underwent DWI scanning twice with 15 b-factors from 0 to 3000 at 3.0T. Triexponential fits were applied to calculate the molecular diffusion coefficient (D), the pseudo-diffusion coefficient (D*), the ultrahigh apparent diffusion coefficient (ADC_uh ), and perfusion fraction (f). The interobserver and short-term interscan reproducibility were evaluated, and the change in these parameters with age were assessed.

RESULTS

The D, ADC_uh , and f values presented good to excellent reproducibility. With increasing age, a trend of increasing D values was observed, with significant difference in both peripheral zone (PZ, P = 0.01) and central gland (CG, P = 0.01) of normal prostate tissue. The f value increased in the CG beginning at 50 years of age while the ADC_uh value decreased in the PZ after 50 years of age; all of them showed significant differences between groups A and C and groups B and C (P = 0.01/0.01).

CONCLUSION

The D, ADC_uh , and f values have good to excellent reproducibility in the normal prostate, and these values change with age. The ultrahigh b-values magnetic resonance imaging (MRI) can provide additional information (ADC_uh ), which is different from the IVIM (intravoxel incoherent motion)-derived parameters.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:801-812.

Diagnostic value of 18F-FDG PET/CT for cutaneous extranodal natural killer/T-cell lymphoma, nasal type

OBJECTIVE

To evaluate the use of fluorine-18 fluorodeoxyglucose (F-FDG) PET/computed tomography (CT) in the diagnosis of cutaneous extranodal natural killer/T-cell lymphoma, nasal type (C-ENK/T-NT).

METHODS

A total of 39 patients with newly diagnosed C-ENK/T-NT were enrolled between May 2006 and November 2013. Anatomic regions (n=429; five cutaneous and six extracutaneous regions per patient) were assessed using an F-FDG PET/CT scan and conventional staging methods (CSMs). F-FDG PET/CT and CSMs were compared and evaluated for their ability to detect tumor lesions and their influence on the staging and treatment strategies. Biopsy and clinical follow-up were used as the gold standard for diagnosis.

RESULTS

In total, 139 lesions were detected by CSMs and F-FDG PET/CT, of which there were 50 cutaneous and 89 extracutaneous-positive regions. F-FDG PET/CT detected 48 cutaneous and 88 extracutaneous regions. CSMs, however, detected only 34 cutaneous lesions and 61 extracutaneous lesions that were positive for malignancy (cutaneous comparison of PET/CT vs. CSMs, P<0.001; extracutaneous comparison of PET/CT vs. CSMs, P<0.05). Using F-FDG PET/CT, 8 (42%) patients were in stage I-II and 31 patients (58%) were in stage III-IV. F-FDG PET/CT staging was consistent with the final stage determination in 94.9% (37/39) of patients, whereas CSMs staging was correct in final stage determination in 74.4% (29/39) of patients (P=0.025).

CONCLUSION

Our study showed that F-FDG PET/CT scanning is a valuable modality for the detection of cutaneous and extracutaneous lesions of C-ENK/T-NT. F-FDG PET/CT may therefore influence future staging and treatment strategies.

Does the Reporting Quality of Diagnostic Test Accuracy Studies, as Defined by STARD 2015, Affect Citation?

Objective

To determine the rate with which diagnostic test accuracy studies that are published in a general radiology journal adhere to the Standards for Reporting of Diagnostic Accuracy Studies (STARD) 2015, and to explore the relationship between adherence rate and citation rate while avoiding confounding by journal factors.

Materials and Methods

All eligible diagnostic test accuracy studies that were published in the Korean Journal of Radiology in 2011–2015 were identified. Five reviewers assessed each article for yes/no compliance with 27 of the 30 STARD 2015 checklist items (items 28, 29, and 30 were excluded). The total STARD score (number of fulfilled STARD items) was calculated. The score of the 15 STARD items that related directly to the Quality Assessment of Diagnostic Accuracy Studies (QUADAS)-2 was also calculated. The number of times each article was cited (as indicated by the Web of Science) after publication until March 2016 and the article exposure time (time in months between publication and March 2016) were extracted.

Results

Sixty-three articles were analyzed. The mean (range) total and QUADAS-2-related STARD scores were 20.0 (14.5–25) and 11.4 (7–15), respectively. The mean citation number was 4 (0–21). Citation number did not associate significantly with either STARD score after accounting for exposure time (total score: correlation coefficient = 0.154, p = 0.232; QUADAS-2-related score: correlation coefficient = 0.143, p = 0.266).

Conclusion

The degree of adherence to STARD 2015 was moderate for this journal, indicating that there is room for improvement. When adjusted for exposure time, the degree of adherence did not affect the citation rate.

The diagnostic value of biexponential apparent diffusion coefficients in myopathy

To investigate the performance of a biexponential signal decay model using DWI in myopathies and to differentiate Polymyositis (PM)/Dermatomyositis (DM), Glycogen Storage Diseases (GSDs) and Muscular Dystrophies (MDs) utilizing diffusion-weighted imaging. 11 healthy volunteers (control group) and 46 patients with myopathy were enrolled in the retrospective study. 27 of 46 patients had PM/DM, 7 patients GSDs and 12 patients MDs. After conventional MR sequences, diffusion weighted imaging with a b-factor ranging from 0 to 1200 s/mm(2) was performed on both thighs. The intra-muscular signal-to-noise ratios (SNRs) on multiple-b DWI images were measured for 7 different muscles and compared among the different groups. The median T2 signal intensity and biexponential apparent diffusion coefficients (ADC), including standard ADC, fast ADC, and slow ADC values, were compared among the different groups. The intra-muscular SNRs were statistically significantly different depending on the b value, and also found among the 4 groups (p < 0.05). The median T2 signal intensity of the normal muscles in control group was statistically significantly lower than that of edematous muscles in the PM/DM, GSDs and MDs groups (p = 0.000), while there were no statistically significant differences among the PM/DM, GSDs, and MDs groups (p > 0.05). The median standard ADC value of the edematous muscles in GSDs was statistically significantly lower than that of normal muscles in the control group (p = 0.000) and the median ADC value of the edematous muscles in PM/DM patients was statistically significantly greater than that of the GSDs (p = 0.000) and MDs groups (p = 0.005). The median slow ADC value of the edematous muscles in MDs patients and PM/DM patients was statistically significantly greater than that of GSDs patients (p < 0.05). Intra-muscular SNR decay curves and biexponential ADC parameters are useful in distinguishing among PM/DM, GSDs, and MDs.

Discrimination between Metastatic and Nonmetastatic Mesorectal Lymph Nodes in Rectal Cancer Using Intravoxel Incoherent Motion Diffusion-weighted Magnetic Resonance Imaging

RATIONALE AND OBJECTIVES

The aim of the study was to investigate the diagnostic value of intravoxel incoherent motion diffusion-weighted magnetic resonance imaging (IVIM DWI) for discriminating nonmetastatic from metastatic mesorectal lymph nodes in rectal cancer.

MATERIALS AND METHODS

IVIM DWI was performed preoperatively on 50 patients with rectal carcinoma. The short-axis diameter, short- to long-axis diameter ratio, and IVIM-based parameter (pure diffusion coefficient [D], pseudo-diffusion coefficient [D*] and perfusion fraction [f]) values were compared between the metastatic and nonmetastatic lymph node groups.

RESULTS

The short-axis diameter; short- to long-axis diameter ratio; and D, D*, and f values for the nonmetastatic lymph node group (n = 28) were 6.446 ± 1.201 mm, 0.815 ± 0.099, 1.071 ± 0.234 × 10(-3) mm(2)/s, 15.443 ± 5.946 mm(2)/s and 0.261 ± 0.128, respectively, and were 9.045 ± 3.185 mm, 0.809 ± 0.099, 0.816 ± 0.121 × 10(-3) mm(2)/s, 11.679 ± 7.521 × 10(-3) mm(2)/s, and 0.190 ± 0.064, respectively, for the metastatic lymph node group (n = 31). The short-axis diameter for the metastatic group was significantly higher than for the nonmetastatic group (P <0.001). The metastatic group exhibited significantly lower D and D* values than the nonmetastatic group (P <0.01). The short- to long-axis diameter ratio and f values did not differ significantly between the two groups. Optimal cutoff values (area under the curve, sensitivity, and specificity) for distinguishing metastatic from nonmetastatic lymph nodes were as follows: short-axis diameter = 5.563 mm (0.783, 74.2%, 82.1%); D = 0.667 × 10(-3) mm(2)/s (0.885, 77.4%, 89.3%); and D* = 0.485 × 10(-3) mm(2)/s (0.727, 80.6%, 67.9%).

CONCLUSION

IVIM DWI is useful to differentiate between metastatic and nonmetastatic mesorectal lymph nodes in rectal cancer.

Diffusion-weighted magnetic resonance imaging in cancer: Reported apparent diffusion coefficients, in-vitro and in-vivo reproducibility

There is considerable disparity in the published apparent diffusion coefficient (ADC) values across different anatomies. Institutions are increasingly assessing repeatability and reproducibility of the derived ADC to determine its variation, which could potentially be used as an indicator in determining tumour aggressiveness or assessing tumour response. In this manuscript, a review of selected articles published to date in healthy extra-cranial body diffusion-weighted magnetic resonance imaging is presented, detailing reported ADC values and discussing their variation across different studies. In total 115 studies were selected including 28 for liver parenchyma, 15 for kidney (renal parenchyma), 14 for spleen, 13 for pancreatic body, 6 for gallbladder, 13 for prostate, 13 for uterus (endometrium, myometrium, cervix) and 13 for fibroglandular breast tissue. Median ADC values in selected studies were found to be 1.28 × 10(-3) mm(2)/s in liver, 1.94 × 10(-3) mm(2)/s in kidney, 1.60 × 10(-3) mm(2)/s in pancreatic body, 0.85 × 10(-3) mm(2)/s in spleen, 2.73 × 10(-3) mm(2)/s in gallbladder, 1.64 × 10(-3) mm(2)/s and 1.31 × 10(-3) mm(2)/s in prostate peripheral zone and central gland respectively (combined median value of 1.54×10(-3) mm(2)/s), 1.44 × 10(-3) mm(2)/s in endometrium, 1.53 × 10(-3) mm(2)/s in myometrium, 1.71 × 10(-3) mm(2)/s in cervix and 1.92 × 10(-3) mm(2)/s in breast. In addition, six phantom studies and thirteen in vivo studies were summarized to compare repeatability and reproducibility of the measured ADC. All selected phantom studies demonstrated lower intra-scanner and inter-scanner variation compared to in vivo studies. Based on the findings of this manuscript, it is recommended that protocols need to be optimised for the body part studied and that system-induced variability must be established using a standardized phantom in any clinical study. Reproducibility of the measured ADC must also be assessed in a volunteer population, as variations are far more significant in vivo compared with phantom studies.

Comparison of mono-exponential and bi-exponential models of diffusion-weighted MRI in diagnosis of small VX2 hepatic tumors in rabbits

AIM: To investigate the value of mono-exponential model with single b-factor and bi-exponential model with extended b-factor range of diffusion-weighted imaging (DWI) in diagnosis of small VX2 hepatic tumors ( ≤ 3 cm) in rabbits.

METHODS: On the 7^th day and 14^th day after tumor implantation, 50 New Zealand white rabbits with VX2 hepatic tumors underwent DWI based on single b-factor (b values of 0 and 800 s/mm²) and multi-b-factor (b values of 0, 20, 50, 100, 200, 400, 600, 800 and 1200 s/mm²). Apparent diffusion coefficient (ADC), slow ADC, fast ADC and fraction fast ADC (f_fast) were measured in the rim of tumor (TR) and the normal region (NR) and compared between the two groups. The best thresholds of ADC, slow ADC, fast ADC and f_fast were calculated by the receiver operating characteristic curve (ROC).

RESULTS: There were significant differences between TR and NR in ADC values on days 7 and 14 (P < 0.05). The values of slow ADC of TR were superior than those of NR on both days 7 and 14. Fast ADC and f_fast of NR were higher than those of TR on the 14^th day (P < 0.05). Expect for slow ADC, no statistical difference was observed in ADC, Fast-ADC or f_fast of TR between the 7^th day and 14^th day. Slow ADC offered the highest sensitivity and specificity compared to ADC, slow-ADC, fast-ADC and f_fast for differentiating between TR and NR on both days 7 and 14.

CONCLUSION: The parameter values of mono-exponential model and bi-exponential model, especially slow-ADC, reflect perfusion of microcirculation and diffusion of water molecules, thus having value for the diagnosis of small hepatic tumors.

Triexponential function analysis of diffusion-weighted MRI for diagnosing prostate cancer

BACKGROUND

To evaluate more detailed information noninvasively through on diffusion and perfusion in prostate cancer (PCa) using triexponential analysis of diffusion-weighted imaging (DWI).

METHODS

Sixty-three prostate cancer patients underwent preoperative 3.0 Tesla MRI including eight b-values DWI. Triexponential analysis was performed to obtain three diffusion coefficients (Dp , Df , Ds ), as well as fractions (Fp , Ff , Fs ). Each diffusion parameter for cancerous lesions and normal tissues was compared and the relationship between diffusion parameters and Gleason score (GS) was assessed. K(trans) , Ve , and the ratios of intracellular components measured in histopathological specimens were compared with diffusion parameters.

RESULTS

Dp was significantly greater for cancerous lesions than normal peripheral zone (PZ) (P < 0.001), whereas Dp in transition zone (TZ) showed no significant difference (P = 0.74, 95% confidence interval (CI) = -4.69-6.48). Ds was significantly smaller for each cancerous lesions in PZ and TZ (P < 0.001, respectively). There was no significant difference in Df between cancerous lesions and normal tissues in PZ and TZ (P = 0.07, 95% CI = -0.29-0.12 and P = 0.53, 95% CI = -3.51-2.29, respectively). D obtained with biexponential analysis were significantly smaller in cancerous lesions than in normal tissue in PZ and TZ (P < 0.001 for both), while D* in PZ and TZ showed no significant difference (P = 0.14, 95% CI = -1.60-0.24 and P = 0.31, 95% CI = -3.43-1.16, respectively). Dp in PZ and TZ showed significant correlation with K(trans) (R = 0.85, P < 0.001; R = 0.81, P < 0.001, respectively), while D(*) in PZ obtained with biexponential analysis showed no such correlation (P = 0.08, 95% CI = -0.14-0.30). Fs was significantly correlated with intracellular space fraction evaluated in histopathological specimens in PZ and TZ cancer (R = 0.41, P < 0.05; R = 0.59, P < 0.001, respectively). Ff and Fs correlated significantly with GS in PZ and TZ cancer (PZ: R = -0.44, P < 0.05; R = 0.37, P < 0.05, TZ: R = -0.59, P < 0.05; R = 0.57, P < 0.05, respectively).

CONCLUSION

Triexponential analysis is a noninvasive approach that can provide more detailed information regarding diffusion and perfusion of PCa than biexponential analysis.

Comparison of stretched-Exponential and monoexponential model diffusion-Weighted imaging in prostate cancer and normal tissues

BACKGROUND

To compare stretched-exponential and monoexponential model diffusion-weighted imaging (DWI) in prostate cancer and normal tissues.

METHODS

Twenty-seven patients with prostate cancer underwent DWI exam using b-values of 0, 500, 1000, and 2000 s/mm(2) . The distributed diffusion coefficients (DDC) and α values of prostate cancer and normal tissues were obtained with stretched-exponential model and apparent diffusion coefficient (ADC) values using monoexponential model. The ADC, DDC (both in 10(-3) mm(2)/s), and α values (range, 0-1) were compared among different prostate tissues. The ADC and DDC were also compared and correlated in each tissue, and the standardized differences between DDC and ADC were compared among different tissues.

RESULTS

Data were obtained for 31 cancers, 36 normal peripheral zone (PZ) and 26 normal central gland (CG) tissues. The ADC (0.71 ± 0.12), DDC (0.60 ± 0.18), and α value (0.64 ± 0.05) of tumor were all significantly lower than those of the normal PZ (1.41 ± 0.22, 1.47 ± 0.20, and 0.85 ± 0.09) and CG (1.25 ± 0.14, 1.32 ± 0.13, and 0.82 ± 0.06) (all P < 0.05). ADC was significantly higher than DDC in cancer, but lower than DDC in the PZ and CG (all P < 0.05). The ADC and DDC were strongly correlated (R(2)  = 0.99, 0.98, 0.99, respectively, all P < 0.05) in all the tissue, and standardized difference between ADC and DDC of cancer was slight but significantly higher than that in normal tissue.

CONCLUSION

The stretched-exponential model DWI provides more parameters for distinguishing prostate cancer and normal tissue and reveals slight differences between DDC and ADC values.

Non-Gaussian water diffusion kurtosis imaging of prostate cancer

PURPOSE

To evaluate the non-Gaussian water diffusion properties of prostate cancer (PCa) and determine the diagnostic performance of diffusion kurtosis (DK) imaging for distinguishing PCa from benign tissues within the peripheral zone (PZ), and assessing tumor lesions with different Gleason scores.

MATERIALS AND METHODS

Nineteen patients who underwent diffusion weighted (DW) magnetic resonance imaging using multiple b-values and were pathologically confirmed with PCa were enrolled in this study. Apparent diffusion coefficient (ADC) was derived using a monoexponential model, while diffusion coefficient (D) and kurtosis (K) were determined using a DK model. Differences between the ADC, D and K values of benign PZ and PCa, as well as those of tumor lesions with Gleason scores of 6, 7 and ≥8 were assessed. Correlations between parameters D and K in PCa were analyzed using Pearson's correlation coefficient. ADC, D and K values were correlated with Gleason scores of 6, 7 and ≥8, respectively.

RESULTS

ADC and D values were significantly (p<0.001) lower in PCa (0.79±0.14μm(2)/ms and 1.56±0.23μm(2)/ms, respectively) compared to benign PZ (1.23±0.19μm(2)/ms and 2.54±0.24μm(2)/ms, respectively). K values were significantly (p<0.001) greater in PCa (0.96±0.20) compared to benign PZ (0.59±0.08). D and K showed fewer overlapping values between benign PZ and PCa compared to ADC. There was a strong negative correlation between D and K values in PCa (Pearson correlation coefficient r=-0.729; p<0.001). ADC and K values differed significantly in tumor lesions with Gleason scores of 6, 7 and ≥8 (p<0.001 and p=0.001, respectively), although no significant difference was detected for D values (p=0.325). Significant correlations were found between the ADC value and Gleason score (r=-0.828; p<0.001), as well as the K value and Gleason score (r=0.729; p<0.001).

CONCLUSION

DK model may add value in PCa detection and diagnosis. K potentially offers a new metric for assessment of PCa.