Whole-lesion diffusion metrics for assessment of bladder cancer aggressiveness

Does volumetric measurement of ADC values achieve higher diagnostic performance in bladder cancer MRI?

BACKGROUND

Apparent diffusion coefficient (ADC) value is an important part of bladder cancer magnetic resonance imaging (MRI) assessment and can predict the aggressive and invasive potentials. There is growing interest in whole tumor volume measurements.

PURPOSE

To investigate if the volumetric ADC measurement method will significantly exceed the diagnostic performance of the selected region of interest (ROI) method in everyday practice.

MATERIAL AND METHODS

A prospective evaluation was carried out of 50 patients with bladder cancer by two radiologists. The mean and the minimum ADC values were measured using both methods. The inter-reader agreement was determined by the intraclass correlation coefficient. The ADC values were compared between different grades, states of muscle invasion, and lympho-vascular invasion (LVI); then, validity was evaluated using receiver operating characteristic (ROC) curves. Areas under the curve (AUC) were then compared for the level of statistical significance.

RESULTS

The inter-observer agreement was excellent for the ADC values using both methods. The volumetric measurement provides higher mean and lower minimum ADC values with statistically significant differences (P <0.00001). The highest diagnostic accuracy for differentiating tumor grade and predicting muscle invasion was for the minimum ADC by a selected ROI. However, the differences between the achieved AUCs were of no statistical significance. None of the ADC values predicted LVI with statistical significance.

CONCLUSION

The selected ROI and volumetric measurement methods of mean and minimum ADC in bladder cancer yield different values, still having comparable diagnostic performance with accurate ROI sampling. The minimum ADC value by ROI is preferred in everyday clinical practice.

Practical Guide to VI-RADS: MRI Protocols, Lesion Characterization, and Pitfalls

Urothelial carcinoma is the most common type of bladder cancer (BC), accounting for approximately 90% of all cases. Evaluating the depth of tumor invasion in the bladder wall (tumor staging) is essential for determining the treatment and prognosis in patients with BC. Neoadjuvant therapy followed by radical cystectomy is the most common treatment of localized muscle-invasive BC (MIBC). Therefore, it is vital to differentiate non-MIBC from MIBC. Transurethral resection of bladder tumor (TURBT) is the reference standard to determine the extent of tumor invasion into the bladder wall through tissue sampling. However, this diagnostic and therapeutic method may not adequately sample the muscularis propria, leading to a higher risk of residual disease, early recurrence, and tumor understaging in approximately 50% of patients during the initial TURBT. Multiparametric MRI can overcome some of the limitations of TURBT when evaluating BC, particularly regarding tumor staging. In this context, the Vesical Imaging Reporting and Data System (VI-RADS) classification was developed to establish standards for bladder multiparametric MRI and interpretation. It uses a 5-point scale to assess the likelihood of detrusor muscle invasion. T2-weighted MR images are particularly useful as an initial guide, especially for categories 1-3, while the presence of muscular invasion is determined with diffusion-weighted and dynamic contrast-enhanced sequences. Diffusion-weighted imaging takes precedence as the dominant method when optimal image quality is achieved. The presence of a stalk or a thickened inner layer and no evidence of interruption of the signal intensity of the muscular layer are central for predicting a low likelihood of muscle invasion. ©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material. See the invited commentary by Hoegger in this issue.

Prediction of overall survival in patients with pancreatic ductal adenocarcinoma: histogram analysis of ADC value and correlation with pathological intratumoral necrosis

BACKGROUND

To evaluate the utility of histogram analysis (HA) of apparent diffusion coefficient (ADC) values to predict the overall survival (OS) in patients with pancreatic ductal adenocarcinoma (PDAC) and to correlate with pathologically evaluated massive intratumoral necrosis (MITN).

MATERIALS AND METHODS

Thirty-nine patients were included in this retrospective study with surgically resected PDAC who underwent preoperative magnetic resonance imaging. Twelve patients received neoadjuvant chemotherapy. HA on the ADC maps were performed to obtain the tumor HA parameters. Using Cox proportional regression analysis adjusted for age, time-dependent receiver-operating-characteristic (ROC) curve analysis, and Kaplan-Meier estimation, we evaluated the association between HA parameters and OS. The association between prognostic factors and pathologically confirmed MITN was assessed by logistic regression analysis.

RESULTS

The median OS was 19.9 months. The kurtosis (P < 0.001), entropy (P = 0.013), and energy (P = 0.04) were significantly associated with OS. The kurtosis had the highest area under the ROC curve (AUC) for predicting 3-year survival (AUC 0.824) among these three parameters. Between the kurtosis and MITN, the logistic regression model revealed a positive correlation (P = 0.045). Lower survival rates occurred in patients with high kurtosis (cutoff value > 2.45) than those with low kurtosis (≤ 2.45) (P < 0.001: 1-year survival rate, 75.2% versus 100%: 3-year survival rate, 14.7% versus 100%).

CONCLUSIONS

HA derived kurtosis obtained from tumor ADC maps might be a potential imaging biomarker for predicting the presence of MITN and OS in patients with PDAC.

Apparent Diffusion Coefficient Value as a Biomarker for Detecting Muscle-Invasive and High-Grade Bladder Cancer: A Systematic Review

Background: Several studies have investigated the potential role of the apparent diffusion coefficient (ADC) value of diffusion-weighted magnetic resonance imaging as a biomarker of high-grade and invasive bladder cancer. Methods: PubMed and the Cochrane Library were systematically searched in September 2021 to extract studies that evaluated the associations between ADC values, pathological T stage, and histological grade bladder cancers. The diagnostic performance of ADC values in detecting muscle-invasive bladder cancer (MIBC) and high-grade disease was systematically reviewed. Results: Six studies were included in this systematic review. MIBC showed significantly lower ADC values than non-muscle-invasive bladder cancer (NMIBC) in all six studies. The median (range) sensitivity, specificity, and area under the curve (AUC) of ADC values to detect MIBC among the four eligible studies were 73.5% (68.8–90.0%), 79.9% (66.7–84.4%), and 0.762 (0.730–0.884), respectively. Similarly, high-grade disease showed significantly lower ADC values than did low-grade disease in all four eligible studies. The median (range) sensitivity, specificity, and AUC of ADC values for detecting high-grade disease among the three eligible studies were 75.0% (73.0–76.5%), 95.8% (76.2–100%), and 0.902 (0.804–0.906), respectively. Conclusions: The ADC value is a non-invasive diagnostic biomarker for discriminating muscle-invasive and high-grade bladder cancer.

Combining volumetric apparent diffusion coefficient histogram analysis with vesical imaging reporting and data system to predict the muscle invasion of bladder cancer

OBJECTIVE

The objective of this study was to explore whether volumetric apparent diffusion coefficient (ADC) histogram analysis can provide additional value to Vesical Imaging Reporting and Data System (VI-RADS) in differentiating muscle-invasive bladder cancer (MIBC) from non-muscle-invasive bladder cancer (NMIBC).

MATERIALS AND METHODS

80 patients were retrospectively reviewed with pathologically proven NMIBC (n = 53) or MIBC (n = 27). All patients underwent MRI including diffusion-weighted imaging (DWI) (b = 0, 800 s/mm²), and the VI-RADS score was evaluated based on DWI. Volumetric ADC histogram parameters were calculated from the volumetric of interest (VOI) on DWI, including the min ADC, mean ADC, median ADC, max ADC, 10th, 25th, 75th, 90th percentiles ADC, skewness, kurtosis, and entropy. The Mann-Whitney U-test was used to compare histogram parameters between NMIBC and MIBC. Receiver operating characteristic analysis was used to evaluate the diagnostic value of each significant parameter.

RESULTS

Among all parameters, the VI-RADS yield the highest Area Under the Curve (AUC, 0.88; sensitivity, 88.89%; specificity, 83.61%). MIBC had significantly lower min ADC, mean ADC, median ADC, 10th, 25th, 75th, and 90th percentiles ADC than NMIBC (p = 0.002, p < 0.001, p < 0.001, p = 0.003, p = 0.004, p < 0.001, p < 0.001). Skewness and kurtosis of MIBC were significantly higher than those of NMIBC (p < 0.001, p < 0.001). The combination of VI-RADS and skewness showed significantly higher AUC (AUC 0.923; 95% CI 0.847-0.969) than only with VI-RADS (AUC 0.880; 95% CI 0.793-0.940).

CONCLUSION

Volumetric ADC histogram analysis and VI-RADS are both useful methods in differentiating MIBC from NMIBC, and the volumetric ADC histogram analysis can provide additional value to VI-RADS.

Urothelial Carcinoma of the Bladder: Radiologic Perspective

방광암은 비교적 흔히 진단되는 암이며 재발이 흔해 영상의학적 검사에서 흔히 만날 수 있다. 방광암의 정확한 진단과 병기 평가는 어떤 치료를 할 것인지를 정하고 예후를 평가하는데 큰 영향을 미친다. 방광암의 임상적 병기 평가는 요도경유방광종양절제술로 진단과 치료를 겸해서 이루어졌지만, 저평가되는 경우가 흔히 있다. 수술 전 방광암의 위치, 크기, 근육층 침범 유무, 림프절전이, 원격전이, 상부요로 암 유무 등을 영상의학적 검사에서 정확히 진단 및 평가할 수 있다면 더욱 적절히 처치 및 관리를 할 수 있다. 이런 정확한 진단을 위해서는 영상을 판독하는 영상의학과 의사는 먼저 방광암의 임상적인 특징을 잘 알고 있어야 한다. 그리고 영상 검사들의 종류와 특징, 한계를 알고 있어야 한다. 최근 자기공명영상의 발달로 방광 영상의 질 및 방광암의 진단과 평가가 향상되었다. 그리고 방광 이미징 보고 및 데이터시스템이 발표되어 객관적으로 방광암의 근육층 침범 가능성을 평가할 수 있게 되었다. 방광암 치료 종류를 알고 그에 따른 치료 후 변화에는 무엇이 있는지 어떻게 평가하는지도 알아야 하겠다. 이 종설에서는 방광 요로상피세포암의 특징과 다양한 영상의학 검사와 소견에 대해서 알아보고자 한다.

Overview of VI-RADS in Bladder Cancer

OBJECTIVE. The purpose of this article is to review the natural history and management of bladder cancer, with insight into MRI applications for the assessment of muscle invasiveness of bladder cancer using the newly developed Vesical Imaging Reporting and Data System (VI-RADS) score. CONCLUSION. Multiparametric MRI and the VI-RADS score have been consistently validated across several different institutions as appropriate tools for local staging of bladder cancer and have been proven to contribute to the diagnostic workup and management of urinary bladder cancer.

MRI of Bladder Cancer: Local and Nodal Staging

Accurate staging of bladder cancer (BC) is critical, with local tumor staging directly influencing management decisions and affecting prognosis. However, clinical staging based on clinical examination, including cystoscopy and transurethral resection of bladder tumor (TURBT), often understages patients compared to final pathology at radical cystectomy and lymph node (LN) dissection, mainly due to underestimation of the depth of local invasion and the presence of LN metastasis. MRI has now become established as the modality of choice for the local staging of BC and can be additionally utilized for the assessment of regional LN involvement and tumor spread to the pelvic bones and upper urinary tract (UUT). The recent development of the Vesical Imaging-Reporting and Data System (VI-RADS) recommendations has led to further improvements in bladder MRI, enabling standardization of image acquisition and reporting. Multiparametric magnetic resonance imaging (mpMRI) incorporating morphological and functional imaging has been proven to further improve the accuracy of primary and recurrent tumor detection and local staging, and has shown promise in predicting tumor aggressiveness and monitoring response to therapy. These sequences can also be utilized to perform radiomics, which has shown encouraging initial results in predicting BC grade and local stage. In this article, the current state of evidence supporting MRI in local, regional, and distant staging in patients with BC is reviewed. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 2 J. Magn. Reson. Imaging 2020;52:649-667.

Rectal Cancer Invasiveness: Whole-Lesion Diffusion-Weighted Imaging (DWI) Histogram Analysis by Comparison of Reduced Field-of-View and Conventional DWI Techniques

To explore the role of whole-lesion histogram analysis of apparent diffusion coefficient (ADC) for discriminating between T stages of rectal carcinoma by comparison of reduced field-of-view (FOV) and conventional DWI techniques. 102 patients with rectal cancer were enrolled in this retrospective study. All patients received preoperative MR scan at 3 T, including reduced and full FOV DWI sequences. Histogram parameters from two DWI methods were calculated and correlated with histological T stage of rectal cancer. The diagnostic performance of individual parameter for differentiating stage pT1-2 and pT3-4 tumors from both DWI techniques was assessed by receiver operating characteristic curve analysis. There were significant differences for the parameters of ADCmean, 50th, 75th, 90th, 95th percentiles, skewness and kurtosis of both DWI sequences in patients with pT1-2 as compared to those with pT3-4 tumors (P < 0.05), in addition to parameters including ADCmin (P = 0.015) and 25th percentile (P = 0.006) from rFOV DWI. Correlations were noted between T staging and above histogram parameters from rFOV DWI (r: −0.741–0.682) and fFOV DWI (r: −0.449–0.449), besides parameters of ADCmin (0.370) and 25th percentile (−0.425) from rFOV DWI. The AUCs of 75th and 90th percentiles from rFOV DWI were significantly higher than that from fFOV DWI (P = 0.0410 and P = 0.0208). The whole-lesion histogram analysis based on rFOV DWI was overall more advantageous than the one based on fFOV DWI in differentiating T staging of rectal cancer and the 90th percentile ADC from rFOV DWI was the value with the highest AUC (0.932).

Histogram analysis of DCE-MRI for chemoradiotherapy response evaluation in locally advanced esophageal squamous cell carcinoma

AIMS

The aim of the study was to predict and assess treatment response by histogram analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to patients with locally advanced esophageal squamous cell carcinoma receiving chemoradiotherapy (CRT).

MATERIALS AND METHODS

Seventy-two patients with locally advanced esophageal squamous cell carcinoma who underwent DCE-MRI before and after chemoradiotherapy were enrolled and divided into the complete response (CR) group and the non-CR group based on RECIST. The histogram parameters (10th percentile, 90th percentile, median, mean, standard deviation, skewness, and kurtosis) of pre-CRT and post-CRT were compared using a paired Student's t test in the CR and non-CR groups, respectively. The histogram parameter differences between the CR and the non-CR groups were compared using an unpaired Student's t test. A receiver operating characteristic (ROC) analysis was performed to evaluate the diagnostic performance.

RESULTS

The histogram parameters of K^trans values were observed to have significantly decreased after chemoradiotherapy in the CR group. The CR responders showed significantly higher median, mean, and 10th and 90th percentile of pre-K^trans values than those of the non-CR group. The histogram analysis indicated the decreased heterogeneity in the CR group after CRT. Esophageal cancer with higher pre-K^trans and lower post-K^trans values indicated a good treatment response to CRT. Pre-K^trans-10th showed the best diagnostic performance in predicting the chemoradiotherapy response.

CONCLUSIONS

The histogram parameters of K^trans are useful in the assessment and prediction of the chemoradiotherapy response in patients with advanced esophageal squamous cell carcinoma. DCE-MRI could serve as an adjunctive imaging technique for treatment planning.

Exploratory Study of Apparent Diffusion Coefficient Histogram Metrics in Assessing Pancreatic Malignancy

PURPOSE

To evaluate whole-lesion 3D-histogram apparent diffusion coefficient (ADC) metrics for assessment of pancreatic malignancy.

METHODS

Forty-two pancreatic malignancies (36 pancreatic adenocarcinoma [PDAC], 6 pancreatic neuroendocrine [PanNET]) underwent abdominal magnetic resonance imaging (MRI) with diffusion-weighted imaging before endoscopic ultrasound biopsy or surgical resection. Two radiologists independently placed 3D volumes of interest to derive whole-lesion histogram ADC metrics. Mann-Whitney tests and receiver operating characteristic analyses were used to assess metrics' diagnostic performance for lesion histology, T-stage, N-stage, and grade.

RESULTS

Whole-lesion ADC histogram metrics lower in PDACs than PanNETs for both readers (P ≤ .026) were mean ADC (area under the curve [AUC] = 0.787-0.792), mean of the bottom 10th percentile (mean_0-10) (AUC = 0.787-0.880), mean of the 10th-25th percentile (mean_10-25) (AUC = 0.884-0.917) and mean of the 25th-50th percentile (mean_25-50) (AUC = 0.829-0.829). For mean_10-25 (metric with highest AUC for identifying PDAC), for reader 1 a threshold > 0.94 × 10^-3 mm²/s achieved sensitivity 94% and specificity 83%, and for reader 2 a threshold > 0.82 achieved sensitivity 97% and specificity 67%. Metrics lower in nodal status ≥ N₁ than N₀ for both readers (P ≤ .043) were mean_0-10 (AUC = 0.789-0.822) and mean_10-25 (AUC = 0.800-0.822). For mean_10-25 (metric with highest AUC for identifying N₀), for reader 1 a threshold <1.17 achieved sensitivity 87% and specificity 67%, and for reader 2 a threshold <1.04 achieved sensitivity 87% and specificity 83%. No metric was associated with T-stage (P > .195) or grade (P > .215).

CONCLUSION

Volumetric ADC histogram metrics may serve as non-invasive biomarkers of pancreatic malignancy. Mean_10-25 outperformed standard mean for lesion histology and nodal status, supporting the role of histogram analysis.

Pituitary macroadenoma: Accuracy of apparent diffusion coefficient magnetic resonance imaging in grading tumor aggressiveness

PURPOSE

The purpose of this study is to evaluate the accuracy of apparent diffusion coefficient magnetic resonance imaging in grading tumor aggressiveness using histogram apparent diffusion coefficient values.

MATERIALS AND METHODS

Eighteen patients with surgically proved pituitary macroadenomas were included in this study. Diffusion-weighted imaging with single-shot echo-planar sequence at 3-T with a 32-channel head coil was performed with b values of 0 and 1000 s/mm². Calculated apparent diffusion coefficient maps were generated, and a 3-D volume of interest was placed on the tumor while superimposing contrast-enhanced magnetic resonance images. All apparent diffusion coefficient values within the volume of interest were used to compute the average apparent diffusion coefficient of the tumor. The apparent diffusion coefficient values were binned to construct the apparent diffusion coefficient histogram. Using the histogram, the mean, percentiles, skewness, and kurtosis of the apparent diffusion coefficient of the entire tumor were computed. Apparent diffusion coefficient histogram parameters were compared with the MIB-1 index, invasiveness, and recurrence for grading tumor aggressiveness of pituitary adenomas.

RESULTS

The skewness of the apparent diffusion coefficient histogram only showed significant differences among MIB-1 indices ( p = 0.030). All apparent diffusion coefficient histogram parameters showed no significant differences between negative and positive invasion. The skewness and kurtosis of the apparent diffusion coefficient histogram showed significant differences between positive and negative recurrence (skewness p = 0.011, kurtosis p = 0.011). Receiver-operating characteristics analysis between positive and negative recurrence showed that both skewness and kurtosis of the apparent diffusion coefficient achieved area under the curve at 0.967.

CONCLUSION

Skewness and kurtosis of the apparent diffusion coefficient histogram were the predictive parameters for assessing tumor proliferative potential and recurrence of pituitary adenomas.

Bladder cancer: detection and image quality compared among iShim, RESOLVE, and ss-EPI diffusion-weighted MR imaging with high b value at 3.0 T MRI

To compare the detection of bladder neoplasms and image quality among the diffusion-weighted imaging (DWI) acquired by the prototype single-shot echo-planar-imaging (ss-EPI) sequence for integrated slice-specific dynamic shimming (iShim), readout segmentation of long variable echo trains (RESOLVE) and conventional ss-EPI sequences.Around 63 patients with 77 bladder lesions were enrolled. The MR protocol included T1WI, T2WI and 3 types of DWI. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of each DWI for the detection of bladder tumor were computed. The subjective scores of imaging quality, diagnostic confidence, and detection of tumors of stage T2 or greater were recorded. The contrast-to-noise ratio (CNR), signal intensity ratios, and apparent diffusion coefficient (ADC) values were measured. The univariate analysis of variance technique, the Friedman test, and Bland-Altman plots were used in the statistical analysis. Observer performance of tumor T stage was tested using receiver operating characteristic (ROC) curve analysis.The sensitivity, NPV, and accuracy of iShim (92.75%; 61.54%; 93.51%) for detection of bladder tumor were superior to those of RESOLVE (84.06%; 42.11%; 85.71%) and ss-EPI (86.96%; 47.06%; 88.31%). All qualitative scores of iShim were higher than RESOLVE (all P < .05) and ss-EPI (all P < .05). The CNR, signal intensity ratios between bladder lesion and urine, lesion, and submucosal stalk (or nearby normal bladder wall), and between distal normal bladder wall and urine of iShim (39.84 ± 12.11, 2.40 ± 0.60, 1.98 ± 0.43, 1.28 ± 0.16) were higher than RESOLVE (16.97 ± 7.08, 1.62 ± 0.41, 1.52 ± 0.42, 1.15 ± 0.29, all P < .05) and ss-EPI (27.89 ± 9.65, 1.66 ± 0.46, 1.57 ± 0.50, 0.99 ± 0.22, all P < .05). No significant difference of ADC values were found for iShim and RESOLVE (P=0.46), iShim, and ss-EPI (P = 0.97), RESOLVE and ss-EPI (P = .48). The Az value for the detection of tumors of stage T2 or greater was slightly higher with the iShim DWI sequence (0.89) than with the RESOLVE (0.87, P = 0.72) or ss-EPI (0.85, P = .38) sequence.The iShim DWI has relatively better detection of bladder tumor and image quality without significant ADC value difference.

Quantitative Assessment of Heterogeneity in Bladder Tumor MRI Diffusivity: Can Response be Predicted Prior to Neoadjuvant Chemotherapy?

Background:

It is a critical unmet need to predict chemosensitivity in muscle-invasive bladder cancer patients who receive neoadjuvant chemotherapy (NAC). Quantification of tumor heterogeneity has been shown to be useful in the assessment of therapeutic response. Apparent diffusion coefficient (ADC) is derived from diffusion weighted MRI (DWI) to quantify the water diffusivity which characterizes micro-cellularity in tumor tissues.

Objective:

The aim of this study is to assess if a quantitative measurement of ADC heterogeneity in bladder tumors can be a predictor of therapeutic response to NAC.

Materials and Methods:

Twenty patients with pT2 bladder cancer have been included in this study. Patient MRI was performed on a 3T system with DWI prior to NAC. Regions of interest (ROIs) were placed over the whole tumor volume on ADC maps to acquire a data matrix of voxel-wise ADC values for each patient. We performed histogram analysis on each ADC data matrix to calculate uniformity (U) and entropy (E). These quantities were subsequently correlated with the patient’s response to chemotherapy. Statistical significance was found with P < 0.05.

Results:

Fifteen patients were categorized as responders, and five as non-responders. The data showed that tumors of responders were significantly higher in U (P = 0.01) and lower in E (P < 0.01) than non-responders. This finding indicates that resistant tumors were more heterogeneous in their spatial distribution of ADC values. While this difference in ADC heterogeneity was not always visually recognizable, it could be quantified by the data analytics.

Conclusions:

This study demonstrates that the quantitative readout of tumor heterogeneity in micro-cellularity is associated with the patient’s defined response to chemotherapy. Quantification of tumor ADC heterogeneity may provide useful information to enable the prediction of chemotherapeutic response prior to the treatment to improve patient outcomes.

Predicting the nodal status in gastric cancers: The role of apparent diffusion coefficient histogram characteristic analysis

PURPOSE

To explore the application of histogram analysis in preoperative T and N staging of gastric cancers, with a focus on characteristic parameters of apparent diffusion coefficient (ADC) maps.

MATERIALS AND METHODS

Eighty-seven patients with gastric cancers underwent diffusion weighted magnetic resonance imaging (b=0, 1000s/mm²), which generated ADC maps. Whole-volume histogram analysis was performed on ADC maps and 7 characteristic parameters were obtained. All those patients underwent surgery and postoperative pathologic T and N stages were determined.

RESULTS

Four parameters, including skew, kurtosis, s-sD_av and sample number, showed significant differences among gastric cancers at different T and N stages. Most parameters correlated with T and N stages significantly and worked in differentiating gastric cancers at different T or N stages. Especially skew yielded a sensitivity of 0.758, a specificity of 0.810, and an area under the curve (AUC) of 0.802 for differentiating gastric cancers with and without lymph node metastasis (P<0.001). All the parameters, except AUC_low, showed good or excellent inter-observer agreement with intra-class correlation coefficients ranging from 0.710 to 0.991.

CONCLUSION

Characteristic parameters derived from whole-volume ADC histogram analysis could help assessing preoperative T and N stages of gastric cancers.

Preoperative prediction of muscular invasiveness of bladder cancer with radiomic features on conventional MRI and its high-order derivative maps

PURPOSE

To determine radiomic features which are capable of reflecting muscular invasiveness of bladder cancer (BC) and propose a non-invasive strategy for the differentiation of muscular invasiveness preoperatively.

METHODS

Sixty-eight patients with clinicopathologically confirmed BC were included in this retrospective study. A total of 118 cancerous volumes of interest (VOI) were segmented from patients' T2 weighted MR images (T2WI), including 34 non-muscle invasive bladder carcinomas (NMIBCs, stage <T2) and 84 muscle invasive ones (MIBCs, stage ≥T2). The radiomic features quantifying tumor signal intensity and textures were extracted from each VOI and its high-order derivative maps to characterize heterogeneity of tumor tissues. Statistical analysis was used to build radiomic signatures with significant inter-group differences of NMIBCs and MIBCs. The synthetic minority oversampling technique (SMOTE) and a support vector machine (SVM)-based feature selection and classification strategy were proposed to first rebalance the imbalanced sample size and then further select the most predictive and compact signature subset to verify its differentiation capability.

RESULTS

From each tumor VOI, a total of 63 radiomic features were derived and 30 of them showed significant inter-group differences (P ≤ 0.01). By using the SVM-based feature selection algorithm with rebalanced samples, an optimal subset including 13 radiomic signatures was determined. The area under receiver operating characteristic curve and Youden index were improved to 0.8610 and 0.7192, respectively.

CONCLUSION

3D radiomic signatures derived from T2WI and its high-order derivative maps could reflect muscular invasiveness of bladder cancer, and the proposed strategy can be used to facilitate the preoperative prediction of muscular invasiveness in patients with bladder cancer.

Utility of whole-lesion ADC histogram metrics for assessing the malignant potential of pancreatic intraductal papillary mucinous neoplasms (IPMNs)

PURPOSE

To evaluate whole-lesion ADC histogram metrics for assessing the malignant potential of pancreatic intraductal papillary mucinous neoplasms (IPMNs), including in comparison with conventional MRI features.

METHODS

Eighteen branch-duct IPMNs underwent MRI with DWI prior to resection (n = 16) or FNA (n = 2). A blinded radiologist placed 3D volumes-of-interest on the entire IPMN on the ADC map, from which whole-lesion histogram metrics were generated. The reader also assessed IPMN size, mural nodularity, and adjacent main-duct dilation. Benign (low-to-intermediate grade dysplasia; n = 10) and malignant (high-grade dysplasia or invasive adenocarcinoma; n = 8) IPMNs were compared.

RESULTS

Whole-lesion ADC histogram metrics demonstrating significant differences between benign and malignant IPMNs were: entropy (5.1 ± 0.2 vs. 5.4 ± 0.2; p = 0.01, AUC = 86%); mean of the bottom 10th percentile (2.2 ± 0.4 vs. 1.6 ± 0.7; p = 0.03; AUC = 81%); and mean of the 10-25th percentile (2.8 ± 0.4 vs. 2.3 ± 0.6; p = 0.04; AUC = 79%). The overall mean ADC, skewness, and kurtosis were not significantly different between groups (p ≥ 0.06; AUC = 50-78%). For entropy (highest performing histogram metric), an optimal threshold of >5.3 achieved a sensitivity of 100%, a specificity of 70%, and an accuracy of 83% for predicting malignancy. No significant difference (p = 0.18-0.64) was observed between benign and malignant IPMNs for cyst size ≥3 cm, adjacent main-duct dilatation, or mural nodule. At multivariable analysis of entropy in combination with all other ADC histogram and conventional MRI features, entropy was the only significant independent predictor of malignancy (p = 0.004).

CONCLUSION

Although requiring larger studies, ADC entropy obtained from 3D whole-lesion histogram analysis may serve as a biomarker for identifying the malignant potential of IPMNs, independent of conventional MRI features.

Non-small cell lung cancer: Whole-lesion histogram analysis of the apparent diffusion coefficient for assessment of tumor grade, lymphovascular invasion and pleural invasion

PURPOSE

Investigating the diagnostic accuracy of histogram analyses of apparent diffusion coefficient (ADC) values for determining non-small cell lung cancer (NSCLC) tumor grades, lymphovascular invasion, and pleural invasion.

MATERIALS AND METHODS

We studied 60 surgically diagnosed NSCLC patients. Diffusion-weighted imaging (DWI) was performed in the axial plane using a navigator-triggered single-shot, echo-planar imaging sequence with prospective acquisition correction. The ADC maps were generated, and we placed a volume-of-interest on the tumor to construct the whole-lesion histogram. Using the histogram, we calculated the mean, 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles of ADC, skewness, and kurtosis. Histogram parameters were correlated with tumor grade, lymphovascular invasion, and pleural invasion. We performed a receiver operating characteristics (ROC) analysis to assess the diagnostic performance of histogram parameters for distinguishing different pathologic features.

RESULTS

The ADC mean, 10th, 25th, 50th, 75th, 90th, and 95th percentiles showed significant differences among the tumor grades. The ADC mean, 25th, 50th, 75th, 90th, and 95th percentiles were significant histogram parameters between high- and low-grade tumors. The ROC analysis between high- and low-grade tumors showed that the 95th percentile ADC achieved the highest area under curve (AUC) at 0.74. Lymphovascular invasion was associated with the ADC mean, 50th, 75th, 90th, and 95th percentiles, skewness, and kurtosis. Kurtosis achieved the highest AUC at 0.809. Pleural invasion was only associated with skewness, with the AUC of 0.648.

CONCLUSIONS

ADC histogram analyses on the basis of the entire tumor volume are able to stratify NSCLCs' tumor grade, lymphovascular invasion and pleural invasion.

Dynamic Contrast-enhanced MR Imaging in Renal Cell Carcinoma: Reproducibility of Histogram Analysis on Pharmacokinetic Parameters

Pharmacokinetic parameters derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) have been increasingly used to evaluate the permeability of tumor vessel. Histogram metrics are a recognized promising method of quantitative MR imaging that has been recently introduced in analysis of DCE-MRI pharmacokinetic parameters in oncology due to tumor heterogeneity. In this study, 21 patients with renal cell carcinoma (RCC) underwent paired DCE-MRI studies on a 3.0 T MR system. Extended Tofts model and population-based arterial input function were used to calculate kinetic parameters of RCC tumors. Mean value and histogram metrics (Mode, Skewness and Kurtosis) of each pharmacokinetic parameter were generated automatically using ImageJ software. Intra- and inter-observer reproducibility and scan–rescan reproducibility were evaluated using intra-class correlation coefficients (ICCs) and coefficient of variation (CoV). Our results demonstrated that the histogram method (Mode, Skewness and Kurtosis) was not superior to the conventional Mean value method in reproducibility evaluation on DCE-MRI pharmacokinetic parameters (K^trans & V_e) in renal cell carcinoma, especially for Skewness and Kurtosis which showed lower intra-, inter-observer and scan-rescan reproducibility than Mean value. Our findings suggest that additional studies are necessary before wide incorporation of histogram metrics in quantitative analysis of DCE-MRI pharmacokinetic parameters.

Assessment of histological differentiation in gastric cancers using whole-volume histogram analysis of apparent diffusion coefficient maps

PURPOSE

To investigate the efficacy of histogram analysis of the entire tumor volume in apparent diffusion coefficient (ADC) maps for differentiating between histological grades in gastric cancer.

MATERIALS AND METHODS

Seventy-eight patients with gastric cancer were enrolled in a retrospective 3.0T magnetic resonance imaging (MRI) study. ADC maps were obtained at two different b values (0 and 1000 sec/mm² ) for each patient. Tumors were delineated on each slice of the ADC maps, and a histogram for the entire tumor volume was subsequently generated. A series of histogram parameters (eg, skew and kurtosis) were calculated and correlated with the histological grade of the surgical specimen. The diagnostic performance of each parameter for distinguishing poorly from moderately well-differentiated gastric cancers was assessed by using the area under the receiver operating characteristic curve (AUC).

RESULTS

There were significant differences in the 5^th , 10^th , 25^th , and 50^th percentiles, skew, and kurtosis between poorly and well-differentiated gastric cancers (P < 0.05). There were correlations between the degrees of differentiation and histogram parameters, including the 10^th percentile, skew, kurtosis, and max frequency; the correlation coefficients were 0.273, -0.361, -0.339, and -0.370, respectively. Among all the histogram parameters, the max frequency had the largest AUC value, which was 0.675.

CONCLUSION

Histogram analysis of the ADC maps on the basis of the entire tumor volume can be useful in differentiating between histological grades for gastric cancer.

LEVEL OF EVIDENCE

4 J. Magn. Reson. Imaging 2017;45:440-449.

Improving Staging in Bladder Cancer: The Increasing Role of Multiparametric Magnetic Resonance Imaging

CONTEXT

In bladder cancer (BCa) patients, accurate local and regional tumor staging is required when planning treatment. Clinical understaging frequently occurs and leads to undertreatment of the disease, with a negative impact on survival. An improvement in staging accuracy could be attained by advances in imaging. Magnetic resonance imaging (MRI) is currently the best imaging technique for locoregional staging for several malignancies because of its superior soft tissue contrast resolution with the advantage of avoiding exposure to ionizing radiation. Important improvements in MRI technology have led to the introduction of multiparametric MRI (mpMRI), which combines anatomic and functional evaluation.

OBJECTIVE

To review the fundamentals of mpMRI in BCa and to provide a contemporary overview of the available data on the role of this emerging imaging technology.

EVIDENCE ACQUISITION

A nonsystematic literature search using the Medline and Cochrane Library databases was performed up to March 2016. Additional articles were retrieved by cross-matching references of selected articles. Only articles reporting complete data with regard to image acquisition protocols, locoregional staging, monitoring response to therapy, and detection of locoregional recurrence after primary treatment in BCa patients were selected.

EVIDENCE SYNTHESIS

Standardization of acquisition and reporting protocols for bladder mpMRI is paramount. Combining anatomic and functional sequences improves the accuracy of local tumor staging compared with conventional imaging alone. Diffusion-weighted imaging may distinguish BCa type and grade. Functional sequences are capable of monitoring response to chemotherapy and radiation therapy. Diffusion-weighted imaging enhanced by lymphotropic nanoparticles showed high accuracy in pelvic lymph node staging compared with conventional cross-sectional imaging.

CONCLUSIONS

In BCa patients, mpMRI appears a promising tool for accurate locoregional staging, predicting tumor aggressiveness and monitoring response to therapy. Further large-scale studies are needed to confirm these findings.

PATIENT SUMMARY

Better imaging through improved technology will improve outcomes in bladder cancer patients. We reviewed the emerging use of multiparametric magnetic resonance imaging for staging and monitoring bladder cancer. Multiparametric magnetic resonance imaging appears more accurate than current methods for local and nodal staging and monitoring tumor response to treatment, but requires further investigation.

Multiparametric MRI of the prostate: diagnostic performance and interreader agreement of two scoring systems

OBJECTIVE

To compare the diagnostic accuracies and interreader agreements of the Prostate Imaging Reporting and Data System (PI-RADS) v. 2 and University of California San Francisco (UCSF) multiparametric prostate MRI scale for diagnosing clinically significant prostate cancer.

METHODS

This institutional review board-approved retrospective study included 49 males who had 1.5 T endorectal MRI and prostatectomy. Two radiologists scored suspicious lesions on MRI using PI-RADS v. 2 and the UCSF scale. Percent agreement, 2 × 2 tables and the area under the receiver operating characteristic curves (Az) were used to assess and compare the individual and overall scores of these scales. Interreader agreements were estimated with kappa statistics.

RESULTS

Reader 1 (R1) detected 78 lesions, and Reader 2 (R2) detected 80 lesions. Both identified 52 of 65 significant cancers. The Az for PI-RADS v. 2 and UCSF scale for R1 were 0.68 and 0.69 [T2 weighted imaging (T2WI)], 0.75 and 0.68 [diffusion-weighted imaging (DWI)] and 0.64 and 0.72 (overall score), respectively, and were 0.72 and 0.75 (T2WI), 0.73 and 0.67 (DWI) and 0.66 and 0.75 (overall score) for R2. The dynamic contrast-enhanced percent agreements between scales were 100% (R1) and 95% (R2). PI-RADS v. 2 DWI of R1 performed better than UCSF DWI (Az = 0.75 vs Az = 0.68; p = 0.05); no other differences were found. The interreader agreements were higher for PI-RADS v. 2 (T2WI: 0.56 vs 0.42; DWI: 0.60 vs 0.46; overall: 0.61 vs 0.42). The UCSF approach to derive the overall PI-RADS v. 2 scores increased the Az for the identification of significant cancer (R1 to 0.76, p < 0.05; R2 to 0.71, p = 0.35).

CONCLUSION

Although PI-RADS v. 2 DWI score may have a higher discriminatory performance than the UCSF scale counterpart to diagnose clinically significant cancer, the utilization of the UCSF scale weighing system for the integration of PI-RADS v. 2 individual parameter scores improved the accuracy its overall score.

ADVANCES IN KNOWLEDGE

PI-RADS v. 2 is moderately accurate for the identification of clinically significant prostate cancer, but the utilization of alternative approaches to derive the overall PI-RADS v. 2 score, including the one used by the UCSF system, may improve its diagnostic accuracy.

Hypovascular hepatic nodules at gadoxetic acid-enhanced MRI: whole-lesion hepatobiliary phase histogram metrics for prediction of progression to arterial-enhancing hepatocellular carcinoma

PURPOSE

To explore whole-lesion histogram analysis of the hepatobiliary phase (HBP) defect in indeterminate hypovascular liver lesions for predicting progression to arterial-enhancing hepatocellular carcinoma (HCC).

METHODS

Twenty patients undergoing gadoxetic acid-enhanced MRI for HCC screening with 12° and 25° flip angle (FA) HBP acquisitions demonstrating an indeterminate lesion showing HBP hypointensity but no arterial enhancement were included. Volumes-of-interest were placed on HBP defects, from which histogram metrics were obtained. Associations between these metrics and progression to arterial-enhancing HCC on follow-up imaging were investigated. Lesions were also assessed for the presence of a signal abnormality on conventional sequences.

RESULTS

40% of lesions progressed to arterial-enhancing HCC; 60% were stable at ≥6 months follow-up. Neither T2-hyperintensity increased diffusion signal nor portal/equilibrium phase washout was different between progressing and nonprogressing lesions (p = 1.0). Among direct signal intensity-based measures (overall mean; mean of bottom 10th, 10-25th, and 25-50th percentiles), area-under-the-curve (AUC) for prediction of progression to arterial-enhancing HCC was consistently higher at 25° (range 0.619-0.657) than at 12° (range 0.512-0.548). However, at both FAs, the four measures with highest AUC were measures related to lesion texture and heterogeneity [standard deviation (SD), coefficient of variation (CV), skewness, and entropy], having AUC of 0.655-0.750 at 12° and 0.686-0.800 at 25. The metric with highest AUC at 12° was SD (AUC = 0.750) and at 25° was CV (AUC = 0.800).

CONCLUSION

Whole-lesion histogram HBP measures of indeterminate hypovascular liver lesions may help predict progression to arterial-enhancing HCC by reflecting greater lesion heterogeneity, particularly at higher FA. Larger studies are therefore warranted.

Pitfalls and Limitations of Diffusion-Weighted Magnetic Resonance Imaging in the Diagnosis of Urinary Bladder Cancer

Adequately selecting a therapeutic approach for bladder cancer depends on accurate grading and staging. Substantial inaccuracy of clinical staging with bimanual examination, cystoscopy, and transurethral resection of bladder tumor has facilitated the increasing utility of magnetic resonance imaging to evaluate bladder cancer. Diffusion-weighted imaging (DWI) is a noninvasive functional magnetic resonance imaging technique. The high tissue contrast between cancers and surrounding tissues on DWI is derived from the difference of water molecules motion. DWI is potentially a useful tool for the detection, characterization, and staging of bladder cancers; it can also monitor posttreatment response and provide information on predicting tumor biophysical behaviors. Despite advancements in DWI techniques and the use of quantitative analysis to evaluate the apparent diffusion coefficient values, there are some inherent limitations in DWI interpretation related to relatively poor spatial resolution, lack of cancer specificity, and lack of standardized image acquisition protocols and data analysis procedures that restrict the application of DWI and reproducibility of apparent diffusion coefficient values. In addition, inadequate bladder distension, artifacts, thinness of bladder wall, cancerous mimickers of normal bladder wall and benign lesions, and variations in the manifestation of bladder cancer may interfere with diagnosis and monitoring of treatment. Recognition of these pitfalls and limitations can minimize their impact on image interpretation, and carefully applying the analyzed results and combining with pathologic grading and staging to clinical practice can contribute to the selection of an adequate treatment method to improve patient care.