Luminal-type breast cancer: correlation of apparent diffusion coefficients with the Ki-67 labeling index

The Apparent Diffusion Coefficient (ADC) is a useful biomarker in predicting metastatic colon cancer using the ADC-value of the primary tumor

Purpose

To investigate the role of the apparent diffusion coefficient (ADC) as a potential imaging biomarker to predict metastasis (lymph node metastasis and distant metastasis) in colon cancer based on the ADC-value of the primary tumor.

Methods

Thirty patients (21M, 9F) were included retrospectively. All patients received a 1.5T MRI of the colon including T2 and DWI sequences. ADC maps were calculated for each patient. An expert reader manually delineated all colon tumors to measure mean ADC and histogram metrics (mean, min, max, median, standard deviation (SD), skewness, kurtosis, 5th-95th percentiles) were calculated. Advanced colon cancer was defined as lymph node mestastasis (N+) or distant metastasis (M+). The student Mann Whitney U-test was used to assess the differences between the ADC means of early and advanced colon cancer. To compare the accuracy of lymph node metastasis (N+) prediction based on morpholigical criteria versus ADC-value of the primary tumor, two blinded readers, determined the lymph node metastasis (N0 vs N+) based on morphological criteria. The sensitivity and specificity in predicting lymph node metastasis was calculated for both readers and for the ADC-value of the primary tumor, with histopathology results as the gold standard.

Results

There was a significant difference between the mean ADC-value of advanced versus early tumors (p = 0.002). The optimal cut off value was 1179 * 10⁻³ mm2/s with an area under the curve (AUC) of 0.83 and a sensitivity and specificity of 81% and 86% respectively to predict advanced tumors. Histogram analyses did not add any significant additional value.

The sensitivity and specificity for the prediction of lymph node metastasis based on morphological criteria were 40% and 63% for reader 1 and 30% and 88% for reader 2 respectively. The primary tumor ADC-value using 1.179 * 10⁻³ mm2/s as threshold had a 100% sensitivity and specificity in predicting lymph node metastasis.

Conclusion

The ADC-value of the primary tumor has the potential to predict advanced colon cancer, defined as lymph node metastasis or distant metastasis, with lower ADC values significantly associated with advanced tumors. Furthermore the ADC-value of the primary tumor increases the prediction accuracy of lymph node metastasis compared with morphological criteria.

Correlations between Apparent Diffusion Coefficient and Gleason Score in Prostate Cancer: A Systematic Review

BACKGROUND

Reported data regarding the associations between apparent diffusion coefficient (ADC) of diffusion-weighted imaging (DWI) and Gleason score in prostate cancer (PC) are inconsistent.

OBJECTIVE

The aim of the present systematic review was to analyze relationships between ADC and Gleason score in PC.

DESIGN, SETTING, AND PARTICIPANTS

MEDLINE library, SCOPUS, and EMBASE databases were screened for relationships between ADC and Gleason score in PC up to April 2018. Overall, 39 studies with 2457 patients were identified. Data on the following parameters were extracted from the literature: number of patients, cancer localization, and correlation coefficients between ADC and Gleason score.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Associations between ADC and Gleason score were analyzed by the Spearman's correlation coefficient.

RESULTS AND LIMITATIONS

In overall sample, the pooled correlation coefficient between ADC and Gleason score was -0.45 (95% confidence interval [CI]=[-0.50; -0.40]). In PC in the transitional zone, the pooled correlation coefficient was -0.22 (95% CI=[-0.47; 0.03]). In PC in the peripheral zone, the pooled correlation coefficient was -0.48 (95% CI=[-0.54; -0.42]).

CONCLUSIONS

In PC located in the peripheral zone, ADC correlated moderately with Gleason score. In PC located in the transitional zone, ADC correlated weakly with Gleason score.

PATIENT SUMMARY

We reviewed studies using apparent diffusion coefficient for the prediction of Gleason score in prostate cancer patients.

Associations Between Magnetic Resonance Imaging Findings and Clincopathologic Factors in Triple-Negative Breast Cancer

OBJECTIVE

The aim of the study was to evaluate the magnetic resonance imaging findings associated with clinicopathologic factors in patients with triple-negative breast cancer.

METHODS

One hundred one patients with surgically confirmed triple-negative breast cancer who underwent preoperative breast magnetic resonance imaging with diffusion-weighted imaging (DWI) were included in this study. Presence of rim enhancement on contrast-enhanced T1-weighted imaging and hyperintense rim on DWI were visually assessed. Pathologic data about presence of recurrence and presence of lymphovascular invasion (LVI) were reviewed. Statistics for relative risk of recurrence carried out.

RESULTS

Of the 101, 13 cases (12.9%) were recurred after a median follow-up of 18.5 months. Rim enhancement was more frequently seen in the LVI-positive group (P = 0.046). Hyperintense rim on DWI and apparent diffusion coefficient values showed no significant relationship with clinical-pathologic factors.

CONCLUSIONS

Rim enhancement was significantly associated with positive LVI status in patients with triple-negative breast cancer. Our study suggests that rim enhancement may be useful to predict the prognosis.

Histogram Analysis of T1-Weighted, T2-Weighted, and Postcontrast T1-Weighted Images in Primary CNS Lymphoma: Correlations with Histopathological Findings-a Preliminary Study

PURPOSE

Previously, some reports mentioned that magnetic resonance imaging (MRI) can predict histopathological features in primary CNS lymphoma (PCNSL). The reported data analyzed diffusion-weighted imaging findings. The aim of this study was to investigate possible associations between histopathological findings, such as tumor cellularity, nucleic areas and proliferation index Ki-67, and signal intensity on T1-weighted and T2-weighted images in PCNSL.

PROCEDURES

For this study, 18 patients with PCNSL were retrospectively investigated by histogram analysis on precontrast and postcontrast T1-weighted and fluid-attenuated inversion recovery (FLAIR) images. For every patient, histopathology parameters, nucleic count, total nucleic area, and average nucleic area, as well as Ki-67 index, were estimated.

RESULTS

Correlation analysis identified several statistically significant associations. Skewness derived from precontrast T1-weighted images correlated with Ki-67 index (p = - 0.55, P = 0.028). Furthermore, entropy derived from precontrast T1-weighted images correlated with average nucleic area (p = 0.53, P = 0.04). Several parameters from postcontrast T1-weighted images correlated with nucleic count: maximum signal intensity (p = 0.59, P = 0.017), P75 (p = 0.56, P = 0.02), and P90 (p = 0.52, P = 0.04) as well as SD (p = 0.58, P = 0.02). Maximum signal intensity derived from FLAIR sequence correlated with nucleic count (p = 0.50, P = 0.03).

CONCLUSION

Histogram-derived parameters of conventional MRI sequences can reflect different histopathological features in PSNCL.

Association Between Shear Wave Elastography of Virtual Touch Tissue Imaging Quantification Parameters and the Ki-67 Proliferation Status in Luminal-Type Breast Cancer

OBJECTIVES

To evaluate the association between shear wave elastography parameters using virtual touch tissue imaging quantification (VTIQ) and the Ki-67 index in luminal-type breast cancer.

METHODS

Eighty-one patients with 82 lesions of pathologic confirmed luminal-type breast cancer underwent virtual touch tissue imaging quantification examination before surgery between December 2015 and June 2016. Patients were divided into 2 groups according to the Ki-67 index (≥14% versus < 14%), which is used to define luminal type B and luminal type A, respectively. The mean shear wave velocity (SWV_mean ) and lesion-to-adjacent tissues ratio (SWV ratio) were calculated for each lesion.

RESULTS

The SWV_mean , SWV ratio, histologic grade, axillary lymph node involvement, and lymphovascular invasion showed a significant positive association with a high Ki-67 index (all P < .05). Receiver operating characteristic curve analysis for the differential diagnosis between high (≥14%) and low (<14%) Ki-67 groups displayed that the optimal cutoff value for SWV_mean and SWV ratio were 3.99 meters per second and 2.861, with sensitivity 94% and 72%, specificity 40.6% and 56.2%, and area under the receiver operating characteristic curve of 0.689 and 0.651, respectively. Univariate analysis showed that SWV_mean (P = .005), SWV ratio (P = .029), histologic grade (P = .011), presence of axillary node involvement (P = .004), and lymphovascular invasion (P = .008) were significantly associated with high Ki-67 status. Multivariable analysis displayed that SWV_mean (hazard ratio [HR], 1.459, 95% confidence interval [CI], 1.028-2.072; P = .035), histologic grade (HR, 4.105; 95% CI, 1.142-14.763; P = .031), and presence of axillary node involvement (HR, 3.75; 95% CI, 1.228-11.453; P = .020) maintained significance for predicting high Ki-67 status.

CONCLUSIONS

The SWV_mean using the virtual touch tissue imaging quantification method showed significant correlation with the Ki-67 index, suggesting the potential to assess tumor proliferation status in luminal-type breast cancer with a noninvasive manner.

CT scan and magnetic resonance diffusion-weighted imaging in the diagnosis and treatment of esophageal cancer

Value of computed tomography (CT) scan and diffusion-weighted imaging (DWI) in the diagnosis and treatment of esophageal cancer was investigated. Seventy-eight patients with esophageal cancer treated in Jinan Central Hospital (Jinan, China) from January 2013 to June 2014 were selected. All patients underwent CT scan and DWI examination, and their clinical history data were analyzed. DWI was conducted. The short-term curative effect and the 3-year survival rate of patients in the high apparent diffusion coefficient (ADC) value group and the low ADC value group were compared; ADC values in the complete remission (CR) group and the partial remission (PR) group were compared. The difference in value between the length of esophageal lesions and the length of pathological specimens measured by CT scan was significantly different from that detected via DWI examination with b=600, 800 and 1,000 sec/mm², respectively (P<0.05). The diagnostic rate of esophageal cancer via CT scan was significantly lower than that via DWI examination (P<0.05). After radiotherapy, the clinical control rate in the high ADC value group was significantly higher than that in the low ADC value group, and the 3-year survival rate in the former was significantly higher than that in the latter (P<0.05). In the 2nd week during radiotherapy and at the end of radiotherapy, the ADC values in the CR group were significantly higher than those in the PR group (P<0.05). In the 2nd week during radiotherapy and at the end of radiotherapy, ADC values were used to predict the CR rate of radiotherapy for esophageal cancer, and the areas under the receiver operating characteristic (ROC) curve were 0.776 and 0.935, respectively. Compared with CT scan, DWI has higher diagnostic rate and higher sensitivity. The length of esophageal tumor measured by DWI is close to that of pathological entity, which can guide the delineation of the target area of esophageal cancer.

Intravoxel incoherent motion magnetic resonance imaging for breast cancer: A comparison with benign lesions and evaluation of heterogeneity in different tumor regions with prognostic factors and molecular classification

The objective of the present study was to compare the differentiation between breast cancer and benign breast lesions and study regional distribution characteristics in various subtypes of breast cancer using intravoxel incoherent motion (IVIM) parameters. This retrospective study involved 119 patients with breast cancer and 22 patients with benign breast lesions, who underwent 3.0T breast magnetic resonance imaging examinations. The apparent diffusion coefficient (ADC) and IVIM parameters (slow ADC, fast ADC and fraction of fast ADC) were obtained from patients with breast cancer and benign lesions using diffusion-weighted imaging (DWI) with b-values of 0, 50, 100, 150, 200, 400, 500, 1,000 and 1,500 sec/mm². Compared with patients with benign breast lesions, patients with breast cancer exhibited decreased ADC (P<0.001), slow ADC (P<0.001) and fast ADC (P<0.001) values, and higher fraction of fast ADC (P<0.001) values. Tumors with metastatic axillary lymph nodes demonstrated increased fraction of fast ADC values (P<0.001) and decreased slow ADC values (P<0.001) compared with tumors without metastatic axillary lymph nodes. The Fast ADC values of tumor tissues in estrogen receptor (ER) and progesterone receptor (PR) negative groups were higher than in positive groups (P<0.001), and the slow ADC values of tumor tissues were lower in ER and PR negative groups than positive groups (P<0.001). Luminal B (HER2- negative) tumor (P<0.001) and peritumor (P<0.001) tissues exhibited decreased fraction of fast ADC values, in comparison with other subtypes. Triple-negative breast cancer (TNBC) tumor tissue exhibited increased fast ADC (P<0.001) and fraction of fast ADC values (P<0.001), and decreased slow ADC values (P<0.001), when compared with other subtypes. The TNBC tumor edge tissues had increased fraction of fast ADC values compared with other subtypes (P<0.01) and TNBC tumor tissues (P<0.05). Therefore, the IVIM parameters of tumor, tumor edge and peritumor tissues in various subtypes of breast cancer may be useful for differentiation of breast cancer subtypes and to assess the invasive extent of the tumors.

Association among T2 signal intensity, necrosis, ADC and Ki-67 in estrogen receptor-positive and HER2-negative invasive ductal carcinoma

PURPOSE

To determine whether T2 signal intensity, necrosis, and ADC values are associated with Ki-67 in patients with Estrogen Receptor (ER)-positive and Human epidermal growth factor receptor type 2 (HER2)-negative invasive ductal carcinoma (IDC).

MATERIALS AND METHODS

Between March 2012 and February 2013, one hundred eighty seven women with ER-positive and HER2-negative IDC who underwent breast MRI and subsequent surgery were included. Intratumoral signal intensity was evaluated based on a combination of T2-weighted (low or equal, high, or very high) and contrast-enhanced MR images (enhancement or not). Necrosis was defined as very high T2 and no enhancement. Using the analysis of variance and pairwise t-test, a model based on intratumoral signal intensity was developed to assess Ki-67 of the surgical specimen. Inter-observer agreement for the developed model was analyzed. Conventional mean and minimum apparent diffusion coefficient (ADC) measurements were performed and correlated with Ki-67.

RESULTS

As the grade of the developed model increased (Grade I: low or equal T2, Grade II: high T2, or necrosis < 50%, Grade III: necrosis ≥ 50%), mean Ki-67 significantly increased (Grade I to III: 12.5%, 17.6%, 45.0%, respectively; P < 0.001). Good inter-observer agreement was found for the model (κ = 0.846, P < 0.001). ADC did not show significant correlations with Ki-67 (Pearson's correlation coefficient, 0.140 [P = 0.057] for mean ADC; -0.079 [P = 0.284] for minimum ADC).

CONCLUSION

Intratumoral signal intensity but not ADC was associated with Ki-67 in patients with ER-positive and HER2-negative IDC.

Intravoxel incoherent motion magnetic resonance imaging for breast cancer: A comparison with benign lesions and evaluation of heterogeneity in different tumor regions with prognostic factors and molecular classification

The objective of the present study was to compare the differentiation between breast cancer and benign breast lesions and study regional distribution characteristics in various subtypes of breast cancer using intravoxel incoherent motion (IVIM) parameters. This retrospective study involved 119 patients with breast cancer and 22 patients with benign breast lesions, who underwent 3.0T breast magnetic resonance imaging examinations. The apparent diffusion coefficient (ADC) and IVIM parameters (slow ADC, fast ADC and fraction of fast ADC) were obtained from patients with breast cancer and benign lesions using diffusion-weighted imaging (DWI) with b-values of 0, 50, 100, 150, 200, 400, 500, 1,000 and 1,500 sec/mm². Compared with patients with benign breast lesions, patients with breast cancer exhibited decreased ADC (P<0.001), slow ADC (P<0.001) and fast ADC (P<0.001) values, and higher fraction of fast ADC (P<0.001) values. Tumors with metastatic axillary lymph nodes demonstrated increased fraction of fast ADC values (P<0.001) and decreased slow ADC values (P<0.001) compared with tumors without metastatic axillary lymph nodes. The Fast ADC values of tumor tissues in estrogen receptor (ER) and progesterone receptor (PR) negative groups were higher than in positive groups (P<0.001), and the slow ADC values of tumor tissues were lower in ER and PR negative groups than positive groups (P<0.001). Luminal B (HER2- negative) tumor (P<0.001) and peritumor (P<0.001) tissues exhibited decreased fraction of fast ADC values, in comparison with other subtypes. Triple-negative breast cancer (TNBC) tumor tissue exhibited increased fast ADC (P<0.001) and fraction of fast ADC values (P<0.001), and decreased slow ADC values (P<0.001), when compared with other subtypes. The TNBC tumor edge tissues had increased fraction of fast ADC values compared with other subtypes (P<0.01) and TNBC tumor tissues (P<0.05). Therefore, the IVIM parameters of tumor, tumor edge and peritumor tissues in various subtypes of breast cancer may be useful for differentiation of breast cancer subtypes and to assess the invasive extent of the tumors.

Risk stratification of ductal carcinoma in situ using whole-lesion histogram analysis of the apparent diffusion coefficient

OBJECTIVES

To investigate the value of the whole-lesion histogram apparent diffusion coefficient (ADC) metrics for differentiating low-risk from non-low-risk ductal carcinoma in situ (DCIS).

METHODS

The authors identified 93 women with pure DCIS who had undergone preoperative MR imaging and diffusion-weighted imaging from 2013 to 2016. Histogram analysis of pixel-based ADC data of the whole tumour volume was performed by two radiologists using a software tool. The results were compared between low-risk and non-low-risk DCIS. Associations between quantitative ADC metrics and low-risk DCIS were evaluated by receiver operating characteristics (ROC) curve and logistic regression analyses.

RESULTS

In whole-lesion histogram analysis, mean ADC and 5th, 50th and 95th percentiles of ADC were significantly different between low-risk and non-low-risk DCIS (1.522, 1.207, 1.536 and 1.854 × 10^-3 mm²/s versus 1.270, 0.917, 1.261 and 1.657 × 10^-3 mm²/s, respectively; p = .004, p = .003, p = .004 and p = .024, respectively). ROC curve analysis for differentiating low-risk DCIS revealed that 5th percentile ADC yielded the largest area under the curve (0.786) among the metrics of whole-lesion histogram, and the optimal cut-off point was 1.078 × 10^-3 mm²/s (sensitivity 80%, specificity 75.9%, p = .001). Multivariate regression analysis revealed that a high 5th percentile of ADC (> 1.078× 10^-3 mm²/s; odds ratio [OR] = 10.494, p = .016), small tumour size (≤ 2 cm; OR = 12.692, p = .008) and low Ki-67 status (< 14%; OR = 10.879, p = .046) were significantly associated with low-risk DCIS.

CONCLUSIONS

Assessment with whole-lesion histogram analysis of the ADC could be helpful for identifying patients with low-risk DCIS.

KEY POINTS

• Whole-lesion histogram ADC metrics could be helpful for differentiating low-risk from non-low-risk DCIS. • A high 5th percentile ADC was a significant factor associated with low-risk DCIS. • Risk stratification of DCIS is important for their management.

A machine learning approach to radiogenomics of breast cancer: a study of 922 subjects and 529 DCE-MRI features

BACKGROUND

Recent studies showed preliminary data on associations of MRI-based imaging phenotypes of breast tumours with breast cancer molecular, genomic, and related characteristics. In this study, we present a comprehensive analysis of this relationship.

METHODS

We analysed a set of 922 patients with invasive breast cancer and pre-operative MRI. The MRIs were analysed by a computer algorithm to extract 529 features of the tumour and the surrounding tissue. Machine-learning-based models based on the imaging features were trained using a portion of the data (461 patients) to predict the following molecular, genomic, and proliferation characteristics: tumour surrogate molecular subtype, oestrogen receptor, progesterone receptor and human epidermal growth factor status, as well as a tumour proliferation marker (Ki-67). Trained models were evaluated on the set of the remaining 461 patients.

RESULTS

Multivariate models were predictive of Luminal A subtype with AUC = 0.697 (95% CI: 0.647-0.746, p < .0001), triple negative breast cancer with AUC = 0.654 (95% CI: 0.589-0.727, p < .0001), ER status with AUC = 0.649 (95% CI: 0.591-0.705, p < .001), and PR status with AUC = 0.622 (95% CI: 0.569-0.674, p < .0001). Associations between individual features and subtypes we also found.

CONCLUSIONS

There is a moderate association between tumour molecular biomarkers and algorithmically assessed imaging features.

Diffusion-weighted breast imaging

Magnetic resonance imaging (MRI) of the breast represents one of the most sensitive imaging modalities in breast cancer detection. Diffusion-weighted imaging (DWI) is a sequence variation introduced as a complementary MRI technique that relies on mapping the diffusion process of water molecules thereby providing additional information about the underlying tissue. Since water diffusion is more restricted in most malignant tumors than in benign ones owing to the higher cellularity of the rapidly proliferating neoplasia, DWI has the potential to contribute to the identification and characterization of suspicious breast lesions. Thus, DWI might increase the diagnostic accuracy of breast MRI and its clinical value. Future applications including optimized DWI sequences, technical developments in MR devices, and the application of radiomics/artificial intelligence algorithms may expand the potential of DWI in breast imaging beyond its current supplementary role.

Apparent diffusion coefficient histogram in breast cancer brain metastases may predict their biological subtype and progression

Our aims for this study were to investigate the relationship between diffusion weighted image (DWI) parameters of brain metastases (BMs) and biological markers of breast cancer, and moreover, to assess whether DWI parameters accurately predict patient outcomes. DWI data for 34 patients with BMs from breast cancer were retrospectively reviewed. Apparent diffusion coefficient (ADC) histogram parameters were calculated from all measurable BMs. Two region of interest (ROI) methods are used for the analysis: from the largest BM or from all measurable BMs per one patient. ADC histogram parameters were compared between positive and negative groups depending on ER/PR and HER2 statuses. Overall survival analysis after BM (OSBM) and BM-specific progression-free survival (BMPFS) was analyzed with ADC parameters. Regardless of ROI methods, 25th percentile of ADC histogram was significantly lower in the ER/PR-positive group than in the ER/PR-negative group (P < 0.05). Using ROIs from all measurable BMs, Peak location, 50th percentile, 75th percentile, and mean value of ADC histogram were also significantly lower in the ER/PR-positive group than in the ER/PR-negative group (P < 0.05). However, there was no significant difference between HER2-postive and negative group. On univariate analysis, using ROIs from all measurable BMs, lower 25th percentile, 50th percentile and mean of ADC were significant predictors for poor BMPFS. ADC histogram analysis may have a prognostic value over ER/PR status as well as BMPFS.

Can diffusion-weighted imaging predict tumor grade and expression of Ki-67 in breast cancer? A multicenter analysis

Background

Numerous studies have analyzed associations between apparent diffusion coefficient (ADC) and histopathological features such as Ki-67 proliferation index in breast cancer (BC), with mixed results. The purpose of this study was to perform a multicenter analysis to determine relationships between ADC and expression of Ki-67 and tumor grade in BC.

Methods

For this study, data from six centers were acquired. The sample comprises 870 patients (all female; mean age, 52.6 ± 10.8 years). In every case, breast magnetic resonance imaging with diffusion-weighted imaging was performed. The comparison of ADC values in groups was performed by Mann-Whitney U test where the p values are adjusted for multiple testing (Bonferroni correction). The association between ADC and Ki-67 values was calculated by Spearman’s rank correlation coefficient. Sensitivity, specificity, negative and positive predictive values, accuracy, and AUC were calculated for the diagnostic procedures. ADC thresholds were chosen to maximize the Youden index.

Results

Overall, data of 870 patients were acquired for this study. The mean ADC value of the tumors was 0.98 ± 0.22 × 10^− 3 mm² s^− 1. ROC analysis showed that it is impossible to differentiate high/moderate grade tumors from grade 1 lesions using ADC values. Youden index identified a threshold ADC value of 1.03 with a sensitivity of 56.2% and specificity of 67.9%. The positive predictive value was 18.2%, and the negative predictive value was 92.4%. The level of the Ki-67 proliferation index was available for 845 patients. The mean value was 12.33 ± 21.77%. ADC correlated with weak statistical significant with expression of Ki-67 (p = − 0.202, p < 0.001). ROC analysis was performed to distinguish tumors with high proliferative potential from tumors with low expression of Ki-67 using ADC values. Youden index identified a threshold ADC value of 0.91 (sensitivity 64%, specificity 50%, positive predictive value 67.7%, negative predictive value 45.0%).

Conclusions

ADC cannot be used as a surrogate marker for proliferation activity and/or for tumor grade in breast cancer.

A Predictor of Tumor Recurrence in Patients With Endometrial Carcinoma After Complete Resection of the Tumor: The Role of Pretreatment Apparent Diffusion Coefficient

Objectives

The aim of this study was to assess the prognostic and incremental value of pretreatment apparent diffusion coefficient (ADC) values of tumors for the prediction of tumor recurrence after complete resection of the tumor in patients with endometrial cancer.

Methods

This study enrolled 210 patients with stages IA to IIIC endometrial cancer who had undergone complete resection of the tumor and pretreatment magnetic resonance imaging. The minimum and mean ADC values (ADCmin, ADCmean) of tumors and normalized ADC (nADCmin, nADCmean) were calculated from magnetic resonance imaging. The primary outcome was recurrence-free survival (RFS). Receiver operating characteristic analysis was performed to compare the diagnostic performance of ADC values of 4 types. The Kaplan-Meier method, log-rank tests, and Cox regression were used to explore associations between recurrence and the ADC values with adjustment for clinicopathological factors.

Results

In receiver operating characteristic curve analysis, the areas under the curve were significant for ADCmean and nADCmean predicting tumor recurrence but were not significant for ADCmin and nADCmin. Regarding univariate analysis, ADCmean and nADCmean were significantly associated with increased risk of recurrence. Multivariate analysis showed that ADCmean and nADCmean remained independently associated with shorter RFS. In the high-risk group, the RFS of patients with lower ADC values (ADCmean and nADCmean) was significantly shorter than that of patients in the higher ADC value group.

Conclusions

Pretreatment tumor ADCmean and nADCmean were important imaging biomarkers for predicting recurrence in patients after complete resection of the tumor. They might improve existing risk stratification.

Oesophageal squamous cell carcinoma: histogram-derived ADC parameters are not predictive of tumour response to chemoradiotherapy

Objectives

To evaluate correlations between tumour response to definitive chemoradiotherapy (CRT) in oesophageal squamous cell carcinoma (SCC) and histogram-derived apparent diffusion coefficient (ADC) parameters on diffusion-weighted MR images.

Methods

Forty patients with clinical T3–4 oesophageal SCC underwent concurrent CRT. MR examination at 3 T was performed 1–3 days prior to CRT. Readout-segmented echo-planar diffusion imaging was used to acquire ADC maps. Pre- and post-treatment CT examinations were performed. Histogram parameters (mean, 10th, 25th, 50th, 75th, 90th percentiles, skewness and kurtosis) of the ADC values were compared with post-treatment disease status based on RECIST and the tumour regression ratio.

Results

None of the ADC parameters showed significant correlation with post-treatment status (range of Spearman’s ρ values − 0.19 to 0.14, range of p values 0.22–0.47) or tumour regression ratio (range of Spearman’s ρ values − 0.045 to 0.18, range of p values 0.26–0.96). Neither progression-free survival (PFS) (p = 0.17) nor overall survival (OS) (p = 0.15) was significantly different between the two groups corresponding to the lower (< median) and upper arms (≥ median) of the mean ADC values.

Conclusions

Histogram-derived pretreatment ADC parameters were not predictive imaging biomarkers for tumour response to CRT in patients with oesophageal SCC.

Key Points

• Apparent diffusion coefficient (ADC) values are derived from diffusion-weighted MR imaging.

• High-resolution diffusion-weighted images are generated by readout-segmented echo-planar diffusion imaging.

• Readout-segmented echo-planar diffusion-weighted imaging enabled evaluation of ADC parameters.

• Pretreatment ADC parameters do not predict chemoradiotherapy response in patients with oesophageal carcinoma.

Electronic supplementary material

The online version of this article (10.1007/s00330-018-5439-6) contains supplementary material, which is available to authorized users.

Endometrial Stromal Sarcoma of the Uterus: Magnetic Resonance Imaging Findings Including Apparent Diffusion Coefficient Value and Its Correlation With Ki-67 Expression

OBJECTIVE

This study aimed to investigate the conventional magnetic resonance imaging (MRI) and diffusion-weighted imaging (DWI) features of endometrial stromal sarcoma (ESS) including a preliminary investigation of the correlation between the apparent diffusion coefficient (ADC) value and Ki-67 expression.

METHODS

The clinical and MRI data of 15 patients with ESS confirmed by surgery and pathology were analyzed retrospectively. The conventional MR morphological features, signal intensity on DWI, ADC value (n = 14), and clinicopathological marker Ki-67 (n = 13) were evaluated.

RESULTS

Of 15 patients with ESS, 13 tumors were low-grade ESS (LGESS), and the remaining 2 were high-grade ESS (HGESS); 9 tumors were located in the myometrium, 5 were located in the endometrium and/or cervical canal, and 1 was located in extrauterine. Thirteen (87%) of 15 tumors showed a homo- or heterogeneous isointensity on T1-weighted imaging and a heterogeneous hyperintensity on T2-weighted imaging. The hypointense bands were observed in 11 tumors (73%) on T2-weighted imaging. The degenerations (cystic/necrosis/hemorrhage) were observed in 7 LGESS tumors and 2 HGESS tumors. The DWI hyperintensity was observed in 13 tumors (93%) and isointensity in remaining 1. The mean ADC value of the solid components in 14 ESSs was (1.05 ± 0.20) × 10mm/s. The contrast-enhanced MRI showed an obvious enhancement in 14 tumors (93%) (heterogeneous in 7 LGESSs and 2 HGESSs; homogeneous in 5 LGESSs). The ADC value was inversely correlated with the Ki-67 expression (r = -0.613, P = 0.026).

CONCLUSIONS

Patients with ESS showed some characteristics on conventional MRI and DWI, and there was an inverse correlation between the ADC value and Ki-67 expression.

Differentiation of renal cell carcinoma subtypes with different iodine quantification methods using single-phase contrast-enhanced dual-energy CT: areal vs. volumetric analyses

PURPOSE

To investigate the possibility of iodine quantification during a single nephrographic phase in characterizing renal cell carcinoma (RCC) subtypes and if there is a difference between areal and volumetric iodine quantification methods.

MATERIALS AND METHODS

This retrospective study included 110 patients with 113 histopathologically confirmed RCCs scanned by dual-energy CT at the nephrographic phase before surgeries. For each lesion, an areal measurement of the iodine concentration with maximum enhancement (I _{max enhan}) and the iodine concentration with maximum area among slices (I _{max area}), as well as a volumetric iodine concentration of the whole-tumor (I _volume), were evaluated by two independent radiologists. The diagnostic performances in a single nephrographic phase for characterizing RCC subtypes were evaluated, and three iodine quantification methods were compared with each other.

RESULTS

There were significant differences (clear cell vs. papillary and clear cell vs. chromophobe RCC) and no significant differences (papillary vs. chromophobe RCC) at the nephrographic phase in all three methods. The area under the receiver operating characteristic (ROC) curve (AUC) derived from the I _{max enhan} for discriminating clear cell from papillary RCC was significantly higher than that derived from the I _{max area} (P = 0.0357) and the I _volume (P = 0.0206), and no significant differences existed among the three methods in distinguishing clear cell RCC from chromophobe RCC. The reliability of all three parameters was very high with an interclass correlation coefficient (ICC) exceeding 0.8.

CONCLUSIONS

Iodine quantification in a single nephrographic phase can be used to differentiate RCC subtypes preoperatively, and the areal maximum enhancement iodine quantification would probably be the most appropriate approach.

Diffusion-weighted imaging features of breast tumours and the surrounding stroma reflect intrinsic heterogeneous characteristics of molecular subtypes in breast cancer

Breast cancer heterogeneity is the main obstacle preventing the identification of patients with breast cancer with poor prognoses and treatment responses; however, such heterogeneity has not been well characterized. The purpose of this retrospective study was to reveal heterogeneous patterns in the apparent diffusion coefficient (ADC) signals in tumours and the surrounding stroma to predict molecular subtypes of breast cancer. A dataset of 126 patients with breast cancer, who underwent preoperative diffusion-weighted imaging (DWI) on a 3.0-T image system, was collected. Breast images were segmented into regions comprising the tumour and surrounding stromal shells in which features that reflect heterogeneous ADC signal distribution were extracted. For each region, imaging features were computed, including the mean, minimum, variance, interquartile range (IQR), range, skewness, kurtosis and entropy of ADC values. Univariate and stepwise multivariate logistic regression modelling was performed to identify the magnetic resonance imaging features that optimally discriminate luminal A, luminal B, human epidermal growth factor 2 (HER2)-enriched and basal-like molecular subtypes. The performance of the predictive models was evaluated using the area under the receiver operating characteristic curve (AUC). Univariate logistic regression analysis showed that the skewness in the tumour boundary achieved an AUC of 0.718 for discrimination between luminal A and non-luminal A tumours, whereas the IQR of the ADC value in the tumour boundary had an AUC of 0.703 for classification of the HER2-enriched subtype. Imaging features in the tumour boundary and the proximal peritumoral stroma corresponded to a higher overall prediction performance than those in other regions. A multivariate logistic regression model combining features in all the regions achieved an overall AUC of 0.800 for the classification of the four tumour subtypes. These findings suggest that features in the tumour boundary and stroma around the tumour may be further assessed as potential predictors of molecular subtypes of breast cancer.

Associations between apparent diffusion coefficient (ADC) and KI 67 in different tumors: a meta-analysis. Part 2: ADCmin

The purpose of this part of the meta-analysis was to summarize data regarding associations between minimum apparent diffusion coefficient (ADC_min) and KI 67 in different tumors. MEDLINE library was screened for associations between ADC_min and KI 67 in different tumors up to April 2017. Overall, 23 studies with 944 patients were identified. Associations between ADC and KI 67 were analyzed by Spearman's correlation coefficient. The pooled correlation coefficient between ADC_min and KI 67 for all included tumors was ρ = -0.47. In detail, the correlation coefficients for separate tumors were as follows: cerebral lymphoma: ρ = -0.61 (95% CI = [-0.82; -0.41]); cervical cancer: ρ = -0.56 (95% CI = [-0.68;-0.43]); pituitary adenoma: ρ = -0.55 (95% CI = [-1.31; 0.22]); glioma: ρ = -0.40 (95% CI = [-0.55; -0.24]); breast cancer: ρ = -0.37 (95% CI = [-0.74; -0.01]); meningioma, ρ = -0.15 (95% CI = [-0.38; 0.07]).

Utility of apparent diffusion coefficient as an imaging biomarker for assessing the proliferative potential of invasive ductal breast cancer

AIM

To determine the clinical utility of apparent diffusion coefficient (ADC) metrics for the non-invasive assessment of tumour proliferation indicated by Ki-67 labelling index (LI) in invasive ductal breast cancer.

MATERIALS AND METHODS

Eighty patients with 80 histopathologically proven invasive ductal breast cancers underwent diffusion-weighted imaging with b-values of 0 and 800 s/mm² at a 3-T system. ADC metrics including ADC_mean, ADC_median, ADC_min, ADC_max, and ΔADC (ADC_max-ADC_min) were recorded from the entire tumour volume on ADC maps, and correlated with the Ki-67 LI. Ki-67 staining of ≥14% was considered to indicate high proliferation and <14% was considered to indicate low proliferation.

RESULTS

ADC_min, ADC_max, and ΔADC showed significant correlations with the Ki-67 LI (for all tumours, r=-0.311, 0.436, and 0.551, respectively; for luminal/human epidermal growth factor receptor 2 (HER2)-negative group, r=-0.437, 0.512, and 0.639, respectively; all p<0.01), whereas ADC_mean and ADC_median showed no significant correlation (both p>0.05). Receiver operating characteristic (ROC) curve analysis for the differentiation of high- from low-proliferation groups showed that ΔADC yielded the highest area under the ROC curve for the whole tumour population (0.825; 95% confidence interval [CI]: 0.724, 0.901), as well as for the luminal/HER2-negative group (0.844; 95% CI: 0.692, 0.940).

CONCLUSION

ΔADC may serve as a promising imaging biomarker for the prediction of Ki-67 proliferation status in invasive ductal breast cancer.

Differentiation Between Luminal-A and Luminal-B Breast Cancer Using Intravoxel Incoherent Motion and Dynamic Contrast-Enhanced Magnetic Resonance Imaging

RATIONALE AND OBJECTIVES

The study aimed to investigate whether intravoxel incoherent motion (IVIM) and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) can differentiate luminal-B from luminal-A breast cancer MATERIALS AND METHODS: Biexponential analyses of IVIM and DCE MRI were performed using a 3.0-T MRI scanner, involving 134 patients with 137 pathologically confirmed luminal-type invasive breast cancers. Luminal-type breast cancer was categorized as luminal-B breast cancer (LBBC, Ki-67 ≧ 14%) or luminal-A breast cancer (LABC, Ki-67 < 14%). Quantitative parameters from IVIM (pure diffusion coefficient [D], perfusion-related diffusion coefficient [D*], and fraction [f]) and DCE MRI (initial percentage of enhancement and signal enhancement ratio [SER]) were calculated. The apparent diffusion coefficient (ADC) was also calculated using monoexponential fitting. We correlated these data with the Ki-67 status.

RESULTS

The D and ADC values of LBBC were significantly lower than those of LABC (P = 0.028, P = 0.037). The SER of LBBC was significantly higher than that of LABC (P = 0.004). A univariate analysis showed that a significantly lower D (<0.847 x 10^-3 mm²/s), lower ADC (<0.960 × 10^-3 mm²/s), and higher SER (>1.071) values were associated with LBBC (all P values <0.01), compared to LABC. In a multivariate analysis, a higher SER (>1.071; odds ratio: 3.0099, 95% confidence interval: 1.4246-6.3593; P = 0.003) value and a lower D (<0.847 × 10^-3 mm²/s; odds ratio: 2.6878, 95% confidence interval: 1.0445-6.9162; P = 0.040) value were significantly associated with LBBC, compared to LABC.

CONCLUSION

The SER derived from DCE MRI and the D derived from IVIM are associated independently with the Ki-67 status in patients with luminal-type breast cancer.

Diffusion-weighted MRI characteristics associated with prognostic pathological factors and recurrence risk in invasive ER+/HER2- breast cancers

BACKGROUND

Hormone receptor-positive breast cancer is the most common subtype; better tools to identify which patients in this group would derive clear benefit from chemotherapy are needed.

PURPOSE

To evaluate the prognostic potential of diffusion-weighted MRI (DWI) by investigating associations with pathologic biomarkers and a genomic assay for 10-year recurrence risk.

STUDY TYPE

Retrospective.

SUBJECTS

In all, 107 consecutive patients (from 2/2010 to 1/2013) with estrogen receptor (ER)-positive/HER2neu-negative invasive breast cancer who had the 21-gene recurrence score (RS) test (Oncotype DX, Genomic Health).

FIELD STRENGTH/SEQUENCE

Each subject underwent presurgical 3T breast MRI, which included DWI (b = 0, 800 s/mm² ).

ASSESSMENT

Apparent diffusion coefficient (ADC) and contrast-to-noise ratio (CNR) were measured for each lesion by a fifth year radiology resident. Pathological markers (Nottingham histologic grade, Ki-67, RS) were determined from pathology reports. Medical records were reviewed to assess recurrence-free survival.

STATISTICAL TESTS

RS was stratified into low (<18), moderate (18-30), and high (>30)-risk groups. Associations of DWI characteristics with pathologic biomarkers were evaluated by binary or ordinal logistic regression, as appropriate, with adjustment for multiple comparisons. Post-hoc comparisons between specific groups were also performed.

RESULTS

ADCmean (odds ratio [OR] = 0.61 per 1 standard deviation [SD] increase, adj. P = 0.044) and CNR (OR = 1.76 per 1-SD increase, adj. P = 0.026) were significantly associated with increasing tumor grade. DWI CNR was also significantly associated with a high (Ki-67 ≥14%) proliferation rate (OR = 2.55 per 1-SD increase, adj. P = 0.026). While there were no statistically significant linear associations in ADC (adj. P = 0.80-0.85) and CNR (adj. P = 0.56) across all three RS groups by ordinal logistic regression, post-hoc analyses suggested that high RS lesions exhibited lower ADCmean (P = 0.037) and ADCmax (P = 0.004) values and higher CNR (P = 0.008) compared to lesions with a low or moderate RS.

DATA CONCLUSION

DWI characteristics correlated with tumor grade, proliferation index, and RS, and may potentially help to identify those with highest recurrence risk and most potential benefit from chemotherapy.

LEVEL OF EVIDENCE

3 Technical Efficacy Stage 3 J. Magn. Reson. Imaging 2017.

[Correlations between apparent diffusion coefficient in diffusion?weighted magnetic resonance imaging and molecular subtypes of invasive breast cancer masses]

OBJECTIVE

To study the correlation of apparent diffusion coefficient (ADC) measured by diffusion-weighted magnetic resonance imaging (MRI) with the molecular subtypes and biological prognostic factors of invasive breast cancer masses.

METHODS

Breast MRI data (including dynamic enhanced and diffusion-weighted imaging) were collected from 64 patients with pathologically confirmed invasive breast cancer masses (a total of 69 lesions). The mean ADC values of the lesions were calculated and their correlations were analyzed with the 5 molecular subtypes of invasive breast cancer and the biological prognostic factors including estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor 2 (HER2), and Ki-67 index.

RESULTS

The ADC values did not differ significantly among the 5 molecular subtypes of invasive breast cancer masses (P>0.05) or among lesions with different ER, PR, or HER2 status (P>0.05). The mean ADC values were significantly higher in Ki-67-positive lesions than in the negative lesions (P=0.023 and negatively correlated with the expressions of Ki-67 (r=-0.249).

CONCLUSION

ADC value can not be used to identify the molecular subtypes of invasive breast cancer masses or to evaluate the biological prognosis of the lesions, but its correlation with Ki-67 expression may help in prognostic evaluation and guiding clinical therapy of the tumors.

Ki67 Proliferation Index as a Histopathological Predictive and Prognostic Parameter of Oral Mucosal Melanoma in Patients without Distant Metastases

Background: To investigate the relationship between clinical and histopathological characteristics and overall survival of patients with oral mucosal melanoma (OMM) without distal metastasis in order to provide predictive prognostic information of OMM.

Methods: Ki67 expression was assessed by immunohistochemistry in 123 patients with OMM without distant metastases. The associations between Ki67 expression and clinical features and overall survival (OS) of patients were statistically analyzed. The Ki67 levels of the primary and recurrent lesions from 14 OMM patients were compared.

Results: Univariate analysis showed that tumor type and cervical lymph node (CLN) status, as well as Ki67 expression, were all correlated with survival. Cox proportional hazards regression analysis identified Ki67 expression and CLN status as independent prognostic factors in OMM patients. Further, we found that Ki67 expression was associated with clinical tumor type of OMM. Moreover, with a cut-off point of 20%, patients with lower Ki67 scores showed a survival advantage over those with higher Ki67 scores.

Conclusions: Ki67 expression may be a useful pathological predictor of survival of OMM patients without distant metastases.

DWI in the Assessment of Breast Lesions

Diffusion-weighted imaging (DWI) holds promise to address some of the shortcomings of routine clinical breast magnetic resonance imaging (MRI) and to expand the capabilities of imaging in breast cancer management. DWI reflects tissue microstructure, and provides unique information to aid in characterization of breast lesions. Potential benefits under investigation include improving diagnostic accuracy and guiding treatment decisions. As a result, DWI is increasingly being incorporated into breast MRI protocols and multicenter trials are underway to validate single-institution findings and to establish clinical guidelines. Advancements in DWI acquisition and modeling approaches are helping to improve image quality and extract additional biologic information from breast DWI scans, which may extend diagnostic and prognostic value.

Can diffusion-weighted imaging add information in the evaluation of breast lesions considered suspicious on magnetic resonance imaging?

OBJECTIVE

To assess the role of diffusion-weighted imaging (DWI) in the evaluation of breast lesions classified as suspicious on magnetic resonance imaging (MRI), correlating the findings with the results of the histological analysis.

MATERIALS AND METHODS

This was a retrospective, descriptive study based on a review of the medical records of 215 patients who were submitted to MRI with DWI before undergoing biopsy at a cancer center. Apparent diffusion coefficient (ADC) values were calculated for each lesion, and the result of the histological analysis was considered the gold standard.

RESULTS

The mean age was 49 years. We identified 252 lesions, 161 (63.9%) of which were found to be malignant in the histological analysis. The mean ADC value was higher for the benign lesions than for the malignant lesions (1.50 × 10-3 mm2/s vs. 0.97 × 10-3 mm2/s), the difference being statistically significant (p < 0.001). The ADC cut-off point with the greatest sensitivity and specificity on the receiver operating characteristic curve was 1.03 × 10-3 mm2/s. When the DWI and conventional MRI findings were combined, the accuracy reached 95.9%, with a sensitivity of 95.7% and a specificity of 96.4%.

CONCLUSION

The use of DWI could facilitate the characterization of breast lesions, especially those classified as BI-RADS 4, increasing the specificity and diagnostic accuracy of MRI.

Associations between apparent diffusion coefficient (ADC) and KI 67 in different tumors: a meta-analysis. Part 1: ADCmean

Diffusion weighted imaging (DWI) is a magnetic resonance imaging (MRI) technique based on measure of water diffusion in tissues. This diffusion can be quantified by apparent diffusion coefficient (ADC). Some reports indicated that ADC can reflect tumor proliferation potential. The purpose of this meta-analysis was to provide evident data regarding associations between ADC and KI 67 in different tumors. Studies investigating the relationship between ADC and KI 67 in different tumors were identified. MEDLINE library was screened for associations between ADC and KI 67 in different tumors up to April 2017. Overall, 42 studies with 2026 patients were identified. The following data were extracted from the literature: authors, year of publication, number of patients, tumor type, and correlation coefficients. Associations between ADC and KI 67 were analyzed by Spearman's correlation coefficient. The reported Pearson correlation coefficients in some studies were converted into Spearman correlation coefficients. The pooled correlation coefficient between ADC_mean and KI 67 for all included tumors was ρ = -0.44. Furthermore, correlation coefficient for every tumor entity was calculated. The calculated correlation coefficients were as follows: ovarian cancer: ρ = -0.62, urothelial carcinomas: ρ = -0.56, cerebral lymphoma: ρ = -0.55, neuroendocrine tumors: ρ = -0.52, glioma: ρ = -0.51, lung cancer: ρ = -0.50, prostatic cancer: ρ = -0.43, rectal cancer: ρ = -0.42, pituitary adenoma:ρ = -0.44, meningioma, ρ = -0.43, hepatocellular carcinoma: ρ = -0.37, breast cancer: ρ = -0.22.

Cone-beam Breast Computed Tomography: CT Density Does Not Reflect Proliferation Potential and Receptor Expression of Breast Carcinoma

PURPOSE: Recently, cone-beam breast computed tomography (CBCT) is established for the breast investigation. The purpose of the present study was to investigate possible associations between CBCT findings and histopathological features in breast cancer. METHODS: Overall, 59 female patients, mean age of 64.6 years with histological proven breast cancer were included into the study. In all cases, non-contrast CBCT examination was done. The diagnosis of the identified lesions was confirmed histologically by biopsy. Immunohistochemical staining against estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and Ki-67 was performed for every lesion. Collected data were evaluated by means of descriptive statistics. Spearman's correlation coefficient was used to analyze the association between CT density and Ki-67 values. P values <0.05 were taken to indicate statistical significance in all instances. RESULTS: The size of the lesion varied from 2.7 to 90.0, mean size, 15.88 ± 13.0 mm. The mean value of CT density of the lesions was 63.95 ± 38.18 HU. The density tended to be higher in tubular carcinoma. Correlation analysis identified no significant correlations between CT density and Ki-67 level (r = −0.031, P = .784). There were no statistically significant differences of CT density between tumors with different receptor status. CONCLUSIONS: No significant associations between CT density and receptor status in breast cancer. Tubular carcinoma tended to have higher CT density in comparison to other subtypes of breast carcinomas.

Heterogeneity of Diffusion-Weighted Imaging in Tumours and the Surrounding Stroma for Prediction of Ki-67 Proliferation Status in Breast Cancer

Breast tissue heterogeneity is related to risk factors that lead to more aggressive tumour growth and worse prognosis, yet such heterogeneity has not been well characterized. The aim of this study is to reveal the heterogeneous signal patterns of the apparent diffusion coefficient (ADC) of a tumour and its surrounding stromal tissue and to predict the Ki-67 proliferation status in oestrogen receptor (ER)-positive breast cancer patients. A dataset of 82 patients who underwent diffusion-weighted imaging (DWI) examination was collected. The ADC map was segmented into regions comprising the tumour and the surrounding stromal shells. To reflect correlations between each region in terms of its mean ADC value, a functional graph was constructed consisting of nodes as regions and edges as interactions between two nodes. Analysis of the graph revealed a higher average degree in samples over-expressing Ki-67 than in samples with low Ki-67 expression. In the low-Ki-67 group, most of the identified edges represented correlations between adjacent regions, whereas additional edges representing correlations between non-adjacent regions were found in the high-Ki-67 group. The ADC signal in various breast stromal regions surrounding the tumour showed a discriminative pattern and would be valuable for estimating the Ki-67 proliferation status by DWI.

PET/MR in invasive ductal breast cancer: correlation between imaging markers and histological phenotype

BACKGROUND

Differences in genetics and receptor expression (phenotypes) of invasive ductal breast cancer (IDC) impact on prognosis and treatment response. Immunohistochemistry (IHC), the most used technique for IDC phenotyping, has some limitations including its invasiveness. We explored the possibility of contrast-enhanced positron emission tomography magnetic resonance (CE-FDG PET/MR) to discriminate IDC phenotypes.

METHODS

21 IDC patients with IHC assessment of oestrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor-2 (HER2), and antigen Ki-67 (Ki67) underwent CE-FDG PET/MR. Magnetic resonance-perfusion biomarkers, apparent diffusion coefficient (ADC), and standard uptake value (SUV) were compared with IHC markers and phenotypes, using a Student's t-test and one-way ANOVA.

RESULTS

ER/PR- tumours demonstrated higher Kepmean and SUVmax than ER or PR+ tumours. HER2- tumours displayed higher ADCmean, Kepmean, and SUVmax than HER2+tumours. Only ADCmean discriminated Ki67⩽14% tumours (lower ADCmean) from Ki67>14% tumours. PET/MR biomarkers correlated with IHC phenotype in 13 out of 21 patients (62%; P=0.001).

CONCLUSIONS

Positron emission tomography magnetic resonance might non-invasively help discriminate IDC phenotypes, helping to optimise individual therapy options.

Primary and metastatic ovarian cancer: Characterization by 3.0T diffusion-weighted MRI

Objectives

We aimed to investigate whether apparent diffusion coefficients (ADCs) measured by 3.0T diffusion-weighted magnetic resonance imaging (DWI) associate with histological aggressiveness of ovarian cancer (OC) or predict the clinical outcome. This prospective study enrolled 40 patients with primary OC, treated 2011-2014.

Methods

DWI was performed prior to surgery. Two observers used whole lesion single plane region of interest (WLsp-ROI) and five small ROIs (S-ROI) to analyze ADCs. Samples from tumours and metastases were collected during surgery. Immunohistochemistry and quantitative reverse transcription polymerase chain reaction (qRT-PCR) were used to measure the expression of vascular endothelial growth factor (VEGF) and its receptors.

Results

The interobserver reliability of ADC measurements was excellent for primary tumours ICC 0.912 (WLsp-ROI). Low ADCs significantly associated with poorly differentiated OC (WLsp-ROI P = 0.035). In primary tumours, lower ADCs significantly associated with high Ki-67 (P = 0.001) and low VEGF (P = 0.001) expression. In metastases, lower ADCs (WLsp-ROI) significantly correlated with low VEGF receptors mRNA levels. ADCs had predictive value; 3-year overall survival was poorer in patients with lower ADCs (WLsp-ROI P = 0.023, S-ROI P = 0.038).

Conclusion

Reduced ADCs are associated with histological severity and worse outcome in OC. ADCs measured with WLsp-ROI may serve as a prognostic biomarker of OC.

Key Points

• Reduced ADCs correlate with prognostic markers: poor differentiation and high Ki-67 expression

• ADCs also significantly correlated with VEGF protein expression in primary tumours

• Lower ADC values are associated with poorer survival in ovarian cancer

• Whole lesion single plane-ROI ADCs may be used as a prognostic biomarker in OC

The Changing World of Breast Cancer: A Radiologist's Perspective

Compared with other fields of medicine, there is hardly an area that has seen such fast development as the world of breast cancer. Indeed, the way we treat breast cancer has changed fundamentally over the past decades. Breast imaging has always been an integral part of this change, and it undergoes constant adjustment to new ways of thinking. This relates not only to the technical tools we use for diagnosing breast cancer but also to the way diagnostic information is used to guide treatment. There is a constant change of concepts for and attitudes toward breast cancer, and a constant flux of new ideas, new treatment approaches, and new insights into the molecular and biological behavior of this disease. Clinical breast radiologists and even more so, clinician scientists, interested in breast imaging need to keep abreast with this rapidly changing world. Diagnostic or treatment approaches that are considered useful today may be abandoned tomorrow. Approaches that seem irrelevant or far too extravagant today may prove clinically useful and adequate next year. Radiologists must constantly question what they do, and align their clinical aims and research objectives with the changing needs of contemporary breast oncology. Moreover, knowledge about the past helps better understand present debates and controversies. Accordingly, in this article, we provide an overview on the evolution of breast imaging and breast cancer treatment, describe current areas of research, and offer an outlook regarding the years to come.

Diagnostic Performance of Diffusion Tensor Imaging with Readout-segmented Echo-planar Imaging for Invasive Breast Cancer: Correlation of ADC and FA with Pathological Prognostic Markers

Purpose:

To assess the diagnostic performance of readout-segmented echo-planar diffusion tensor imaging (DTI based on rs-EPI) for breast cancer and to determine the correlation between the apparent diffusion coefficient (ADC) and fractional anisotropy (FA) values obtained from DTI based on rs-EPI with prognostic markers of invasive breast cancer.

Materials and Methods:

This retrospective study examined 80 pathologically proven breast lesions (22 benign and 58 malignant lesions) of 80 patients who underwent both diffusion-weighted imaging based on single-shot echo-planar imaging (DWI based on ss-EPI) and DTI based on rs-EPI with b-values of 0 and 1000. We identified and compared the diagnostic performances of the DWI based on ss-EPI and the DTI based on rs-EPI using ADCs by conducting a receiver-operating-characteristics (ROC) analysis. We determined the correlations between the ADCs and the prognostic markers and those of the FA values and the same markers.

Results:

The median ADCs of the benign and malignant lesions based on the ss-EPI were 1.57 and 1.2 × 10⁻³ mm²/sec, and those based on the rs-EPI were 1.53 and 1.09 × 10⁻³ mm²/sec, respectively. The area under the curve on the ROC analysis based on rs-EPI (0.924) was greater than that based on ss-EPI (0.897). There were no significant correlations between the ADCs and the prognostic markers, but there were significant correlations between the FA values and the estrogen receptor status, a proliferative marker, the nuclear grade and the intrinsic subtype.

Conclusion:

For breast cancer, DTI based on rs-EPI had superior diagnostic performance compared to DWI based on ss-EPI. Compared with the ADCs, the FA values were more closely correlated with prognostic markers of invasive breast cancer.

Diffusion-weighted breast MRI: Clinical applications and emerging techniques

Diffusion-weighted MRI (DWI) holds potential to improve the detection and biological characterization of breast cancer. DWI is increasingly being incorporated into breast MRI protocols to address some of the shortcomings of routine clinical breast MRI. Potential benefits include improved differentiation of benign and malignant breast lesions, assessment and prediction of therapeutic efficacy, and noncontrast detection of breast cancer. The breast presents a unique imaging environment with significant physiologic and inter-subject variations, as well as specific challenges to achieving reliable high quality diffusion-weighted MR images. Technical innovations are helping to overcome many of the image quality issues that have limited widespread use of DWI for breast imaging. Advanced modeling approaches to further characterize tissue perfusion, complexity, and glandular organization may expand knowledge and yield improved diagnostic tools.

LEVEL OF EVIDENCE

5 J. Magn. Reson. Imaging 2016 J. Magn. Reson. Imaging 2017;45:337-355.

Tumor apparent diffusion coefficient as an imaging biomarker to predict tumor aggressiveness in patients with estrogen-receptor-positive breast cancer

The purpose of this retrospective study was to evaluate whether tumor apparent diffusion coefficient (ADC) was correlated with pathologic biomarkers such as tumor cellularity, Ki67, tumor-infiltrating lymphocytes (TILs), and peritumoral lymphocytic infiltrate (PLI) in patients with estrogen receptor (ER)-positive breast cancer. The study was approved by the institutional review board and informed consent was waived. From July 2014 to December 2014, we reviewed 140 ER-positive tumors in 138 consecutive patients (range, 28-77 years; mean, 52 years) who underwent preoperative breast MRI and definitive surgery. All patients underwent diffusion-weighted imaging with a 3T scanner. Two radiologists drew the region of interest of the entire tumor and obtained the mean and pixel-based histogram of ADC. On pathology, two pathologists reviewed tumor cellularity, Ki67, TILs, and PLI. Multiple linear regression analysis was used to determine pathologic variables independently associated with ADC. Tumors with high tumor cellularity and high Ki67 had significantly lower ADCs than those with low tumor cellularity and low Ki67 (P < 0.05 for all). Tumors without PLI had significantly higher standard deviation than those with PLI (0.23 ± 0.08 versus 0.18 ± 0.05; P < 0.001). Median ADC was negatively correlated with tumor cellularity (r = -0.441), and Ki67 (r = -0.382). The standard deviation of ADC was also negatively correlated with the degree of PLI (r = -0.319). On multivariate linear regression analysis, tumor cellularity and Ki67 were independently associated with tumor ADC. Tumor ADC would be an MRI biomarker for the prediction of tumor aggressiveness indicators such as Ki67, tumor cellularity, and PLI in ER-positive breast cancer. Copyright © 2016 John Wiley & Sons, Ltd.

Intravoxel incoherent motion diffusion-weighted MR imaging of breast cancer: association with histopathological features and subtypes

OBJECTIVE

To evaluate the associations between intravoxel incoherent motion (IVIM)-derived parameters and histopathological features and subtypes of breast cancer.

METHODS

Pre-operative MRI from 275 patients with unilateral breast cancer was analyzed. The apparent diffusion coefficient (ADC) and IVIM parameters [tissue diffusion coefficient (Dt), perfusion fraction (fp) and pseudodiffusion coefficient] were obtained from cancer and normal tissue using diffusion-weighted imaging with b-values of 0, 30, 70, 100, 150, 200, 300, 400, 500 and 800 s mm(-2). We then compared the IVIM parameters of tumours with different histopathological features and subtypes.

RESULTS

The ADC and Dt were lower and fp was higher in cancers than in normal tissues (p < 0.001). The Dt was lower in high Ki-67 cancer than in low Ki-67 cancer (p = 0.019), whereas ADC showed no significant difference (p = 0.309). Luminal B [human epidermal growth factor receptor 2 (HER2)-negative] cancer showed lower ADC (p = 0.003) and Dt (p = 0.001) than other types.

CONCLUSION

We found low tissue diffusivity in high Ki-67 cancer and luminal B (HER2-negative) cancer using IVIM imaging.

ADVANCES IN KNOWLEDGE

Low tissue diffusivity is more clearly shown in high Ki-67 tumours and luminal B (HER2-negative) tumours with the IVIM model.

The Changing World of Breast Cancer: A Radiologist's Perspective

Compared with other fields of medicine, there is hardly an area that has seen such fast development as the world of breast cancer. Indeed, the way we treat breast cancer has changed fundamentally over the past decades. Breast imaging has always been an integral part of this change, and it undergoes constant adjustment to new ways of thinking. This relates not only to the technical tools we use for diagnosing breast cancer but also to the way diagnostic information is used to guide treatment. There is a constant change of concepts for and attitudes toward breast cancer, and a constant flux of new ideas, new treatment approaches, and new insights into the molecular and biological behavior of this disease. Clinical breast radiologists and even more so, clinician scientists, interested in breast imaging need to keep abreast with this rapidly changing world. Diagnostic or treatment approaches that are considered useful today may be abandoned tomorrow. Approaches that seem irrelevant or far too extravagant today may prove clinically useful and adequate next year. Radiologists must constantly question what they do, and align their clinical aims and research objectives with the changing needs of contemporary breast oncology. Moreover, knowledge about the past helps better understand present debates and controversies. Accordingly, in this article, we provide an overview on the evolution of breast imaging and breast cancer treatment, describe current areas of research, and offer an outlook regarding the years to come.

Supine Versus Standing Radiographs for Detecting Ischiofemoral Impingement: A Propensity Score-Matched Analysis

OBJECTIVE

The purpose of this study was to assess parameters of ischiofemoral impingement on supine and standing anteroposterior hip radiographs and to suggest optimal cutoff points for detection of ischiofemoral impingement.

MATERIALS AND METHODS

A retrospective study included patients with a clinical history of hip pain. All hip joints with evidence of quadratus femoris muscle edema on MR images were included in the ischiofemoral impingement patient group. An age- and sex-matched control group was derived from the same cohort by propensity score matching. On radiographs, two readers independently measured the following parameters: ischiofemoral space, quadratus femoris space, hamstring tendon area, ischiofemoral distance on supine radiograph, ischiofemoral distance on standing radiograph, and femoral neck-shaft angle. Group differences in parameters were assessed by Mann-Whitney U test. The intraclass correlation coefficient and the ROC AUC were obtained. Correlations between radiographic and MRI measures were assessed with Pearson correlation and Bland-Altman plot analyses. The Youden J index was used to select optimum cutoff points for each parameter.

RESULTS

There were 30 patients (44 hip joints; mean age, 54.8 ± 11 years) in the ischiofemoral impingement group and 88 patients (88 hip joints; mean age, 51.8 ± 13.4 years) in the control group. There were significant group differences in ischiofemoral space, quadratus femoris space, ischiofemoral distance on supine radiograph, ischiofemoral distance on standing radiograph, and neck-shaft angle (p < 0.05). Ischiofemoral distance on supine and standing radiographs exhibited good discriminative ability (AUC > 0.80). The optimal cutoff points for ischiofemoral distances on supine and standing radiographs were 19.9 and 19.1 mm for reader 1 and 21.1 and 17.0 mm for reader 2. Ischiofemoral space, quadratus femoris space, ischiofemoral distance on supine radiograph, and ischiofemoral distance on standing radiograph exhibited nearly perfect interobserver agreement (r > 0.8).

CONCLUSION

Ischiofemoral distances on supine and standing hip radiographs had good diagnostic performance and can be used as a screening tool, with optimal cutoff points.

Additional Value of Diffusion-Weighted Imaging to Evaluate Prognostic Factors of Breast Cancer: Correlation with the Apparent Diffusion Coefficient

BACKGROUND

Breast cancer is a heterogeneous disease with diverse prognoses. The main prognostic determinants are lymph node status, tumor size, histological grade, and biological factors, such as hormone receptors, human epidermal growth factor receptor 2 (HER2), Ki-67 protein levels, and p53 expression. Diffusion-weighted imaging (DWI) can be used to measure the apparent diffusion coefficient (ADC) that provides information related to tumor cellularity and the integrity of the cell membranes.

OBJECTIVES

The goal of this study was to evaluate whether ADC measurements could provide information on the prognostic factors of breast cancer.

PATIENTS AND METHODS

A total of 71 women with invasive breast cancer, treated consecutively, who underwent preoperative breast MRIs with DWI at 3.0 Tesla and subsequent surgery, were prospectively included in this study. Each DWI was acquired with b values of 0 and 1000 s/mm(2). The mean ADC values of the lesions were measured, including the entire lesion on the three largest sections. We performed histopathological analyses for the tumor size, lymph node status, histological grade, hormone receptors, human epidermal growth factor receptor 2 (HER2), Ki-67, p53, and molecular subtypes. The associations with the ADC values and prognostic factors of breast cancer were evaluated using the independent-samples t test and the one-way analysis of variance (ANOVA).

RESULTS

A low ADC value was associated with lymph node metastasis (P < 0.01) and with high Ki-67 protein levels (P = 0.03). There were no significant differences in the ADC values among the histological grade (P = 0.48), molecular subtype (P = 0.51), tumor size (P = 0.46), and p53 protein level (P = 0.62).

CONCLUSION

The pre-operative use of the 3.0 Tesla DWI could provide information about the lymph node status and tumor proliferation for breast cancer patients, and could help determine the optimal treatment plan.

Contrast-Enhanced Ultrasonography Features of Breast Malignancies with Different Sizes: Correlation with Prognostic Factors

This study was to investigate the correlation between contrast-enhanced ultrasonography (CEUS) characteristics with prognostic factors in breast cancers with different sizes. A retrospective analysis of CEUS characteristics of 104 pathologically proven malignant lesions from 104 women was conducted. Lesions were divided into two groups according to their size measured by US (Group 1: maximum diameter ≤20 mm; Group 2: maximum diameter >20 mm). Features including enhancement degree, order and pattern, enlargement of the enhancement area, and penetrating vessels on CEUS were evaluated. Pathologic prognostic factors, including estrogen and progesterone receptor status, and the expression of c-erb-B2, p53, Ki-67, and VEGF were assessed. Comparison of enhancement pattern parameters between Group 1 and Group 2 showed statistically significant differences (P < 0.0001). A significant correlation was found between enlargement of the enhancement area and ER positivity in Group 1 (P = 0.032). In Group 2 the absence of penetrating vessels was significantly associated with VEGF negativity (P = 0.022) and ER negativity (P = 0.022). Centripetal enhancement reflected VEGF negativity (P = 0.033) in lesions with diameter >20 mm. Thus, breast cancers with different sizes show different CEUS features; small breast cancers show homogeneous enhancement pattern while cancers with diameter >20 mm show homogeneous enhancement pattern. Some CEUS characteristics of differently sized breast cancers could be correlated with prognostic factors, which may be useful in prognosis assessment.

Combination of diffusion tensor imaging and conventional MRI correlates with isocitrate dehydrogenase 1/2 mutations but not 1p/19q genotyping in oligodendroglial tumours

OBJECTIVES

To explore the correlations of conventional MRI (cMRI) and diffusion tensor imaging (DTI) values with the 1p/19 codeletion and IDH mutations in oligodendroglial tumours (OTs).

METHODS

Eighty-four patients with OTs who underwent cMRI and DTI were retrospectively reviewed. The maximal fractional anisotropy and minimal apparent diffusion coefficient (ADC) were measured and compared using the Mann-Whitney U test. Receiver operating characteristic curves, logistic regression analysis and four-table statistics analysis were performed to predict genotypings.

RESULTS

OTs with 1p/19q codeletion or IDH mutations were prone to locate in frontal (P = 0.106 and 0.005, respectively) and insular lobes and were associated with absent or blurry contrast enhancement (P = 0.040 and 0.013, respectively). DTI values showed significant differences between OTs with and without IDH mutations (P < 0.05) but not in OTs with and without 1p/19q loss. The Ki-67 index significantly correlated with IDH mutations (P = 0.002) but not with 1p/19q codeletion. A combination of DTI and cMRI for the identification of IDH mutations resulted in sensitivity, specificity, positive and negative predictive values of 92.2 %, 75.8 %, 93.8 % and 71.1 %, respectively.

CONCLUSIONS

Combination of DTI and cMRI correlates with isocitrate dehydrogenase 1/2 mutations but not 1p/19q genotyping in OTs.

KEY POINTS

• OTs with 1p/19q codeletion were associated with absent or blurry contrast enhancement • OTs with IDH mutations were also associated with absent or blurry contrast enhancement • OTs with IDH mutations were prone to locate in frontal and insular lobes • DTI values can provide a non-invasive method for assessing the IDH status of OTs • A combination of DTI and cMRI correlates with isocitrate dehydrogenase 1/2 mutations.

Early-stage invasive ductal carcinoma: Association of tumor apparent diffusion coefficient values with axillary lymph node metastasis

PURPOSE

To evaluate any association between tumor apparent diffusion coefficient (ADC) values and axillary lymph node metastasis (ALNM) in early-stage invasive ductal carcinoma.

MATERIALS AND METHODS

Records of 270 invasive ductal carcinoma patients with stages T1 and T2 disease who underwent breast magnetic resonance imaging, including diffusion-weighted imaging with b values of 0 and 1000s/mm(2) were reviewed retrospectively. The tumor ADC values were analyzed for their utility in predicting ALNM using multivariate regression analysis and receiver operating characteristic (ROC) curve analysis.

RESULTS

Of the 270 patients, 58 (21.5%) experienced ALNM. The mean tumor ADC values were significantly lower in patients with ALNM than in those without metastasis (0.880 × 10(-3) vs. 0.999 × 10(-3)mm(2)/s, P<0.001). A ROC curve demonstrated a tumor ADC value of 0.991 × 10(-3)mm(2)/s to be the optimal cut-off for predicting ALNM. In a multivariate analysis, lower tumor ADC (≤ 0.991 × 10(-3)mm(2)/s; adjusted odds ratio (OR)=5.861, P<0.001), large tumor size (>2 cm; adjusted OR=3.156, P=0.002) and the presence of lymphovascular invasion (adjusted OR=4.125, P<0.001) were independent variables associated with ALNM. When tumor ADC value was added to known risk factors (i.e., tumor size and lymphovascular invasion), a significant improvement in the accuracy of risk prediction for axillary node metastasis was shown (c-statistic=0.758 vs. 0.816, P=0.026).

CONCLUSION

In early-stage invasive ductal carcinoma, lower tumor ADC values are associated with the presence of ALNM.