Pre-treatment diffusion-weighted MR imaging for predicting tumor recurrence in uterine cervical cancer treated with concurrent chemoradiation: value of histogram analysis of apparent diffusion coefficients

Prediction of Recurrent Cervical Cancer in 2-Year Follow-Up After Treatment Based on Quantitative and Qualitative Magnetic Resonance Imaging Parameters: A Preliminary Study

PURPOSE

This study investigated predictors of cervical cancer (CC) recurrence from native T1 mapping, conventional imaging, and clinicopathologic metrics.

PATIENTS AND METHODS

In total, 144 patients with histopathologically confirmed CC (90 with and 54 without surgical treatment) were enrolled in this prospective study. Native T1 relaxation time, conventional imaging, and clinicopathologic characteristics were acquired. The association of quantitative and qualitative parameters with post-treatment tumor recurrence was assessed using univariate and multivariate Cox proportional hazard regression analyses. Independent risk factors were combined into a model and individual prognostic index equation for predicting recurrence risk. The receiver operating characteristic (ROC) curve determined the optimal cutoff point.

RESULTS

In total, 12 of 90 (13.3%) surgically treated patients experienced tumor recurrence. Native T1 values (X1) [hazard ratio (HR) 1.008; 95% confidence interval (CI) 1.001-1.016], maximum tumor diameter (X2) (HR 1.065; 95% CI 1.020-1.113), and parametrial invasion (X3) (HR 3.930; 95% CI 1.013-15.251) were independent tumor recurrence risk factors. The individual prognostic index (PI) of the established recurrence risk model was PI = 0.008X1 + 0.063X2 + 1.369X3. The area under the ROC curve (AUC) of the Cox regression model was 0.923. A total of 20 of 54 (37.0%) non-surgical patients experienced tumor recurrence. Native T1 values (X1) (HR 1.012; 95% CI 1.007-1.016) and lymph node metastasis (X2) (HR 4.064; 95% CI 1.378-11.990) were independent tumor recurrence risk factors. The corresponding PI was calculated as follows: PI = 0.011X1 + 1.402X2; the Cox regression model AUC was 0.921.

CONCLUSIONS

Native T1 values combined with conventional imaging and clinicopathologic variables could facilitate the pretreatment prediction of CC recurrence.

Prognostic value of apparent diffusion coefficient in neuroendocrine carcinomas of the uterine cervix

Objectives

This research was designed to examine the associations between the apparent diffusion coefficient (ADC) values and clinicopathological parameters, and to explore the prognostic value of ADC values in predicting the International Federation of Gynecology and Obstetrics (FIGO) stage and outcome of patients suffering from neuroendocrine carcinomas of the uterine cervix (NECCs).

Methods

This retrospective study included 83 patients with NECCs, who had undergone pre-treatment magnetic resonance imaging (MRI) between November 2002 and June 2019. The median follow-up period was 50.7 months. Regions of interest (ROIs) were drawn manually by two radiologists. ADC values in the lesions were calculated using the Functool software. These values were compared between different clinicopathological parameters groups. The Kaplan–Meier approach was adopted to forecast survival rates. Prognostic factors were decided by the Cox regression method.

Results

In the cohort of 83 patients, nine, 42, 23, and nine patients were in stage I, II, III, and IV, respectively. ADCmean, ADCmax, and ADCmin were greatly lower in stage IIB–IVB than in stage I–IIA tumours, as well as in tumours measuring ≥ 4 cm than in those < 4 cm. ADCmean, FIGO stage, and age at dianosis were independent prognostic variables for the 5-year overall survival (OS). ADCmin, FIGO stage, age at diagnosis and para-aortic lymph node metastasis were independent prognostic variables for the 5-year progression-free survival (PFS) in multivariate analysis. For surgically treated patients (n = 45), ADCmax was an independent prognostic parameter for both 5-year OS and 5-year PFS.

Conclusions

ADCmean, ADCmin, and ADCmax are independent prognostic factors for NECCs. ADC analysis could be useful in predicting the survival outcomes in patients with NECCs.

Risk factors for the recurrence of cervical cancer using MR-based T1 mapping: A pilot study

Objectives

This study aimed to identify risk factors for recurrence in patients with cervical cancer (CC) through quantitative T1 mapping.

Methods

A cohort of 107 patients histopathologically diagnosed with CC at our institution between May 2018 and April 2021 was categorized into surgical and non-surgical groups. Patients in each group were further divided into recurrence and non-recurrence subgroups depending on whether they showed recurrence or metastasis within 3 years of treatment. The longitudinal relaxation time (native T1) and apparent diffusion coefficient (ADC) value of the tumor were calculated. The differences between native T1 and ADC values of the recurrence and non-recurrence subgroups were analyzed, and receiver operating characteristic (ROC) curves were drawn for parameters with statistical differences. Logistic regression was performed for analysis of significant factors affecting CC recurrence. Recurrence-free survival rates were estimated by Kaplan–Meier analysis and compared using the log-rank test.

Results

Thirteen and 10 patients in the surgical and non-surgical groups, respectively, showed recurrence after treatment. There were significant differences in native T1 values between the recurrence and non-recurrence subgroups in the surgical and non-surgical groups (P&lt;0.05); however, there was no difference in ADC values (P&gt;0.05). The areas under the ROC curve of native T1 values for discriminating recurrence of CC after surgical and non-surgical treatment were 0.742 and 0.780, respectively. Logistic regression analysis indicated that native T1 values were risk factors for tumor recurrence in the surgical and non-surgical groups (P=0.004 and 0.040, respectively). Compared with cut-offs, recurrence-free survival curves of patients with higher native T1 values of the two groups were significantly different from those with lower ones (P=0.000 and 0.016, respectively).

Conclusion

Quantitative T1 mapping could help identify CC patients with a high risk of recurrence, supplementing information on tumor prognosis other than clinicopathological features and providing the basis for individualized treatment and follow-up schemes.

Diagnostic value of the apparent diffusion coefficient in differentiating malignant from benign endometrial lesions

Introduction

Magnetic resonance imaging (MRI) with its innovative techniques, such as diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC), increases the diagnostic accuracy in distinguishing between malignant and benign lesions of the endometrium. The aim of the study was MRI differentiation between malignant and benign endometrial lesions and correlation with histopathological findings with a special emphasis on quantitative analysis. An additional aim was to correlate the ADC values and histological tumor grades.

Methods

The prospective study included 119 female patients with or without vaginal bleeding and pathological values of endometrial thickness, who underwent MRI examinations. According to MRI reports the patients were divided into 45 suspicious malignant and 74 suspicious benign endometrial lesions. The radiological diagnosis was compared to the histopathological evaluation, which confirmed 37 malignant lesions while the rest were benign.

Results

The mean ADC value for malignant lesions was 0.761 ± 0.13×10^-3 mm²/s and for benign lesions was 1.318 ± 0.20×10^-3 mm²/s. The ADC values for malignant lesions were expectedly lower than those of benign lesions (p<0.001). The ADC cut-off value was 1.007×10^-3 mm²/s with a sensitivity of 100%, specificity of 92.7%, a positive predictive value of 60.3%, and a negative predictive value of 100%. In comparison with the histopathological findings, the sensitivity of MRI was 100%, specificity 90.2%, positive predictive value was 82.2%, and negative predictive value was 100%. Observing the histological grades 1, 2, and 3 of endometrial carcinoma, no statistically significant differences of mean ADC values were found. The mean ADC values for histological tumor grades 1,2 and 3 were 0.803 ± 0.13×10^-3 mm²/s, 0.754 ± 0.12×10^-3 mm²/s and 0.728 ± 0.13×10^-3 mm²/s, respectively.

Conclusion

DWI and ADC values represent clinically useful tools for the differentiation between malignant and benign endometrial lesions with high sensitivity and good specificity, but the results failed to demonstrate their usefulness in differentiating histological grades of endometrial cancer.

Prognosis prediction of uterine cervical cancer using changes in the histogram and texture features of apparent diffusion coefficient during definitive chemoradiotherapy

OBJECTIVES

We investigated prospectively whether, in cervical cancer (CC) treated with concurrent chemoradiotherapy (CCRT), the Apparent diffusion coefficient (ADC) histogram and texture parameters and their change rates during treatment could predict prognosis.

METHODS

Fifty-seven CC patients treated with CCRT at our institution were included. They underwent MRI scans up to four times during the treatment course (1st, before treatment [n = 41], 2nd, at the start of image-guided brachytherapy (IGBT) [n = 41], 3rd, in the middle of IGBT [n = 27], 4th, after treatment [n = 53]). The entire tumor was manually set as the volume of interest (VOI) manually in the axial images of the ADC map by two radiologists. A total of 107 image features (morphology features 14, histogram features 18, texture features 75) were extracted from the VOI. The recurrence prediction values of the features and their change rates were evaluated by Receiver operating characteristics (ROC) analysis. The presence or absence of local and distant recurrence within two years was set as an outcome. The intraclass correlation coefficient (ICC) was also calculated.

RESULTS

The change rates in kurtosis between the 1st and 3rd, and 1st and 2nd MRIs, and the change rate in grey level co-occurrence matrix_cluster shade between the 2nd and 3rd MRIs showed particularly high predictive powers (area under the ROC curve = 0.785, 0.759, and 0.750, respectively), which exceeded the predictive abilities of the parameters obtained from pre- or post-treatment MRI only. The change rate in kurtosis between the 1st and 2nd MRIs had good reliability (ICC = 0.765).

CONCLUSIONS

The change rate in ADC kurtosis between the 1st and 2nd MRIs was the most reliable parameter, enabling us to predict prognosis early in the treatment course.

Added-Value of Diffusion-Weighted Imaging (DWI) and Dynamic Contrast-Enhanced (DCE-MRI) Magnetic Resonance Imaging in the Preoperative Assessment of Cervical Cancer

Purpose

To evaluate the added-value of diffusion-weighted imaging (DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in the preoperative assessment of carcinoma cervix.

Methods

This prospective study was carried out on histopathologically proven 45 patients of carcinoma cervix presented to a tertiary care hospital with bleeding per vagina between August 2017 and July 2018. Relevant local per vaginal examination and MRI examination of the pelvis were performed.

Results

A total of 45 patients with carcinoma of the cervix, having 11 patients (24.4%) in Stage-I, 22 patients (48.9%) in Stage-II, 3 patients (6.7%) in Stage-III and 9 patients (20%) in stage-IV, were included in this study sample. The mean ADC value of the carcinoma of cervix was 0.802 ± 0.123 [SD] × 10^-3 mm²/s. The stage-I carcinoma cervix had a mean ADC value of 0.915 ± 0.109 [SD] × 10^-3 mm²/s, Stage-II 0.778 ± 0.099 [SD] × 10^-3 mm²/s, Stage-III 0.762 ± 0.123 [SD] × 10^-3 mm²/s and Stage-IV 0.737 ± 0.116 [SD] × 10^-3 mm²/s. ROC curve analysis showed the percentage of signal intensity changes within cervical tumor on arterial phase of DCE-MRI had a threshold value of 42.25 in differentiating Stage-I carcinoma of cervix from other stages with a sensitivity of 81.8% and specificity of 44.1%.

Conclusion

The DWI and DCE-MRI added valuable inputs over conventional MR sequences in the early diagnosis and preoperative staging of carcinoma cervix. DCE-MRI had a high accuracy for assessing the cervical stromal and parametrial invasions, which helps in selecting the optimal therapeutic protocol and prognostication in gynecological malignancies.

The Value of Whole-Tumor Texture Analysis of ADC in Predicting the Early Recurrence of Locally Advanced Cervical Squamous Cell Cancer Treated With Concurrent Chemoradiotherapy

Objectives

To investigate the value of whole-tumor texture analysis of apparent diffusion coefficient (ADC) map in predicting the early recurrence of patients with locally advanced cervical squamous cell cancer (LACSC) treated with concurrent chemoradiotherapy (CCRT) and establish a combined prediction model including clinical variables and first-order texture features.

Methods

In total, 219 patients (training: n = 153; testing: n = 66) with stage IIB-IVA LACSC treated by CCRT between January 2014 and December 2019 were retrospectively enrolled in this study. Clinical variables and 22 first-order texture features extracted from ADC map were collected. The Mann-Whitney U test or independent sample t test, chi-square test or Fisher’s exact were used to analyze statistically significant parameters, logistic regression analysis was used for multivariate analysis, and receiver operating characteristic analysis was used to compare the diagnostic performance.

Results

In the clinical variables, T stage and lymph node metastasis (LNM) were independent risk factors, and the areas under the curve (AUCs) of the clinical model were 0.697 and 0.667 in the training and testing cohorts, the sensitivity and specificity were 48.8% and 85.5% in the training cohort, and 84.1% and 51.1% in the testing cohort, respectively. In the first-order texture features, mean absolute deviation (MAD) was the independent protective factor, with an AUC of 0.756 in the training cohort and 0.783 in the testing cohort. The sensitivity and specificity were 95.3% and 52.7% in the training cohort and 94.7% and 53.2% in the testing cohort, respectively. The combined model (MAD, T stage, and LNM) was established, it exhibited the highest AUC of 0.804 in the training cohort and 0.821 in the testing cohort, which was significantly higher than the AUC of the clinical prediction model. The sensitivity and specificity were 67.4% and 85.5% in the training cohort and 94.7% and 70.2% in the testing cohort, respectively.

Conclusions

The first-order texture features of the ADC map could be used along with clinical predictive biomarkers to predict early recurrence in patients with LACSC treated by CCRT.

An MRI-based radiomics signature and clinical characteristics for survival prediction in early-stage cervical cancer

OBJECTIVES

To investigate the prognostic role of magnetic resonance imaging (MRI)-based radiomics signature and clinical characteristics for overall survival (OS) and disease-free survival (DFS) in the early-stage cervical cancer.

METHODS

A total of 207 cervical cancer patients (training cohort: n = 144; validation cohort: n = 63) were enrolled. 792 radiomics features were extracted from T2W and diffusion-weighted imaging (DWI). 19 clinicopathological parameters were collected from the electronic medical record system. Least absolute shrinkage and selection operator (LASSO) regression analysis was used to select significant features to construct prognostic model for OS and DFS. Kaplan-Meier (KM) analysis and log-rank test were applied to identify the association between the radiomics score (Rad-score) and survival time. Nomogram discrimination and calibration were evaluated as well. Associations between radiomics features and clinical parameters were investigated by heatmaps.

RESULTS

A radiomics signature derived from joint T2W and DWI images showed better prognostic performance than that from either T2W or DWI image alone. Higher Rad-score was associated with worse OS (p < 0.05) and DFS (p < 0.05) in the training and validation set. The joint models outperformed both radiomics model and clinicopathological model alone for 3-year OS and DFS estimation. The calibration curves reached an agreement. Heatmap analysis demonstrated significant associations between radiomics features and clinical characteristics.

CONCLUSIONS

The MRI-based radiomics nomogram showed a good performance on survival prediction for the OS and DFS in the early-stage cervical cancer. The prediction of the prognostic models could be improved by combining with clinical characteristics, suggesting its potential for clinical application.

ADVANCES IN KNOWLEDGE

This is the first study to build the radiomics-derived models based on T2W and DWI images for the prediction of survival outcomes on the early-stage cervical cancer patients, and further construct a combined risk scoring system incorporating the clinical features.

Magnetic resonance imaging-based texture analysis for the prediction of postoperative clinical outcome in uterine cervical cancer

OBJECTIVES

Magnetic resonance imaging (MRI)-based texture analysis (MRTA) is a novel image analysis tool that offers objective information about the spatial arrangement of MRI signal intensity. We aimed to investigate the value of MRTA in predicting the postoperative clinical outcome of patients with uterine cervical cancer.

METHODS

This retrospective study included 115 patients with surgically proven cervical cancer who underwent preoperative pelvic 3T-MRI, and MRTA was performed on T2-weighted images (T2), apparent diffusion coefficient (ADC) maps, and contrast-enhanced T1-weighted images (CE-T1). Filtration histogram-based texture analysis was used to generate six first-order statistical parameters [mean intensity, standard deviation (SD), mean of positive pixels (MPP), entropy, skewness, and kurtosis] at five spatial scaling factors (SSFs, 2-6 mm) as well as from unfiltered images. Cox proportional hazard models and time-dependent receiver operating characteristic analyses were used to evaluate the associations between parameters and recurrence-free survival (RFS).

RESULTS

During a median follow-up of 36 months, tumor recurrence was found in 26 patients (22.6%). Multivariate analysis demonstrated that CE-T1 MPP and T2 kurtosis at SSF3-5, CE-T1 MPP at SSF6, and CE-T1 SD at unfiltered images were independent predictors of RFS (p < 0.05). Regarding the 2-year RFS for CE-T1 MPP and T2 kurtosis at SSF5, and CE-T1 MPP at SSF6, patients with > optimal cutoff values demonstrated significantly worse survival than those with ≤ optimal cutoff values (p < 0.05).

CONCLUSION

Preoperative MRTA may be useful for predicting postoperative outcome in patients with cervical cancer.

Impact of hypoxia on cervical cancer outcomes

The annual global incidence of cervical cancer is approximately 604 000 cases/342 000 deaths, making it the fourth most common cancer in women. Cervical cancer is a major healthcare problem in low and middle income countries where 85% of new cases and deaths occur. Secondary prevention measures have reduced incidence and mortality in developed countries over the past 30 years, but cervical cancer remains a major cause of cancer deaths in women. For women who present with Fédération Internationale de Gynécologie et d'Obstétrique (FIGO 2018) stages IB3 or upwards, chemoradiation is the established treatment. Despite high rates of local control, overall survival is less than 50%, largely due to distant relapse. Reducing the health burden of cervical cancer requires greater individualization of treatment, identifying those at risk of relapse and progression for modified or intensified treatment. Hypoxia is a well known feature of solid tumors and an established therapeutic target. Low tumorous oxygenation increases the risk of local invasion, metastasis and treatment failure. While meta-analyses show benefit, many individual trials targeting hypoxia failed in part due to not selecting patients most likely to benefit. This review summarizes the available hypoxia-targeted strategies and identifies further research and new treatment paradigms needed to improve patient outcomes. The applications and limitations of hypoxia biomarkers for treatment selection and response monitoring are discussed. Finally, areas of greatest unmet clinical need are identified to measure and target hypoxia and therefore improve cervical cancer outcomes.

Staging, recurrence and follow-up of uterine cervical cancer using MRI: Updated Guidelines of the European Society of Urogenital Radiology after revised FIGO staging 2018

OBJECTIVES

The recommendations cover indications for MRI examination including acquisition planes, patient preparation, imaging protocol including multi-parametric approaches such as diffusion-weighted imaging (DWI-MR),  dynamic contrast-enhanced imaging (DCE-MR) and standardised reporting. The document also underscores the value of whole-body 18-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography (FDG-PET/CT) and highlights potential future methods.

METHODS

In 2019, the ESUR female pelvic imaging working group reviewed the revised 2018 FIGO staging system, the up-to-date clinical management guidelines, and the recent imaging literature. The RAND-UCLA Appropriateness Method (RAM) was followed to develop the current ESUR consensus guidelines following methodological steps: literature research, questionnaire developments, panel selection, survey, data extraction and analysis.

RESULTS

The updated ESUR guidelines are recommendations based on ≥ 80% consensus among experts. If ≥ 80% agreement was not reached, the action was indicated as optional.

CONCLUSIONS

The present ESUR guidelines focus on the main role of MRI in the initial staging, response monitoring and evaluation of disease recurrence. Whole-body FDG-PET plays an important role in the detection of lymph nodes (LNs) and distant metastases.

KEY POINTS

• T2WI and DWI-MR are now recommended for initial staging, monitoring of response and evaluation of recurrence. • DCE-MR is optional; its primary role remains in the research setting. • T2WI, DWI-MRI and whole-body FDG-PET/CT enable comprehensive assessment of treatment response and recurrence.

The adjunctive value of diffusion weighted imaging in diagnosis and follow up of uterovaginal diffuse B-cell lymphoma: A case report and literature review

BACKGROUND

Lymphoma of the female gynecologic tract is extremely rare. Typically, lymphoma is managed non surgically unlike other non-lymphomatous malignant tumors raising the importance to differentiate between both entities.

CASE REPORT

We describe the magnetic resonance imaging (MRI) features of a case of uterovaginal diffuse large B-cell lymphoma in a 50-year-old postmenopausal woman emphasizing Diffusion-Weighted Imaging (DWI) as a diagnostic and follow up tool. We reviewed the literature regarding the diagnostic methods for female genital lymphoma. Forty-five cases including our patient were reviewed with age range from 22 to 85 years. Vaginal bleeding was the most common presentation. The diagnosis was established by Papanicolaou smear, cervical biopsy (25/45), endometrial biopsy (6/45), vaginal biopsy (2/45), pelvic mass biopsy (2/45), iliac LN biopsy (1/45) and surgical diagnosis (8/45). Diffuse large B-cell lymphomas (DLBCL) constitute the vast majority of the cases (82%). The uterine cervix was involved at diagnosis in the majority of these cases (68%) while uterine body (42%) and vagina (28%) were less involved. Pelvic lymphadenopathy was found in 15 cases while extra genital lymphomatous infiltration in 13 cases. Sonographic findings were nonspecific while CT provided excellent data about extra-genital involvement. Thirteen cases underwent pelvic MRI that displayed superior detection of disease extension and parametric involvement. Diffusion restriction was reported only in one case without quantitative analysis of ADC map.

CONCLUSION

MRI shows unique features that help to differentiate uterovaginal lymphoma from the much more common carcinomas and discriminate post-operative changes from tumor recurrence. It exhibits a marked restricted diffusion pattern with lower ADC values than carcinomas and post-operative changes.

Noninvasive Assessment of Liver Parenchyma Using Gray-Scale Ultrasound-Based Histogram Analysis in Patients With Chronic Hepatitis B Infection

The aims of this study were to examine the alterations of liver echo-intensity histogram parameters in chronic hepatitis B (CHB) patients and to assess the potential role of histogram parameters in the evaluation of hepatic fibrosis. A total of 52 patients with CHB who underwent liver biopsies were included in the study. The control group consisted of 30 healthy individuals. Histogram parameters were obtained from histogram analysis of gray-scale ultrasound images of both groups. The histogram parameters of the groups were compared. The association of histogram parameters with the grading and staging of histological activity index (HAI) in patients with CHB were evaluated. The patient group had statistically significant lower skewness, kurtosis, and higher variance, mean, 50th, and 90th percentile values compared with control group. When patients with CHB were divided into subgroups according to HAI stage, there was the increasing trend in skewness values and decreasing trend in kurtosis values across subgroups. The first percentile values showed negative correlation with HAI staging in patients with CHB. Ultrasound is a fast, inexpensive, and reproducible imaging method; histogram analysis of gray-scale ultrasound images may provide useful information for evaluation of hepatic fibrosis in CHB patients.

Advances in MR Imaging of the Female Pelvis

This article focuses on advanced MR imaging techniques of the female pelvis and clinical applications for benign and malignant disease. General and abbreviated protocols for female pelvic MR imaging are reviewed. Diffusion-weighted imaging, dynamic contrast-enhanced MR imaging, and susceptibility-weighted imaging are discussed in the context of adnexal mass characterization using the ADNEx-MR scoring system, evaluation of endometriosis, local staging of cervical and endometrial cancers, assessment of nodal and peritoneal metastasis, and potential detection of leiomyosarcoma. MR defecography is also discussed regarding evaluation of multicompartmental pelvic floor disorders.

Impact of different b-value combinations on radiomics features of apparent diffusion coefficient in cervical cancer

Background

The impact of variable b-value combinations on apparent diffusion coefficient (ADC)-based radiomics features has not been fully addressed in literature.

Purpose

To investigate the correlation between radiomics features extracted from ADC maps and various b-value combinations in cervical cancer.

Material and Methods

Diffusion-weighted images (b-values: 0, 600, 800, and 1000 s/mm2) of 20 patients with cervical cancer were included. Tumors were identified with the largest transversal cross-section and manually segmented by radiologist. For each b-value combination, 92 radiomics features were extracted and coefficient of variance (CV) was used to evaluate the robustness of radiomics features with different b-value combinations. Features with CV > 5% were normalized by the mean feature variation across the group.

Results

Out of a total of 92 radiomics features, 18 were classified as robust features with CV ≤5%. Among the rest (CV > 5%), 11, 23, and 40 features demonstrated 5%< CV ≤10%, 10%< CV ≤20%, and CV > 20%, respectively. A subset of features in each category (CV > 5%) showed strong correlation with the b-value combination variation, including 44% (7/16) features in gray level co-occurrence matrix, 62% (8/13) features in gray level dependence matrix, 64% (9/14) features in first order, 50% (8/16) features in gray level run length matrix, 57% (8/14) features in gray level size matrix, and 20% (1/5) features in neighborhood gray-tone difference matrix.

Conclusions

Variations in b-value combinations demonstrated impact on radiomics features extracted from ADC maps for cervical cancer. The radiomics features with CV <5% can be considered as robust features and are recommended to be used in multicenter radiomics studies.

Prediction of Early Response to Chemotherapy in Breast Cancer Liver Metastases by Diffusion-Weighted MR Imaging

Objective:

To determine whether change in apparent diffusion coefficient value could predict early response to chemotherapy in breast cancer liver metastases.

Materials and Methods:

We retrospectively studied 42 patients (86 lesions) with breast cancer liver metastases who had undergone conventional magnetic resonance imaging and diffusion-weighted imaging (b = 0.700 s/mm²) before and after chemotherapy. Maximum diameter and mean apparent diffusion coefficient value (×10⁻³ mm²/s) of liver metastases from breast cancer were evaluated. The grouping reference was based on magnetic resonance imaging according to Response Evaluation Criteria in Solid Tumors (RECIST). Analysis of variance and receiver–operating characteristic analyses were performed.

Results:

Eighty-six metastases were classified as 40 responders and 46 nonresponders. A statistically significant correlation was found between prechemotherapy and postchemotherapy apparent diffusion coefficient values in responders, which were 0.9 ± 0.16 × 10⁻³ mm²/s, 1.05 ± 0.12 × 10⁻³ mm²/s, 1.26 ± 0.12 × 10⁻³ mm²/s, and 1.33 ± 0.87 × 10⁻³ mm²/s, respectively. No statistically significant difference was found between prechemotherapy and postchemotherapy apparent diffusion coefficient values in nonresponders. Differences were statistically significant between responders and nonresponders at prechemotherapy, 2 weeks after chemotherapy, and 4 weeks after chemotherapy (P = 0.014, P = .001, and P = .000, respectively). Receiver operating characteristic curves showed that apparent diffusion coefficient values could predict treatment response early at 2 weeks after chemotherapy with 64.5% sensitivity and 91.8% specificity.

Conclusion:

The change in apparent diffusion coefficient value may be a sensitive indicator to predict early response to chemotherapy in breast cancer liver metastases.

The usefulness of diffusion-weighted MRI in the differentiation between focal uterine endometrial soft tissue lesions

Background

Several endometrial conditions may be challenging for radiologists due to the overlap of imaging features and variable endometrial pathologies. MRI with DWI is the most commonly used imaging technique for the diagnosis and characterization of endometrial focal lesions.

Results

The 50 studied lesions were classified according to their histopathological results into the benign group (28 lesions, 56%) and the malignant group (22 lesions, 44%). Conventional MRI could correctly diagnose 39 of the 50 lesions (22/28 benign and 17/22 malignant lesions), achieving a sensitivity of 77.27%, specificity of 78.56%, accuracy of 78%, predictive positive value (PPV) of 73.91%, and negative positive value (NPV) of 81.48%. By combining DWI and apparent diffusion coefficient (ADC) value mapping at a high b value (b = 1000) in MRI, we could correctly diagnose 47 of the 50 lesions (26/28 benign and 21/22 malignant lesions), with increased sensitivity (95.45%), specificity (92.86%), accuracy (94%), PPV (91.3%), and NPV (96%).

Conclusion

Combining DWI with ADC mapping at a high b value in pelvic MRI examination is valuable in differentiating endometrial focal lesions with increased diagnostic sensitivity, specificity, and accuracy.

Aim of the work

This study aimed to evaluate the role of DWI in the diagnosis and differential diagnosis of benign and malignant focal endometrial masses.

Whole lesion histogram analysis of apparent diffusion coefficients on MRI predicts disease-free survival in locally advanced squamous cell cervical cancer after radical chemo-radiotherapy

Background

The aim was to investigate the prognostic value of MR apparent diffusion coefficients (ADC) using histogram analysis (HA) in predicting disease-free survival (DFS) of cervical cancer after chemo-radiation therapy.

Methods

We retrospectively analyzed 103 women with pathologically proven squamous cell uterine cancer who received chemo-radiation therapy between 2009 and 2013. All patients were followed up for more than 2 years. Pre-treatment MR images were retrieved and imported for HA using an in-house developed software program based on 3D Slicer. Regions of interest of whole tumors were drawn manually on DWI with reference to T2WI. HA features (mean, max, min, 50, 10, 90%, kurtosis, and skewness) were extracted from apparent diffusion coefficient (ADC) maps and compared between the recurrence and non-recurrence groups after the 2-year follow-up. Univariate and multivariate Cox regression analysis was used to correlate ADC HA features and relevant clinical variables (age, grade, maximal diameter of tumor, FIGO stage, SCC-Ag) with DFS.

Results

One hundred three patients with stage IB-IV cervical cancers were followed up for 2.0–94.6 months (median 48.9 months). Twenty patients developed recurrence within 2 years. In the recurrence group, the min (P = 0.001) and 10% (P = 0.048) ADC values were significantly lower than those of the non-recurrence group. Univariate and multivariate Cox regression analysis revealed that ADC_min (P = 0.006, HR = 0.110) was significantly correlated with DFS.

Conclusion

Pre-treatment volumetric ADC_min in histogram analysis is an independent factor that is correlated with DFS in cervical cancer patients treated with chemo-radiation therapy.

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.

Whole Lesion Histogram Analysis Derived From Morphological MRI Sequences Might be Able to Predict EGFR- and Her2-Expression in Cervical Cancer

RATIONALE AND OBJECTIVES

Histogram analysis is an imaging analysis in which a whole tumor can be assessed, and every voxel of a radiological image is issued into a histogram. Thereby, statistically information about tumor can be obtained. The purpose of the study was to analyze possible relationships between histogram parameters derived from conventional MRI sequences and several histopathological features in cervical squamous cell carcinomas.

METHODS

A total of 18 female patients (age range 32-79 years) with squamous cell cervical carcinoma were retrospectively enrolled into the study. In all cases, pelvic MRI with a clinically protocol was performed. Histogram analysis was performed as a whole lesion measurement, calculating several percentils, minimum, mean, median, mode, maximum, kurtosis, skewness, and entropy. Histopathological parameters included expression of epidermal-growth factor (EGFR), vascular endothelial growth factor, hypoxia-inducible factor 1-alpha, Her2, and Histone 3. Spearman's correlation coefficient was used to analyze associations between investigated parameters.

RESULTS

Several pre- and postcontrast derived T1-weighted parameters correlated inversely with EGFR expression. For precontrast T1-weighted images, the strongest correlation was found for p90 (ρ = -0.77, p = 0.004). For postcontrast T1-weighted images, the strongest correlation was observed for minimum (ρ = -0.64, p = 0.021). Several parameters derived from T2-weighted images were statistically significant different between Her2-positive and Her2 negative tumors. Skewness had the best p-value ( p = 0.004).

CONCLUSIONS

Histogram analysis parameters of T1-weighted and T2-weighted images reflect HER2 status and EGFR expression in cervical cancer. Histogram parameters cannot predict cell count, proliferation index, or angiogenesis related histopathological features.

MRI of cervical cancer with a surgical perspective: staging, prognostic implications and pitfalls

LEARNING OBJECTIVES

Magnetic resonance imaging (MRI) of the pelvis is the most reliable imaging modality for staging, treatment planning, and follow-up of cervical cancer; and its findings may now be incorporated into the International Federation of Gynecology and Obstetrics Federation (FIGO) 2018 clinical staging of cervical cancer. It is imperative that radiologists are familiar with the imaging appearance of the different stages of cervical cancer as well as the post-treatment changes and imaging pitfalls given the respective clinical manifestations, treatment regimens, and prognosis of an accurate diagnosis. In addition to the different stages of cervical cancer, we address the imaging techniques for diagnosis, staging and treatment implications as well as the changes of the new FIGO staging system.

BACKGROUND

The use of MRI to diagnose and stage cervical cancer is steadily increasing and the new FIGO stagi ng system, previously based on clinical examination, now allows the staging or change of staging based on the imaging findings. MRI can evaluate the extent of disease because of its excellent contrast resolution for pelvic tissues and organs, high accuracy and detailed elaboration of the cervical/uterovaginal anatomy.

CONTENT

Relevant anatomy, including normal MRI appearance of the cervix, parametria and pelvic ligaments; different stages of cervical cancer on MRI with prognostic and therapeutic implications; MRI sequences, other imaging modalities used in the staging and follow-up, treatment of different stages and the appearance of the cervix and cervical cancer post-treatment. Since clinical implications and therapeutic strategies for cervical cancer treatment vary tremendously according to degree of tumor extension, familiarity with relevant MRI techniques and findings is essential for radiologists. It is important that radiologists interpreting pelvic MRI are aware with the different stages of cervical cancer to provide useful information regarding treatment and prognosis. Pitfalls regarding the interpretation of tumor extension can interfere with an accurate diagnosis and have significant therapeutic implications.

Volumetric assessment of apparent diffusion coefficient predicts outcome following chemoradiation for cervical cancer

OBJECTIVE

To determine the utility of volumetric diffusion weighted imaging (DWI) compared to other clinical factors for predicting recurrence and survival in cervical cancer patients treated with definitive chemoradiation.

METHODS AND MATERIALS

We retrospectively studied cervical cancer patients treated with definitive chemoradiation between 2009-2013 at a single institution with a baseline MRI with DWI and 18F-FDG positron emission tomography/computed tomography (FDG-PET) scan. To identify clinical and imaging metrics correlated with survival and recurrence endpoints, variable importance values were calculated from random forest models. To provide clinically relevant threshold values, recursive partitioning analysis dichotomized patients into potential risk groups based on selected metrics. Cox's proportional hazard models assessed the effect of clinical and imaging factors on survival endpoints.

RESULTS

Ninety-three patients were included in the analysis (median age 50 years). At a median follow-up of 35.6 months, 32 patients (34%) had disease recurrence. In the best multivariate model including clinical and imaging parameters, 90th percentile ADC < 1.917 was the only significantly associated factor with worse progression free survival (PFS). Overall survival, PFS, and distant metastasis free survival (DMFS) were significantly different between patient groups divided on 90th percentile ADC with threshold of 1.917 × 10-3 mm2/s and MRI volume with threshold of 18.9 cc (P = 0.037, P = 0.0002, P = 0.001). High MRI volume and low ADC were associated with worse clinical outcomes.

CONCLUSIONS

Volumetric 90th percentile ADC value of the primary tumor on pretreatment MRI was a significant predictor of PFS and DMFS in cervical cancer patients, independent of established clinical factors and SUV on FDG-PET.

Histogram analysis of apparent diffusion coefficient predicts response to radiofrequency ablation in hepatocellular carcinoma

Objective

The aim of this study was to predict tumor progression in patients with hepatocellular carcinoma (HCC) treated with radiofrequency ablation (RFA) using histogram analysis of apparent diffusion coefficients (ADC).

Methods

Breath-hold diffusion weighted imaging (DWI) was performed in 64 patients (33 progressive and 31 stable) with biopsy-proven HCC prior to RFA. All patients had pre-treatment magnetic resonance imaging (MRI) and follow-up computed tomography (CT) or MRI. The ADC values (ADC₁₀, ADC₃₀, ADC_median and ADC_max) were obtained from the histogram’s 10th, 30th, 50th and 100th percentiles. The ratios of ADC₁₀, ADC₃₀, ADC_median and ADC_max to the mean non-lesion area-ADC (RADC₁₀, RADC₃₀, RADC_median, and RADC_max) were calculated. The two patient groups were compared. Key predictive factors for survival were determined using the univariate and multivariate analysis of the Cox model. The Kaplan-Meier survival analysis was performed, and pairs of survival curves based on the key factors were compared using the log-rank test.

Results

The ADC₃₀, ADC_median, ADC_max, RADC₃₀, RADC_median, and RADC_max were significantly larger in the progressive group than in the stable group (P<0.05). The median progression-free survival (PFS) was 22.9 months for all patients. The mean PFS for the stable and progressive groups were 47.7±1.3 and 9.8±1.3 months, respectively. Univariate analysis indicated that RADC₁₀, RADC₃₀, and RADC_median were significantly correlated with the PFS [hazard ratio (HR)=31.02, 43.84, and 44.29, respectively, P<0.05 for all]. Multivariate analysis showed that RADC_median was the only independent predictor of tumor progression (P=0.04). And the cutoff value of RADC_median was 0.71.

Conclusions

Pre-RFA ADC histogram analysis might serve as a useful biomarker for predicting tumor progression and survival in patients with HCC treated with RFA.

Associations between whole tumor histogram analysis parameters derived from ADC maps and expression of EGFR, VEGF, Hif 1-alpha, Her-2 and Histone 3 in uterine cervical cancer

OBJECTIVE

Diffusion weighted imaging (DWI) can be quantified by apparent diffusion coefficient (ADC) and can predict tissue microstructure. The aim of the present study was to analyze possible associations between ADC histogram based parameters with different histopathological parameters in cervical squamous cell carcinoma.

MATERIALS AND METHODS

18 female patients (age range 32-79 years) with squamous cell cervical carcinoma were retrospectively enrolled. In all cases, pelvic MRI was performed with a DWI (b-values 0 and 1000 s/mm²). Histogram analysis was performed as a whole lesion measurement. Histopathological parameters included expression of EGFR, VEGF, Hif1-alpha, Her2 and Histone 3. Spearman's correlation coefficient was used to analyze associations between investigated parameters.

RESULTS

Analyze of the investigated ADC histogram parameters showed a good interreader variability, ranging from 0.705 for entropy to 0.959 for ADCmedian. EGFR expression correlated statistically significant with several histogram parameters. The highest correlation was observed for p75 (p = -0.562, P = 0.015). There were several correlations with histone 3, the highest with p25 (p = -0.610, P = 0.007). None of the ADC related parameters correlated statistically significant with expression of VEGF, Hif1-alpha and Her2.

CONCLUSION

Histogram analysis showed a good interreader agreement. ADC histogram parameters might be able to reflect expression of EGFR and histone 3 in cervical squamous cell carcinomas, but not expression of VEGF, Hif1-alpha and Her2.

Potentials and challenges of diffusion-weighted magnetic resonance imaging in radiotherapy

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Discussion of DW imaging protocols and imaging setup.

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Discussion of mono- and bi-exponential models for quantitative parameter extraction.

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Review of recent publications investigating potential benefits of using DWI in RT, including detailed synoptic table.

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Detailed discussion of geometric and quantitative accuracy of DW imaging and DW-derived parameters.

Purpose

To review the potential and challenges of integrating diffusion weighted magnetic resonance imaging (DWI) into radiotherapy (RT).

Content

Details related to image acquisition of DWI for RT purposes are discussed, along with the challenges with respect to geometric accuracy and the robustness of quantitative parameter extraction. An overview of diffusion- and perfusion-related parameters derived from mono- and bi-exponential models is provided, and their role as potential RT biomarkers is discussed. Recent studies demonstrating potential of DWI in different tumor sites such as the head and neck, rectum, cervix, prostate, and brain, are reviewed in detail.

Conclusion

DWI has shown promise for RT outcome prediction, response assessment, as well as for tumor delineation and characterization in several cancer types. Geometric and quantification robustness is challenging and has to be addressed adequately. Evaluation in larger clinical trials with well designed imaging protocol and advanced analysis models is needed to develop the optimal strategy for integrating DWI in RT.

The Value of Diffusion-Weighted Magnetic Resonance Imaging in Predicting the Efficacy of Radiation and Chemotherapy in Cervical Cancer

Background

To analyze the application value of apparent diffusion coefficient (ADC) and exponent apparent diffusion coefficient (EADC) in evaluating the efficacy of radiation and chemotherapy in cervical cancer using pre- and posttreatment diffusion-weighted magnetic resonance imaging (DW-MRI) scans.

Methods

52 patients with cervical cancer were administered radiation and chemotherapy. Both MRI and DW-MRI were obtained at different stages. The ADC and EADC values, as well as the maximum tumor diameter, were measured and analyzed.

Results

We found that the ADC value increased after treatment, and the EADC value decreased. Changes in the calculated ADC occurred earlier than the morphologic changes of the tumors. A negative correlation was detected between reduced rates in the maximum tumor diameter two months after treatment and pretreatment ADC value (r = –0.658, P < 0.05). An ROC curve and nonlinear regression analysis showed that the formula, y = (1525500.122x² – 4689.962x + 3.482) × 100%, can be used to calculate the percentage of complete remission after treatment according to the pretreatment ADC value.

Conclusion

Our data suggest that pretreatment ADC and EADC values are predictive of the efficacy of radiation and chemotherapy. Both ADC and EADC values during treatment were instrumental in early monitoring and dynamic observation.

Texture Analysis as Imaging Biomarker for recurrence in advanced cervical cancer treated with CCRT

This prospective study explored the application of texture features extracted from T2WI and apparent diffusion coefficient (ADC) maps in predicting recurrence of advanced cervical cancer patients treated with concurrent chemoradiotherapy (CCRT). We included 34 patients with advanced cervical cancer who underwent pelvic MR imaging before, during and after CCRT. Radiomic feature extraction was performed by using software at T2WI and ADC maps. The performance of texture parameters in predicting recurrence was evaluated. After a median follow-up of 31 months, eleven patients (32.4%) had recurrence. At four weeks after CCRT initiated, the most textural parameters (four T2 textural parameters and two ADC textural parameters) showed significant difference between the recurrence and nonrecurrence group (P values range, 0.002~0.046). Among them, RunLengthNonuniformity (RLN) from T2 and energy from ADC maps were the best selected predictors and together yield an AUC of 0.885. The support vector machine (SVM) classifier using ADC textural parameters performed best in predicting recurrence, while combining T2 textural parameters may add little value in prognosis. T2 and ADC textural parameters have potential as non-invasive imaging biomarkers in early predicting recurrence in advanced cervical cancer treated with CCRT.

Prognostic model based on magnetic resonance imaging, whole-tumour apparent diffusion coefficient values and HPV genotyping for stage IB-IV cervical cancer patients following chemoradiotherapy

OBJECTIVES

To develop and validate a prognostic model of integrating whole-tumour apparent diffusion coefficient (ADC) from pretreatment diffusion-weighted (DW) magnetic resonance (MR) imaging with human papillomavirus (HPV) genotyping in predicting the overall survival (OS) and disease-free survival (DFS) for women with stage IB-IV cervical cancer following concurrent chemoradiotherapy (CCRT).

METHODS

We retrospectively analysed three prospectively collected cohorts comprising 300 patients with stage IB-IV cervical cancer treated with CCRT in 2007-2014 and filtered 134 female patients who underwent MR imaging at 3.0 T for final analysis (age, 24-92 years; median, 54 years). Univariate and multivariate Cox regression analyses were used to evaluate the whole-tumour ADC histogram parameters, HPV genotyping and relevant clinical variables in predicting OS and DFS. The dataset was randomly split into training (n = 88) and testing (n = 46) datasets for construction and independent bootstrap validation of the models.

RESULTS

The median follow-up time for surviving patients was 69 months (range, 9-126 months). Non-squamous cell type, ADC₁₀ <0.77 × 10^-3 mm²/s, T3-4, M1 stage and high-risk HPV status were selected to generate a model, in which the OS and DFS for the low, intermediate and high-risk groups were significantly stratified (p < 0.0001). The prognostic model improved the prediction significantly compared with the International Federation of Gynaecology and Obstetrics (FIGO) stage for both the training and independent testing datasets (p < 0.0001).

CONCLUSIONS

The prognostic model based on integrated clinical and imaging data could be a useful clinical biomarker to predict OS and DFS in patients with stage IB-IV cervical cancer treated with CCRT.

KEY POINTS

• ADC ₁₀ is the best prognostic factor among ADC parameters in cervical cancer treated with CCRT • A novel prognostic model was built based on histology, ADC ₁₀ , T and M stage and HPV status • The prognostic model outperforms FIGO stage in the survival prediction.

Early Prediction of Response to Neoadjuvant Chemotherapy Using Dynamic Contrast-Enhanced MRI and Ultrasound in Breast Cancer

Objective

To determine the diagnostic performance of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and DCE ultrasound (DCE-US) for predicting response to neoadjuvant chemotherapy (NAC) in breast cancer patients.

Materials and Methods

This Institutional Review Board-approved prospective study was performed between 2014 and 2016. Thirty-nine women with breast cancer underwent DCE-US and DCE-MRI before the NAC, follow-up DCE-US after the first cycle of NAC, and follow-up DCE-MRI after the second cycle of NAC. DCE-MRI parameters (transfer constant [K_trans], reverse constant [k_ep], and leakage space [V_e]) were assessed with histograms. From DCE-US, peak-enhancement, the area under the curve, wash-in rate, wash-out rate, time to peak, and rise time (RT) were obtained. After surgery, all the imaging parameters and their changes were compared with histopathologic response using the Miller-Payne Grading (MPG) system. Data from minor and good responders were compared using Wilcoxon rank sum test, chi-square test, or Fisher's exact test. Receiver operating characteristic curve analysis was used for assessing diagnostic performance to predict good response.

Results

Twelve patients (30.8%) showed a good response (MPG 4 or 5) and 27 (69.2%) showed a minor response (MPG 1–3). The mean, 25th, 50th, and 75th percentiles of K_trans and K_ep of post-NAC DCE-MRI differed between the two groups. These parameters showed fair to good diagnostic performance for the prediction of response to NAC (AUC 0.76–0.81, p ≤ 0.007). Among DCE-US parameters, the percentage change in RT showed fair prediction (AUC 0.71, p = 0.023).

Conclusion

Quantitative analysis of DCE-MRI and DCE-US was helpful for early prediction of response to NAC.

Radiomics analysis of apparent diffusion coefficient in cervical cancer: A preliminary study on histological grade evaluation

BACKGROUND

The role of apparent diffusion coefficient (ADC)-based radiomics features in evaluating histopathological grade of cervical cancer is unresolved.

PURPOSE

To determine if there is a difference between radiomics features derived from center-slice 2D versus whole-tumor volumetric 3D for ADC measurements in patients with cervical cancer regarding tumor histopathological grade, and systematically assess the impact of the b value on radiomics analysis in ADC quantifications.

STUDY TYPE

Prospective.

SUBJECTS

In all, 160 patients with histopathologically confirmed squamous cell carcinoma of uterine cervix.

FIELD STRENGTH/SEQUENCE

Conventional and diffusion-weighted MR images (b values = 0, 800, 1000 s/mm² ) were acquired on a 3.0T MR scanner.

ASSESSMENT

Regions of interest (ROIs) were drawn manually along the margin of tumor on each slice, and then the center slice of the tumor was selected with naked eyes in the course of whole-tumor segmentation. A total of 624 radiomics features were derived from T₂ -weighted images and ADC maps. We randomly selected 50 cases and did the reproducibility analysis.

STATISTICAL TESTS

Parameters were compared using Wilcoxon signed rank test, Bland-Altman analysis, t-test, and least absolute shrinkage and selection operator (LASSO) regression with crossvalidation.

RESULTS

In all, 95 radiomics features were insensitive to ROI variation among T₂ images, ADC map of b800, and ADC map of b1000 (P > 0.0002). There was a significant statistical difference between the performances of 2D center-slice and 3D whole-tumor radiomics models in both ADC feature sets of b800 and b1000 (P < 0.0001, P < 0.0001). Compared with ADC features of b800 (0.3758 ± 0.0118), the model of b1000 ADC features appeared to be slightly lower in overall misclassification error (0.3642 ± 0.0162) (P = 0.0076).

DATA CONCLUSION

Several radiomics features extracted from T₂ images and ADC maps were highly reproducible. Whole-tumor volumetric 3D radiomics analysis had a better performance than using the 2D center-slice of tumor in stratifying the histological grade of cervical cancer. A b value of 1000 s/mm² is suggested as the optimal parameter in pelvic DWI scans.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;49:280-290.

Histogram analysis of apparent diffusion coefficient for monitoring early response in patients with advanced cervical cancers undergoing concurrent chemo-radiotherapy

Background Apparent diffusion coefficient (ADC) histogram analysis has been widely used in determining tumor prognosis. Purpose To investigate the dynamic changes of ADC histogram parameters during concurrent chemo-radiotherapy (CCRT) in patients with advanced cervical cancers. Material and Methods This prospective study enrolled 32 patients with advanced cervical cancers undergoing CCRT who received diffusion-weighted (DW) magnetic resonance imaging (MRI) before CCRT, at the end of the second and fourth week during CCRT and one month after CCRT completion. The ADC histogram for the entire tumor volume was generated, and a series of histogram parameters was obtained. Dynamic changes of those parameters in cervical cancers were investigated as early biomarkers for treatment response. Results All histogram parameters except AUC_low showed significant changes during CCRT (all P < 0.05). There were three variable trends involving different parameters. The mode, 5th, 10th, and 25th percentiles showed similar early increase rates (33.33%, 33.99%, 34.12%, and 30.49%, respectively) at the end of the second week of CCRT. The pre-CCRT 5th and 25th percentiles of the complete response (CR) group were significantly lower than those of the partial response (PR) group. Conclusion A series of ADC histogram parameters of cervical cancers changed significantly at the early stage of CCRT, indicating their potential in monitoring early tumor response to therapy.

Role of Functional Magnetic Resonance Imaging Derived Parameters as Imaging Biomarkers and Correlation with Clinicopathological Features in Carcinoma of Uterine Cervix

INTRODUCTION

Magnetic Resonance Imaging (MRI) is emerging as a powerful tool in the evaluation and management of cervical cancer. The role of Diffusion Weighted Imaging (DWI) with Apparent Diffusion Coefficient (ADC) as a non-invasive imaging biomarker is promising in characterization of the tumour and prediction of response.

AIM

The aim of this study was to evaluate the role of conventional MRI and diffusion weighted MRI in predicting clinicopathological prognostic factors.

MATERIALS AND METHODS

This was a retrospective study. The data of 100 cervical cancer patients who had MRI with DWI was retrieved from the database and analysed. Clinico pathological details were collected from the computerized hospital information system. SPSS version 15.0 was used for statistical analysis.

RESULTS

The mean tumour dimensions on MRI in x, y and z axes were 43.04 mm (±13.93, range: 17-85), 37.05mm (±11.83, range: 9-80) and 39.63 mm (±14.81, range: 14 -76). The mean T₂W MRI based tumour volume (TV) was 48.18 (±34.3, range: 7-206) and on DWI images was 36.68(±33.72, range: 2.5-200). The mean ADC value in patients with squamous cell carcinoma was 0.694 (±0.125, n=88), adenocarcinoma was 0.989 (±0.309, n=6), adenosquamous was 0.894 (±0.324, n=4). There was statistical significant difference in mean ADC between squamous vs. non squamous histology (p = 0.02). The mean ADC values of well differentiated, moderately differentiated, and poorly differentiated tumours were 0.841(±0.227, n= 26), 0.729 (±0.125, n=28), 0.648 (±0.099, n=46) respectively. There was significant statistical difference of mean ADC between well differentiated, moderately differentiated (p=0.020) and poorly differentiated tumours (p=0.0001). Difference between the mean ADC values between the node positive and node negative disease was statistically significant (p=0.0001). There was no correlation between the tumour volumes on T₂W and DWI images and ADC values. Sixteen patients had residual/recurrent disease at a median follow up of 12 months (range: 3-59 months). The mean ADC values in this group was 0.71 (n=16) and was not significantly different from the disease free group (mean ADC =0.72, n=74).

CONCLUSION

Higher ADC values are associated with favourable histology and differentiation. Adenocarcinomas have higher ADC values followed by adenosquamous followed by squamous cell carcinomas. Well differentiated tumours had higher ADC values than moderately followed by poorly differentiated tumours. DWI with ADC have a potential role as an imaging biomarker for prognostication and needs further studies for routine clinical applications.

The value of advanced MRI techniques in the assessment of cervical cancer: a review

OBJECTIVES

To assess the value of new magnetic resonance imaging (MRI) techniques in cervical cancer.

METHODS

We searched PubMed and MEDLINE and reviewed articles published from 1990 to 2016 to identify studies that used MRI techniques, such as diffusion weighted imaging (DWI), intravoxel incoherent motion (IVIM) and dynamic contrast enhancement (DCE) MRI, to assess parametric invasion, to detect lymph node metastases, tumour subtype and grading, and to detect and predict tumour recurrence.

RESULTS

Seventy-nine studies were included. The additional use of DWI improved the accuracy and sensitivity of the evaluation of parametrial extension. Most studies reported improved detection of nodal metastases. Functional MRI techniques have the potential to assess tumour subtypes and tumour grade differentiation, and they showed additional value in detecting and predicting treatment response. Limitations included a lack of technical standardisation, which limits reproducibility.

CONCLUSIONS

New advanced MRI techniques allow improved analysis of tumour biology and the tumour microenvironment. They can improve TNM staging and show promise for tumour classification and for assessing the risk of tumour recurrence. They may be helpful for developing optimised and personalised therapy for patients with cervical cancer.

TEACHING POINTS

• Conventional MRI plays a key role in the evaluation of cervical cancer. • DWI improves tumour delineation and detection of nodal metastases in cervical cancer. • Advanced MRI techniques show promise regarding histological grading and subtype differentiation. • Tumour ADC is a potential biomarker for response to treatment.

Whole-lesion ADC histogram and texture analysis in predicting recurrence of cervical cancer treated with CCRT

Purpose

To explore the value of whole-lesion apparent diffusion coefficient (ADC) histogram and texture analysis in predicting tumor recurrence of advanced cervical cancer treated with concurrent chemo-radiotherapy (CCRT).

Methods

36 women with pathologically confirmed advanced cervical squamous carcinomas were enrolled in this prospective study. 3.0 T pelvic MR examinations including diffusion weighted imaging (b = 0, 800 s/mm²) were performed before CCRT (pre-CCRT) and at the end of 2nd week of CCRT (mid-CCRT). ADC histogram and texture features were derived from the whole volume of cervical cancers.

Results

With a mean follow-up of 25 months (range, 11 ∼ 43), 10/36 (27.8%) patients ended with recurrence. Pre-CCRT 75th, 90th, correlation, autocorrelation and mid-CCRT ADC_mean, 10th, 25th, 50th, 75th, 90th, autocorrelation can effectively differentiate the recurrence from nonrecurrence group with area under the curve ranging from 0.742 to 0.850 (P values range, 0.001 ∼ 0.038).

Conclusions

Pre- and mid-treatment whole-lesion ADC histogram and texture analysis hold great potential in predicting tumor recurrence of advanced cervical cancer treated with CCRT.

Comparison of FDG PET metabolic tumour volume versus ADC histogram: prognostic value of tumour treatment response and survival in patients with locally advanced uterine cervical cancer

OBJECTIVE

To evaluate the prognostic utility of volume-based parameters of fluorine-18 fludeoxyglucose positron emission tomography (¹⁸F-FDG PET) and apparent diffusion coefficient (ADC) histogram analysis for tumour response to therapy and event-free survival (EFS) in patients with uterine cervical cancer receiving chemoradiotherapy.

METHODS

The study included 21 patients diagnosed with locally advanced uterine cervical cancer who underwent pre-treatment MRI and ¹⁸F-FDG PET and were treated with concurrent chemoradiotherapy. ¹⁸F-FDG parameters: maximum and mean standardized uptake value; metabolic tumour volume (MTV); total lesion glycolysis (TLG); ADC parameters: maximum, mean and minimum values; percentile ADC values (10-90%); skewness and kurtosis of ADC were measured and compared between the responder and non-responder groups using a Wilcoxon rank-sum test. The Cox regression analysis and Kaplan-Meier survival curves were performed for EFS analysis.

RESULTS

MTV and TLG of the primary tumour were significantly higher in the non-responder group than in the responder group (p = 0.04 and p = 0.01). Applying Cox regression multivariate analysis, MTV [hazard ratio (HR), 4.725; p = 0.036], TLG (HR, 4.725; p = 0.036) and 10-percentile ADC (HR, 5.207; p = 0.048) showed a statistically significant association with EFS. With the optimal cut-off value, the EFS rates above the cut-off value for MTV and TLG were significantly lower than that below the cut-off value (p = 0.002 and p = 0.002).

CONCLUSION

Pre-treatment volume-based quantitative parameters of ¹⁸F-FDG PET may have better potential than ADC histogram for predicting treatment response and EFS in patients with locally advanced cervical cancer. Advances in knowledge: In this study, pre-treatment volume-based quantitative parameters of ¹⁸F-FDG PET had better potential than ADC histogram for predicting treatment response and survival in patients with locally advanced cervical cancer.

Investigation of volumetric apparent diffusion coefficient histogram analysis for assessing complete response and clinical outcomes following pre-operative chemoradiation treatment for rectal carcinoma

PURPOSE

To investigate the relationship of pre-treatment volumetric apparent diffusion coefficient (ADC) histogram parameters with post-operative histopathologic treatment response and clinical outcomes following pre-operative chemoradiation treatment (CRT) in rectal cancer.

MATERIALS AND METHODS

In a Health Insurance Portability and Accountability Act compliant retrospective study, 78 rectal cancer patients treated with pre-operative CRT and rectal MRI were included. MR imaging analysis was performed using OncoTREAT (software tool). Multiple volumetric ADC histogram parameters (voxel distribution across ADC ranges, kurtosis, and skewness) were assessed. Correlation was made to post-operative pathological complete response, clinical, or radiological evidence of disease progression using the Mann-Whitney test.

RESULTS

Post CRT, 8 patients showed pathologic complete response and 13 patients showed distant disease progression. Pre-treatment mean ADC was 1.2 × 10^-3 mm²/s (range 0.3-1.99 × 10^-3 mm²/s). Mean kurtosis measured was 0.56 (range -1 to 6; SD 1.36). Mean skewness was 0.3 (range -1 to 2; SD 0.69). Skewness had significant correlation (p value = 0.006) with disease progression. The mean rectal tumor volume was 24cc (range 1cc-134cc). Pre-treatment MRI tumor volume showed significant correlation (p value = 0.013) with pathologic complete response. Mean ADC and percentage voxels distribution against ADC ranges had no significant correlation with treatment response or disease outcomes.

CONCLUSION

Volumetric ADC histogram analysis of pre-CRT rectal cancer MRI appears promising for prediction of post-CRT complete response and disease progression.

Predicting tumor recurrence in patients with cervical carcinoma treated with definitive chemoradiotherapy: value of quantitative histogram analysis on diffusion-weighted MR images

Background Further research is required for evaluating the use of ADC histogram analysis in more advanced stages of cervical cancer treated with definitive chemoradiotherapy (CRT). Purpose To investigate the utility of apparent diffusion coefficient (ADC) histogram derived from diffusion-weighted magnetic resonance images in cervical cancer patients treated with definitive CRT. Material and Methods The clinical and radiological data of 50 patients with histologically proven cervical squamous cell carcinoma treated with definitive CRT were retrospectively analyzed. The impact of clinicopathological factors and ADC histogram parameters on prognostic factors and treatment outcomes was assessed. Results The mean and median ADC values for the cohort were 1.043 ± 0.135 × 10^-3 mm²/s and 1.018 × 10^-3 mm²/s (range, 0.787-1.443 × 10^-3 mm²/s). The mean ADC was significantly lower for patients with advanced stage (≥IIB) or lymph node metastasis compared with patients with stage <IIB or no lymph node metastasis. The mean ADC, 75th percentile ADC (ADC75), 90th percentile ADC (ADC90), and 95th percentile ADC (ADC95) were significantly lower in patients with tumor recurrence compared with patients without recurrence. In multivariate analysis, tumor size, ADC75 and ADC95 were independent prognostic factors for both overall survival and disease-free survival. Conclusion ADC histogram parameters could be markers for disease recurrence and for predicting survival outcomes. ADC75, ADC90, and ADC95 of the primary tumor were significant predictors of disease recurrence in cervical cancer patients treated with definitive CRT.

Utility of histogram analysis of ADC maps for differentiating orbital tumors

PURPOSE

We aimed to evaluate the role of histogram analysis of apparent diffusion coefficient (ADC) maps for differentiating benign and malignant orbital tumors.

METHODS

Fifty-two patients with orbital tumors were enrolled from March 2013 to November 2014. Pretreatment diffusion-weighted imaging was performed on a 3T magnetic resonance scanner with b factors of 0 and 800 s/mm2, and the corresponding ADC maps were generated. Whole-tumor regions of interest were drawn on all slices of the ADC maps to obtain histogram parameters, including ADCmean, ADCmedian, standard deviation (SD), skewness, kurtosis, quartile, ADC10, ADC25, ADC75, and ADC90. Histogram parameter differences between benign and malignant orbital tumors were compared. The diagnostic value of each significant parameter in predicting malignant tumors was established.

RESULTS

Age, ADCmean, ADCmedian, quartile, kurtosis, ADC10, ADC25, ADC75, and ADC90 parameters were significantly different between benign and malignant orbital tumor groups, while gender, location, SD, and skewness were not significantly different. The best diagnostic performance in predicting malignant orbital tumors was achieved at the threshold of ADC10=0.990 (AUC, 0.997; sensitivity, 96.2%; specificity, 100%).

CONCLUSION

Histogram analysis of ADC maps holds promise for differentiating benign and malignant orbital tumors. ADC10 has the potential to be the most significant parameter for predicting malignant orbital tumors.

Hypoxia in cervical cancer: from biology to imaging

PURPOSE

Hypoxia imaging may improve identification of cervical cancer patients at risk of treatment failure and be utilized in treatment planning and monitoring, but its clinical potential is far from fully realized. Here, we briefly describe the biology of hypoxia in cervix tumors of relevance for imaging, and evaluate positron emission tomography (PET) and magnetic resonance imaging (MRI) techniques that have shown promise for assessing hypoxia in a clinical setting. We further discuss emerging imaging approaches, and how imaging can play a role in future treatment strategies to target hypoxia.

METHODS

We performed a PubMed literature search, using keywords related to imaging and hypoxia in cervical cancer, with a particular emphasis on studies correlating imaging with other hypoxia measures and treatment outcome.

RESULTS

Only a few and rather small studies have utilized PET with tracers specific for hypoxia, and no firm conclusions regarding preferred tracer or clinical potential can be drawn so far. Most studies address indirect hypoxia imaging with dynamic contrast-enhanced techniques. Strong evidences for a role of these techniques in hypoxia imaging have been presented. Pre-treatment images have shown significant association to outcome in several studies, and images acquired during fractionated radiotherapy may further improve risk stratification. Multiparametric MRI and multimodality PET/MRI enable combined imaging of factors of relevance for tumor hypoxia and warrant further investigation.

CONCLUSIONS

Several imaging approaches have shown promise for hypoxia imaging in cervical cancer. Evaluation in large clinical trials is required to decide upon the optimal modality and approach.

Application of magnetic resonance imaging in diagnosis of Uterus Cervical Carcinoma

BACKGROUND AND OBJECTIVE

Effective treatment of Uterus Cervical Carcinoma (UCC) rely heavily on the precise pre-surgical staging. The conventional International Federation of Gynecology and Obstetrics (FIGO) system based on clinical examination is being applied worldwide for UCC staging. Yet its performance just appears passable. Thus, this study aims to investigate the value of applying Magnetic Resonance Imaging (MRI) with clinical examination in staging of UCC.

MATERIALS AND METHODS

A retrospective dataset involving 164 patients diagnosed with UCC was enrolled in this study. The mean age of this study population was 46.1 years (range, 28-#x2013;75 years). All patients underwent operations and UCC types were confirmed by pathological examinations. The tumor stages were determined by two experienced Gynecologist independently based on FIGO examinations and MRI. The diagnostic results were also compared with the post-operative pathologic reports. Statistical data analysis on diagnostic performance was then done and reported.

RESULTS

The study results showed that the overall accuracy of applying MRI in UCC staging was 82.32%, while using FIGO staging method, the staging accuracy was 59.15%.

CONCLUSIONS

MRI is suitable to evaluate tumor extent with high accuracy, and it can offer more objective information for the diagnosis and staging of UCC. Compared with clinical examinations based on FIGO, MRI illustrated relatively high accuracy in evaluating UCC staging, and is worthwhile to be recommended in future clinical practice.

Functional MR imaging in gynecologic malignancies: current status and future perspectives

Using functional MR imaging techniques, we can approach the functional assessment of gynecologic malignancies. Among them, diffusion-weighted imaging (DWI) and dynamic contrast-enhanced MR imaging (DCE-MRI) are two important techniques. This article provides an overview of functional MR imaging techniques, focusing DWI and DCE-MRI on clinical application in gynecologic malignancies. Functional MR imaging techniques play an important role in detection, characterization, staging, treatment response, and outcome prediction, as well as providing conventional morphologic imaging. Familiarity with the characteristics and imaging features of functional MR imaging in gynecologic malignancies will facilitate prompt and accurate diagnosis and treatment.