Advanced ovarian cancer: multiparametric MR imaging demonstrates response- and metastasis-specific effects

Imaging of Peritoneal Metastases in Ovarian Cancer Using MDCT, MRI, and FDG PET/CT: A Systematic Review and Meta-Analysis

This review aims to compare the diagnostic performance of multidetector CT (MDCT), MRI, including diffusion-weighted imaging, and FDG PET/CT in the detection of peritoneal metastases (PMs) in ovarian cancer (OC). A comprehensive search was performed for articles published from 2000 to February 2023. The inclusion criteria were the following: diagnosis/suspicion of PMs in patients with ovarian/fallopian/primary peritoneal cancer; initial staging or suspicion of recurrence; MDCT, MRI and/or FDG PET/CT performed for the detection of PMs; population of at least 10 patients; surgical results, histopathologic analysis, and/or radiologic follow-up, used as reference standard; and per-patient and per-region data and data for calculating sensitivity and specificity reported. In total, 33 studies were assessed, including 487 women with OC and PMs. On a per-patient basis, MRI (p = 0.03) and FDG PET/CT (p < 0.01) had higher sensitivity compared to MDCT. MRI and PET/CT had comparable sensitivities (p = 0.84). On a per-lesion analysis, no differences in sensitivity estimates were noted between MDCT and MRI (p = 0.25), MDCT and FDG PET/CT (p = 0.68), and MRI and FDG PET/CT (p = 0.35). Based on our results, FDG PET/CT and MRI are the preferred imaging modalities for the detection of PMs in OC. However, the value of FDG PET/CT and MRI compared to MDCT needs to be determined. Future research to address the limitations of the existing studies and the need for standardization and to explore the cost-effectiveness of the three imaging modalities is required.

MRI assessment of ovarian masses and correlating with CA-125

BACKGROUND

The combined use of appropriate imaging modalities and serum biomarkers like serum Carcinoembryonic Antigen-125 (CA-125) helps plan treatment strategies and reduce overall mortality.

AIMS AND OBJECTIVES

To assess ovarian masses on Magnetic Resonance Imaging (MRI) and correlate them with serum CA-125 values. To derive a new serum CA-125 cut-off value for differentiating benign from malignant ovarian masses.

MATERIALS AND METHODS

This cross-sectional study was conducted from August 2020 to January 2021 on patients with suspected pelvic masses referred to the department of radio-diagnosis and meeting inclusion and exclusion criteria. Serum CA-125 values and imaging features on MRI were recorded.

RESULTS

A total of 37 ovarian masses were included in the study, of which 14 were malignant and 23 were benign. The mean CA-125 values among benign [35.95 ± 25.42 (mean ± SD) IU/ml] and malignant ovarian masses [444.82 ± 232.9 (mean ± SD) IU/ml] were statistically significant (<0.001). Using the reference serum CA-125 value of 35 IU/ml, specificity and accuracy were 61% and 75.68%. A cut-off value of 80.5 IU/ml recorded specificity and accuracy of 95.7% and 94.59%, respectively, with a sensitivity of 92.86% in differentiating benign from malignant ovarian masses.

CONCLUSION

The serum CA-125 cut-off value of 80.5 IU/ml is a sensitive and specific serum biomarker for ovarian malignancies. A combined approach of MR imaging and serum CA-125 correlation can be used in characterizing ovarian malignancies in routine clinical practice.

A Novel Approach for Estimating Ovarian Cancer Tissue Heterogeneity through the Application of Image Processing Techniques and Artificial Intelligence

PURPOSE

Tumor heterogeneity may be responsible for poor response to treatment and adverse prognosis in women with HGOEC. The purpose of this study is to propose an automated classification system that allows medical experts to automatically identify intratumoral areas of different cellularity indicative of tumor heterogeneity.

METHODS

Twenty-two patients underwent dedicated pelvic MRI, and a database of 11,095 images was created. After image processing techniques were applied to align and assess the cancerous regions, two specific imaging series were used to extract quantitative features (radiomics). These features were employed to create, through artificial intelligence, an estimator of the highly cellular intratumoral area as defined by arbitrarily selected apparent diffusion coefficient (ADC) cut-off values (ADC < 0.85 × 10-3 mm2/s).

RESULTS

The average recorded accuracy of the proposed automated classification system was equal to 0.86.

CONCLUSION

The proposed classification system for assessing highly cellular intratumoral areas, based on radiomics, may be used as a tool for assessing tumor heterogeneity.

Prediction Model of Residual Neural Network for Pathological Confirmed Lymph Node Metastasis of Ovarian Cancer

Purpose. We want to develop a model for predicting lymph node status based on positron emission computed tomography (PET) images of untreated ovarian cancer patients. We use the feature map formed by wavelet transform and the parameters obtained by image segmentation to build the model. The model is expected to help clinicians and provide additional information about what to do with first-visit patients. Materials and Methods. Our study included 224 patients with ovarian cancer. We have chosen two main methods to extract information from images. On the one hand, we segmented the image to extract the parameters to evaluate the clustering effect. On the other hand, we used wavelet transform to extract the image’s texture information to form the image’s feature map. Based on the above two kinds of information, we used residual neural network and support vector machine for modeling. Results. We established a model to predict lymph node metastasis in patients with primary ovarian cancer using PET images. On the training set, our accuracy was 0.8854, AUC: 0.9472, CI: 0.9098-0.9752, sensitivity was 0.9865, and specificity was 0.7952. On the test set, our accuracy was 0.9104, AUC: 0.9259, CI: 0.8417-0.9889, sensitivity was 0.8125, and specificity was 1.0000. Conclusions. We used wavelet transform to process the preoperative medical images of ovarian cancer patients, and the residual neural network can effectively predict the lymph node metastasis of ovarian cancer patients, which is undoubted of great significance for patients’ staging and treatment options.

Advances in the management of peritoneal malignancies

Peritoneal surface malignancies (PSMs) are usually associated with a poor prognosis. Nonetheless, in line with advances in the management of most abdominopelvic metastatic diseases, considerable progress has been made over the past decade. An improved understanding of disease biology has led to the more accurate prediction of neoplasia aggressiveness and the treatment response and has been reflected in the proposal of new classification systems. Achieving complete cytoreductive surgery remains the cornerstone of curative-intent treatment of PSMs. Alongside centralization in expert centres, enabling the delivery of multimodal and multidisciplinary strategies, preoperative management is a crucial step in order to select patients who are most likely to benefit from surgery. Depending on the specific PSM, the role of intraperitoneal chemotherapy and of perioperative systemic chemotherapy, in particular, in the neoadjuvant setting, is established in certain scenarios but questioned in several others, although more prospective data are required. In this Review, we describe advances in all aspects of the management of PSMs including disease biology, assessment and improvement of disease resectability, perioperative management, systemic therapy and pre-emptive management, and we speculate on future research directions.

Early Whole-Body Diffusion-weighted MRI Helps Predict Long-term Outcome Following Peptide Receptor Radionuclide Therapy for Metastatic Neuroendocrine Tumors

Purpose To evaluate the predictive value of 7-week apparent diffusion coefficient change from baseline (ADCratio_7w) at whole-body diffusion-weighted MRI (WB-DWI MRI) after one peptide receptor radionuclide therapy (PRRT) cycle to predict outcome in patients with metastatic neuroendocrine tumor (mNET). Materials and Methods From April 2009 to May 2012, participants in a prospective clinical trial investigating yttrium 90-DOTA Phe1-Tyr³-octreotide (DOTATOC) treatment for mNET (EudraCT no. 2008-007965-22) underwent WB-DWI MRI and gallium 68 (⁶⁸Ga)-DOTATOC PET/CT before and 7 weeks after one PRRT cycle. ADCratio_7w response was compared with the 7-week Response Evaluation Criteria in Solid Tumors version 1.1 and ⁶⁸Ga-DOTATOC PET/CT quantitative responses to predict overall survival (OS) and progression-free survival (PFS) with Cox regression analysis. Results Forty participants were analyzed (mean age, 60 years ± 11 [SD]; 21 men). Median PFS and OS were 10.5 months (range, 2-36 months) and 18 months (range, 3-81 months), respectively. Survival analysis showed significantly positive effects on PFS by age (hazard ratio [HR] = 0.96, P = .007), tumor grade (HR = 2.84, P = .006), Ki-67 index (HR = 1.05, P = .01), ADCratio_7w of the least-responding lesion (ADCratio_7w-least) (HR = 0.94, P < .001), and baseline mean standardized uptake values (SUV_mean) (HR = 0.89, P = .02), with ADCratio_7w-least and SUV_mean remaining significant in multivariable analysis (P < .001, P = .02, respectively). There were significantly positive effects on OS by pretreatment lesion volume (HR = 1.004, P = .004), tumor grade (HR = 2.14, P = .04), Ki-67 index (HR = 1.05, P = .01), and ADCratio_7w-least (HR = 0.97, P < .001), with pretreatment volume and ADCratio_7w-least remaining significant at multivariable analysis (P = .005, P = .002, respectively). Conclusion The ADCratio_7w after start of PRRT for mNET was an independent predictor of patient outcome. Keywords: MR-Diffusion-Weighted Imaging, Radionuclide Therapy, Whole-Body Imaging, Metastases, Tumor Response, Treatment Effects EudraCT no. 2008-007965-22 © RSNA, 2022.

Diffusion-Weighted Magnetic Resonance Imaging in Ovarian Cancer: Exploiting Strengths and Understanding Limitations

Detection, characterization, staging, and response assessment are key steps in the imaging pathway of ovarian cancer. The most common type, high grade serous ovarian cancer, often presents late, so that accurate disease staging and response assessment are required through imaging in order to improve patient management. Currently, computerized tomography (CT) is the most common method for these tasks, but due to its poor soft-tissue contrast, it is unable to quantify early response within lesions before shrinkage is observed by size criteria. Therefore, quantifiable techniques, such as diffusion-weighted magnetic resonance imaging (DW-MRI), which generates high contrast between tumor and healthy tissue, are increasingly being explored. This article discusses the basis of diffusion-weighted contrast and the technical issues that must be addressed in order to achieve optimal implementation and robust quantifiable diffusion-weighted metrics in the abdomen and pelvis. The role of DW-MRI in characterizing adnexal masses in order to distinguish benign from malignant disease, and to differentiate borderline from frankly invasive malignancy is discussed, emphasizing the importance of morphological imaging over diffusion-weighted metrics in this regard. Its key role in disease staging and predicting resectability in comparison to CT is addressed, including its valuable use as a biomarker for following response within individual lesions, where early changes in the apparent diffusion coefficient in peritoneal metastases may be detected. Finally, the task of implementing DW-MRI into clinical trials in order to validate this biomarker for clinical use are discussed, along with the trials that include it within their protocols.

Two-dimensional and three-dimensional T2 weighted imaging-based radiomic signatures for the preoperative discrimination of ovarian borderline tumors and malignant tumors

BACKGROUND

Ovarian cancer is the most women malignancy in the whole world. It is difficult to differentiate ovarian cancers from ovarian borderline tumors because of some similar imaging findings.Radiomics study may help clinicians to make a proper diagnosis before invasive surgery.

PURPOSE

To evaluate the ability of T2-weighted imaging (T2WI)-based radiomics to discriminate ovarian borderline tumors (BOTs) from malignancies based on two-dimensional (2D) and three-dimensional (3D) lesion segmentation methods.

METHODS

A total of 95 patients with pathologically proven ovarian BOTs and 101 patients with malignancies were retrospectively included in this study. We evaluated the diagnostic performance of the signatures derived from T2WI-based radiomics in their ability to differentiate between BOTs and malignancies and compared the performance differences in the 2D and 3D segmentation models. The least absolute shrinkage and selection operator method (Lasso) was used for radiomics feature selection and machine learning processing.

RESULTS

The radiomics score between BOTs and malignancies in four types of selected T2WI-based radiomics models differed significantly at the statistical level (p < 0.0001). For the classification between BOTs and malignant masses, the 2D and 3D coronal T2WI-based radiomics models yielded accuracy values of 0.79 and 0.83 in the testing group, respectively; the 2D and 3D sagittal fat-suppressed (fs) T2WI-based radiomics models yielded an accuracy of 0.78 and 0.99, respectively.

CONCLUSIONS

Our results suggest that T2WI-based radiomic features were highly correlated with ovarian tumor subtype classification. 3D-sagittal MRI radiomics features may help clinicians differentiate ovarian BOTs from malignancies with high ACC.

Extracellular volume fraction with MRI: As an alternative predictive biomarker to dynamic contrast-enhanced MRI for chemotherapy response of pancreatic ductal adenocarcinoma

PURPOSE

To assess the feasibility of extracellular volume (ECV) fraction determined with equilibrium contrast-enhanced MRI for prediction of treatment response to chemotherapy in pancreatic ductal adenocarcinoma (PDAC) in comparison with dynamic contrast-enhanced MRI (DCE-MRI), and to clarify the association between ECV fraction and DCE-MRI-derived pharmacokinetic parameters.

METHODS

This retrospective study included 58 consecutive patients with histologically confirmed PDAC who underwent DCE-MRI before systemic chemotherapy. Tumor pharmacokinetic parameters, including the volume transfer coefficient (K^trans), rate constant (k_ep), and extracellular extravascular volume fraction (v_e) of DCE-MRI, and ECV fraction determined with equilibrium contrast-enhanced MRI were compared between the response and non-response groups. The correlation of tumor ECV fraction with each DCE-MRI-derived pharmacokinetic parameter was examined using Spearman's rank correlation coefficient.

RESULTS

Tumor K^trans, v_e, and ECV fraction were significantly higher in the response group than in the non-response group (all, P < 0.001), whereas no significant difference was found in k_ep (P = 0.119). Tumor ECV fraction showed the highest area under receiver operating characteristic curve of 0.918, with a sensitivity of 89.3%, specificity of 90.0%, and accuracy of 89.7% (cut off, >37.6%). The ECV fraction showed a significant positive correlation with K^trans (Spearman's coefficient = 0.66, P < 0.001) and v_e (Spearman's coefficient = 0.79, P < 0.001).

CONCLUSIONS

ECV fraction determined with equilibrium contrast-enhanced MRI was as useful as DCE-MRI-derived pharmacokinetic parameters for predicting treatment response to chemotherapy in patients with PDAC.

Diffusion-weighted MRI and PET/CT reproducibility in epithelial ovarian cancers during neoadjuvant chemotherapy

PURPOSE

To investigate the reproducibility of diffusion-weighted (DW) MRI and ¹⁸F-Fluorodeoxyglucose (¹⁸F-FDG)-Positron emission tomography/CT (PET/CT) in monitoring response to neoadjuvant chemotherapy in epithelial ovarian cancer.

MATERIALS AND METHODS

Ten women (median age, 67 years; range: 41.8-77.3 years) with stage IIIC-IV epithelial ovarian cancers were included in this prospective trial (NCT02792959) between 2014 and 2016. All underwent initial laparoscopic staging, four cycles of carboplatine-paclitaxel-based chemotherapy and interval debulking surgery. PET/CT and DW-MRI were performed at baseline (C0), after one cycle (C1) and before surgery (C4). Two nuclear physicians and two radiologists assessed five anatomic sites for the presence of ≥1 lesion. Target lesions in each site were defined and their apparent diffusion coefficient (ADC), maximal standardized uptake value (SUV-max), SUV-mean, SUL-peak, metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were monitored (i.e., 10 patients ×5 sites ×3 time-points). Their relative early and late changes were calculated. Intra/inter-observer reproducibilities of qualitative and quantitative analysis were estimated with Kappa and intra-class correlation coefficients (ICCs).

RESULTS

For both modalities, inter- and intra-observer agreement percentages were excellent for initial staging but declined later for DW-MRI, leading to lower Kappa values for inter- and intra-observer variability (0.949 and 1 at C0, vs. 0.633 and 0.643 at C4, respectively) while Kappa values remained>0.8 for PET/CT. Inter- and intra-observer ICCs were>0.75 for SUV-max, SUL-peak, SUV-mean and their change regardless the time-point. ADC showed lower ICCs (range: 0.013-0.811). ANOVA found significant influences of the evaluation time, the measurement used (ADC, SUV-max, SUV-mean, SUV-max, SUL-peak, MTV or TLG) and their interaction on ICC values (P=0.0023, P<0.0001 and P =0.0028, respectively).

CONCLUSION

While both modalities demonstrated high reproducibility at baseline, only SUV-max, SUL-peak, SUV-mean and their changes maintained high reproducibility during chemotherapy.

Impact of tumor heterogeneity and microenvironment in identifying neoantigens in a patient with ovarian cancer

Identification of neoepitopes as tumor-specific targets remains challenging, especially for cancers with low mutational burden, such as ovarian cancer. To identify mutated human leukocyte antigen (HLA) ligands as potential targets for immunotherapy in ovarian cancer, we combined mass spectrometry analysis of the major histocompatibility complex (MHC) class I peptidomes of ovarian cancer cells with parallel sequencing of whole exome and RNA in a patient with high-grade serous ovarian cancer. Four of six predicted mutated epitopes capable of binding to HLA-A*02:01 induced peptide-specific T cell responses in blood from healthy donors. In contrast, all six peptides failed to induce autologous peptide-specific response by T cells in peripheral blood or tumor-infiltrating lymphocytes from ascites of the patient. Surprisingly, T cell responses against a low-affinity p53-mutant Y220C epitope were consistently detected in the patient with either unprimed or in vitro peptide-stimulated T cells even though the patient's primary tumor did not bear this mutation. Our results demonstrated that tumor heterogeneity and distinct immune microenvironments within a patient should be taken into consideration for identification of immunogenic neoantigens. T cell responses to a driver gene-derived p53 Y220C mutation in ovarian cancer warrant further study.

Biomarkers for site-specific response to neoadjuvant chemotherapy in epithelial ovarian cancer: relating MRI changes to tumour cell load and necrosis

BACKGROUND

Diffusion-weighted magnetic resonance imaging (DW-MRI) potentially interrogates site-specific response to neoadjuvant chemotherapy (NAC) in epithelial ovarian cancer (EOC).

METHODS

Participants with newly diagnosed EOC due for platinum-based chemotherapy and interval debulking surgery were recruited prospectively in a multicentre study (n = 47 participants). Apparent diffusion coefficient (ADC) and solid tumour volume (up to 10 lesions per participant) were obtained from DW-MRI before and after NAC (including double-baseline for repeatability assessment in n = 19). Anatomically matched lesions were analysed after surgical excision (65 lesions obtained from 25 participants). A trained algorithm determined tumour cell fraction, percentage tumour and percentage necrosis on histology. Whole-lesion post-NAC ADC and pre/post-NAC ADC changes were compared with histological metrics (residual tumour/necrosis) for each tumour site (ovarian, omental, peritoneal, lymph node).

RESULTS

Tumour volume reduced at all sites after NAC. ADC increased between pre- and post-NAC measurements. Post-NAC ADC correlated negatively with tumour cell fraction. Pre/post-NAC changes in ADC correlated positively with percentage necrosis. Significant correlations were driven by peritoneal lesions.

CONCLUSIONS

Following NAC in EOC, the ADC (measured using DW-MRI) increases differentially at disease sites despite similar tumour shrinkage, making its utility site-specific. After NAC, ADC correlates negatively with tumour cell fraction; change in ADC correlates positively with percentage necrosis.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov NCT01505829.

Whole solid tumor volume histogram parameters for predicting the recurrence in patients with epithelial ovarian carcinoma: a feasibility study on quantitative DCE-MRI

BACKGROUND

Preoperative prediction of the recurrence of epithelial ovarian carcinoma (EOC) can guide the clinical treatment and improve the prognosis. However, there are still no reliable predictive biomarkers.

PURPOSE

To evaluate whether whole solid tumor volume histogram parameters measured from quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can predict the recurrence in patients with EOC.

MATERIAL AND METHODS

We followed up 56 patients with surgical and histopathologically diagnosed EOC who underwent quantitative DCE-MRI scans. The differences of the histogram parameters between patients with and without recurrence were compared. Mann-Whitney U test, Pearson's Chi-squared test, or Fisher's exact test, and receiver operating characteristic (ROC) curves were used for statistical analysis.

RESULTS

All histogram parameters of K^trans, k_ep, and v_e were not significantly different between EOC patients with and without recurrence (P>0.05). For 30 patients with high-grade serous ovarian carcinoma (HGSOC), the histogram parameters of K^trans (mean and 5th, 10th, 25th, 50th, 75th percentiles) and k_ep (mean and 50th percentile) in 12 patients with recurrence were significantly lower than those in 18 patients without recurrence (all P<0.05). ROC curves showed that the 5th percentile of K^trans had the largest area under the curve (AUC) of 0.792 for predicting the recurrence in patients with HGSOC. When the threshold value was ≤0.0263/min, the sensitivity, specificity, and accuracy were 100%, 66.7%, and 80%, respectively.

CONCLUSION

Instead of predicting the recurrence of EOC, whole solid tumor volume quantitative DCE-MRI histogram parameters could predict the recurrence of HGSOC and may be potential biomarkers for the prediction of HGSOC recurrence.

Do DWI and quantitative DCE perfusion MR have a prognostic value in high-grade serous ovarian cancer?

PURPOSE

To evaluate whether perfusion and diffusion parameters from staging MR in ovarian cancer (OC) patients may predict the presence of residual tumor at surgery and the progression-free survival (PFS) in 12 months.

MATERIALS AND METHODS

Patients who are from a single institution, candidate for OC to cytoreductive surgery and undergoing MR for staging purposes were included in this study. Inclusion criteria were: preoperative MR including diffusion-weighted imaging (DWI) and perfusion dynamic contrast-enhanced (DCE) sequence; cytoreductive surgery performed within a month from MR; and minimum follow-up of 12 months. Patients' characteristics including the presence of residual tumor at surgery (R0 or R1) and relapse within 12 months from surgery were recorded. DWI parameters included apparent diffusion coefficient (ADC) of the largest ovarian mass (O-ADC) and normalized ovarian ADC as a ratio between ovarian ADC and muscle ADC (M-ADC). DCE quantitative parameters included were descriptors of tumor vascular properties such as forward and backward transfer constants, plasma volume and volume of extracellular space. Statistical analysis was performed, and p values < 0.05 were considered significant.

RESULTS

Forty-nine patients were included. M-ADC showed a slightly significant association with the presence of residual tumor at surgery. None of the other functional parameters showed either difference between R0 and R1 patients or association with PFS in the first 12 months.

CONCLUSIONS

This preliminary study demonstrated a slightly significant association between normalized ovarian ADC and the presence of residual tumor at surgery. The other perfusion and diffusion parameters were not significant for the endpoints of this study.

Diffusion kurtosis MRI as a predictive biomarker of response to neoadjuvant chemotherapy in high grade serous ovarian cancer

This study assessed the feasibility of using diffusion kurtosis imaging (DKI) as a measure of tissue heterogeneity and proliferation to predict the response of high grade serous ovarian cancer (HGSOC) to neoadjuvant chemotherapy (NACT). Seventeen patients with HGSOC were imaged at 3 T and had biopsy samples taken prior to any treatment. The patients were divided into two groups: responders and non-responders based on Response Evaluation Criteria In Solid Tumours (RECIST) criteria. The following imaging metrics were calculated: apparent diffusion coefficient (ADC), apparent diffusion (Dapp) and apparent kurtosis (Kapp). Tumour cellularity and proliferation were quantified using histology and Ki-67 immunohistochemistry. Mean Kapp before therapy was higher in responders compared to non-responders: 0.69 ± 0.13 versus 0.51 ± 0.11 respectively, P = 0.02. Tumour cellularity correlated positively with Kapp (rho = 0.50, P = 0.04) and negatively with both ADC (rho = -0.72, P = 0.001) and Dapp (rho = -0.80, P < 0.001). Ki-67 expression correlated with Kapp (rho = 0.53, P = 0.03) but not with ADC or Dapp. In conclusion, Kapp was found to be a potential predictive biomarker of NACT response in HGSOC, which suggests that DKI is a promising clinical tool for use oncology and radiology that should be evaluated further in future larger studies.

Measuring response to neoadjuvant chemotherapy in high-grade serous tubo-ovarian carcinoma: an analysis of the correlation between CT imaging and chemotherapy response score

INTRODUCTION

Response to neoadjuvant chemotherapy is measured by CT and the decision to proceed with interval surgery is made on the radiological response after two or three cycles of therapy. The Chemotherapy Response Score grades histological tumor regression in omental metastases resected at interval surgery and is associated with progression-free survival and overall survival. It is uncertain whether radiological response is associated with prognosis and whether radiological response predicts Chemotherapy Response Score.To assess if radiological response is associated with progression-free survival and overall survival. Additionally, to investigate whether radiological response predicts the Chemotherapy Response Score.

METHODS

Retrospective cohort study of patients with high-grade serous ovarian cancer treated with neoadjuvant chemotherapy. Radiological response was assessed by comparing CT imaging at baseline and after neoadjuvant chemotherapy using RECIST (Response Evaluation Criteria In Solid Tumors) and classified as stable disease, partial response, complete response, or progressive disease. Survival analysis was performed using Cox proportional-hazard models and the log-rank test.

RESULTS

A total of 71 patients met the inclusion criteria. Of these, 51 had pre- and post-neoadjuvant chemotherapy CT scans available for analysis. Radiological response was not associated with progression-free survival or overall survival on univariate analysis (stable disease vs partial response; HR for progression-free survival 1.15; 95% CI 0.57 to 2.32; p = 0.690; HR for overall survival 1.19; 95% CI 0.57 to 2.46; p = 0.645). In a multivariate model, radiological response was not associated with either progression-free survival (stable disease vs partial response; HR=1.19; 95% CI 0.498 to 2.85; p = 0.694) or overall survival (stable disease vs partial response; HR=0.954; 95% CI 0.38 to 2.40; p = 0.920). There was a significant association between the Chemotherapy Response Score and radiological response (p = 0.005).

DISCUSSION

A partial response and stable disease on radiological assessment after neoadjuvant chemotherapy in women with advanced high-grade serous ovarian cancer were not associated with survival, despite having a correlation with the Chemotherapy Response Score.

[Diagnostic value of imaging (ultrasonography, doppler, CT, MR, PET-CT) for the diagnosis of a suspicious ovarian mass and staging of ovarian, tubal or primary peritoneal cancer: Article drafted from the French Guidelines in oncology entitled "Initial management of patients with epithelial ovarian cancer" developed by FRANCOGYN, CNGOF, SFOG, GINECO-ARCAGY under the aegis of CNGOF and endorsed by INCa]

Transvaginal ultrasound is the first-line examination allowing characterizing 80 to 90% of adnexal masses (LP1). If performed by an expert, a subjective analysis is optimal. If performed by a non-expert, combining the use of Simple Rules with subjective analysis can achieve the diagnostic performance of an expert (LP1). Whichever the chosen model (subjective analysis by an expert or combination of the Simple Rules with a subjective analysis by a non-expert), a second-line examination will have to be proposed in the complex or indeterminate cases (about 20% of the masses) (grade A). The best-performing second-line test for characterization is pelvic MRI (LP1). If read by an expert, a pathological hypothesis can or should be suggested (grade D). In case of non-expert reading, the use of the ADNEXMR score allows a reliable assessment of the positive predictive value of malignancy to guide the patient towards the best management (gradeC). For preoperative assessment and evaluation of resectability of ovarian, fallopian tube or primary peritoneal cancer, it is recommended to perform a chest abdomen and pelvis CT with contrast agent injection (LP2, grade B). In the event of a contraindication to the injection of iodinated contrast agent (severe renal insufficiency, GFR <30mL/min), an abdomen and pelvis MRI completed with a non-injected chest CT may be proposed (LP3, grade C). By analogy, the same examinations are recommended to evaluate the disease after neo-adjuvant chemotherapy (LP3, Recommendation grade C). Further studies will be required to determine whether PET-CT provides better lymph node assessment before retroperitoneal and pelvic lymphadenectomy. PET-CT may be used to eliminate lymph node involvement in the absence of suspicious lymph nodes on morphological examination (LP3, grade C). The report should specify the localizations leading to a risk of incomplete cytoreductive surgery and lesions outside the field explored during surgery.

Human Ovarian Cancer Tumor Formation in Severe Combined Immunodeficient (SCID) Pigs

Ovarian cancer (OvCa) is the most lethal gynecologic malignancy, with two-thirds of patients having late-stage disease (II-IV) at diagnosis. Improved diagnosis and therapies are needed, yet preclinical animal models for ovarian cancer research have primarily been restricted to rodents, for data on which can fail to translate to the clinic. Thus, there is currently a need for a large animal OvCa model. Therefore, we sought to determine if pigs, being more similar to humans in terms of anatomy and physiology, would be a viable preclinical animal model for OvCa. We injected human OSPC-ARK1 cells, a chemotherapy-resistant primary ovarian serous papillary carcinoma cell line, into the neck muscle and ear tissue of four severe combined immune deficient (SCID) and two non-SCID pigs housed in novel biocontainment facilities to study the ability of human OvCa cells to form tumors in a xenotransplantation model. Tumors developed in ear tissue of three SCID pigs, while two SCID pigs developed tumors in neck tissue; no tumors were detected in non-SCID control pigs. All tumor masses were confirmed microscopically as ovarian carcinomas. The carcinomas in SCID pigs were morphologically similar to the original ovarian carcinoma and had the same immunohistochemical phenotype based on expression of Claudin 3, Claudin 4, Cytokeratin 7, p16, and EMA. Confirmation that OSPC-ARK1 cells form carcinomas in SCID pigs substantiates further development of orthotopic models of OvCa in pigs.

Quantitative imaging of cancer in the postgenomic era: Radio(geno)mics, deep learning, and habitats

Although cancer often is referred to as "a disease of the genes," it is indisputable that the (epi)genetic properties of individual cancer cells are highly variable, even within the same tumor. Hence, preexisting resistant clones will emerge and proliferate after therapeutic selection that targets sensitive clones. Herein, the authors propose that quantitative image analytics, known as "radiomics," can be used to quantify and characterize this heterogeneity. Virtually every patient with cancer is imaged radiologically. Radiomics is predicated on the beliefs that these images reflect underlying pathophysiologies, and that they can be converted into mineable data for improved diagnosis, prognosis, prediction, and therapy monitoring. In the last decade, the radiomics of cancer has grown from a few laboratories to a worldwide enterprise. During this growth, radiomics has established a convention, wherein a large set of annotated image features (1-2000 features) are extracted from segmented regions of interest and used to build classifier models to separate individual patients into their appropriate class (eg, indolent vs aggressive disease). An extension of this conventional radiomics is the application of "deep learning," wherein convolutional neural networks can be used to detect the most informative regions and features without human intervention. A further extension of radiomics involves automatically segmenting informative subregions ("habitats") within tumors, which can be linked to underlying tumor pathophysiology. The goal of the radiomics enterprise is to provide informed decision support for the practice of precision oncology.

Diffusion-weighted imaging and diffusion kurtosis imaging for early evaluation of the response to docetaxel in rat epithelial ovarian cancer

Background

To investigate diffusion-weighted magnetic imaging (DWI) and diffusion kurtosis magnetic imaging (DKI) for the early detection of the response to docetaxel (DTX) chemotherapy in rat epithelial ovarian cancer (EOC).

Methods

7,12-Dimethylbenz[A]anthracene was applied to induce orthotopic EOC in Sprague–Dawley rats. Rats with EOC were treated with DTX on day 0 (treatment group) or were left untreated (control group). DWI and DKI were performed on days 0, 3, 7, 14 and 21 after treatment. On day 21, the tumors were categorized into the sensitive and insensitive groups according to the size change. The cutoff values of the DWI and DKI parameters for the early response were determined. The experiment was repeated, and the treatment group was divided into the sensitive and insensitive groups according to the initially obtained cutoff values. The DWI and DKI parameters were correlated with tumor size, proliferation, apoptosis and tumor necrosis.

Results

In the sensitive vs. insensitive or control group, significant differences were found in the Δ% of the DWI and DKI parameters (ADC, D and K) from day 3 and in tumor size from day 14. Early on day 7, the Δ% of K had an AUC of 1 and sensitivity and specificity values of 100% and 100%, respectively, to detect the response to DTX using a cutoff value of 19.03% reduction in K. From day 7, significant differences were found in the Δ% of Ki-67 and CA125 in the sensitive vs. control group and from day 14 in the sensitive vs. insensitive group. From day 14, there were significant differences in the Δ% of Bcl-2, apoptosis and tumor necrosis in the sensitive vs. control or insensitive group. The Δ% values of ADC and D were negatively correlated with the Δ% values of tumor size, Ki-67, CA125 and Bcl-2 and were positively correlated with the Δ% values of apoptosis and tumor necrosis. The Δ% of K was positively correlated with the Δ% values of tumor size, Ki-67, CA125 and Bcl-2 and was negatively correlated with the Δ% values of apoptosis and tumor necrosis.

Conclusions

DWI and DKI parameters, especially K, are superior for imaging tumor size for the early detection of the response to DTX chemotherapy in induced rat EOC.

Quantitative dynamic contrast-enhanced MR imaging for differentiating benign, borderline, and malignant ovarian tumors

PURPOSE

This study aimed to investigate the diagnostic performance of quantitative DCE-MRI for characterizing ovarian tumors.

METHODS

We prospectively assessed the differences of quantitative DCE-MRI parameters (K^trans, k_ep, and v_e) among 15 benign, 28 borderline, and 66 malignant ovarian tumors; and between type I (n = 28) and type II (n = 29) of epithelial ovarian carcinomas (EOCs). DCE-MRI data were analyzed using whole solid tumor volume region of interest (ROI) method, and quantitative parameters were calculated based on a modified Tofts model. The non-parametric Kruskal-Wallis test, Mann-Whitney U test, Pearson's chi-square test, intraclass correlation coefficient (ICC), variance test, and receiver operating characteristic curves (ROC) were used for statistical analysis.

RESULTS

The largest K^trans and k_ep values were observed in ovarian malignant tumors, followed by borderline and benign tumors (all P < 0.001). K_ep was the better parameter for differentiating benign tumors from borderline and malignant tumors, with a sensitivity of 89.3% and 95.5%, a specificity of 86.7% and 100%, an accuracy of 88.4% and 96.3%, and an area under the curve (AUC) of 0.94 and 0.992, respectively, whereas K^trans was better for differentiating borderline from malignant tumors with a sensitivity of 60.7%, a specificity of 78.8%, an accuracy of 73.4%, and an AUC of 0.743. In addition, a combination with k_ep could further improve the sensitivity to 78.9%. The median K^trans and k_ep values were significantly higher in type II than in type I EOCs.

CONCLUSION

DCE-MRI with volume quantification is a technically feasible method, and can be used for the differentiation of ovarian tumors and for discriminating between type I and type II EOCs.

Early Response Assessment in Pancreatic Ductal Adenocarcinoma Through Integrated PET/MRI

OBJECTIVE

The purpose of this study is to investigate early changes in ¹⁸F-FDG PET/MRI metrics after treatment in patients with advanced pancreatic ductal adenocarcinoma (PDAC) and to correlate those changes with eventual tumor response at standard-of-care CT.

SUBJECTS AND METHODS

Thirteen patients with advanced PDAC underwent integrated FDG PET/MRI before and 4 weeks after treatment initiation. Patients were classified as responders or nonresponders according to Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 at subsequent CT performed 8-12 weeks after treatment initiation. Changes in the primary tumor's maximum standardized uptake value (SUV_max), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) determined at PET and apparent diffusion coefficient (ADC) determined at DWI at 4 weeks were compared between responders and nonresponders.

RESULTS

Seven patients had a partial response according to RECIST, and six did not. Responders displayed significantly greater decreases in MTV (p = 0.003) and TLG (p = 0.006) in the primary pancreatic tumor at 4 weeks. Responders also displayed a greater increase in the mean (p = 0.004) and minimum (p = 0.024) ADC of the primary tumors. Tumor size change at 4 weeks was not significantly different between responders and nonresponders (p = 0.11). PET responders enjoyed longer progression-free survival (PFS) (p = 0.0004) and overall survival (OS) (p = 0.013) than did nonresponders, using either a 60% reduction in MTV or 65% reduction in TLG as a threshold. MRI responders had significantly longer PFS (p = 0.0002) and OS (p = 0.027) than did nonresponders, using a 20% increase in either mean or minimum ADC as a threshold.

CONCLUSION

Integrated PET/MRI can provide early response assessment in patients with advanced PDAC, thus potentially allowing early treatment adaptation in nonresponders.

Magnetic resonance diffusion-weighted imaging in diagnostics of primary fallopian tube carcinoma - is it useful?

Purpose

Primary fallopian tube carcinoma (PFTC) is the rarest form of female genital malignancy. The imaging applied for suspected adnexal masses includes transvaginal ultrasound (US), computed tomography (CT), and magnetic resonance imaging (MRI), but the vast majority of PFTC is recognised intraoperatively.

Material and methods

The study group consisted of seven women with postoperatively histopathological diagnosis of PFTC. To recognise characteristic findings for PFTC, retrospective analysis of preoperative MRI was performed. All patients underwent MRI of the pelvis and abdomen using a 1.5T MR system. Based on the results of the above imaging, suspected adnexal masses were recognised. MRI protocol contained T2-weighted images, fat-suppressed T2-weighted, T2-TIRM, DW EPI, pre- and postcontrast dynamic 3D T1 GRE in transverse orientation, with diffusion weightings of 0, 50, 100, 150, 200, 400, 800, and 1200 s/mm2. Regions of interest were outlined by a radiologist, who documented the character of adnexal masses on diffusion-weighted (DW) images and apparent diffusion coefficient (ADC) maps.

Results

In all seven patients with PFTC unilateral tumour was found. On all DW images (with β values of 0, 50, 100, 150, 200, 400, 800, and 1200 s/mm2) the mean signal intensities of solid parts of tumour were significantly higher than the mean signal intensities of normal ovarian tissue (p = 0.0001). There were no statistically significant differences between eight β values applied for ADC calculations.

Conclusions

Preoperative diagnostics of PFTC is difficult and mainly based on morphological features. Previous research did not show characteristics of PFTC in post-contrast dynamic imaging. In our material a clear increasing of signal intensity in DW imaging occurred independently of the β value.

Heterogeneous Tumor-Immune Microenvironments among Differentially Growing Metastases in an Ovarian Cancer Patient

We present an exceptional case of a patient with high-grade serous ovarian cancer, treated with multiple chemotherapy regimens, who exhibited regression of some metastatic lesions with concomitant progression of other lesions during a treatment-free period. Using immunogenomic approaches, we found that progressing metastases were characterized by immune cell exclusion, whereas regressing and stable metastases were infiltrated by CD8+ and CD4+ T cells and exhibited oligoclonal expansion of specific T cell subsets. We also detected CD8+ T cell reactivity against predicted neoepitopes after isolation of cells from a blood sample taken almost 3 years after the tumors were resected. These findings suggest that multiple distinct tumor immune microenvironments co-exist within a single individual and may explain in part the heterogeneous fates of metastatic lesions often observed in the clinic post-therapy. VIDEO ABSTRACT.

Phosphatidylcholine-specific phospholipase C inhibition reduces HER2-overexpression, cell proliferation and in vivo tumor growth in a highly tumorigenic ovarian cancer model

Antagonizing the oncogenic effects of human epidermal growth factor receptor 2 (HER2) with current anti-HER2 agents has not yet yielded major progress in the treatment of advanced HER2-positive epithelial ovarian cancer (EOC). Using preclinical models to explore alternative molecular mechanisms affecting HER2 overexpression and oncogenicity may lead to new strategies for EOC patient treatment. We previously reported that phosphatidylcholine-specific phospholipase C (PC-PLC) exerts a pivotal role in regulating HER2 overexpression in breast cancer cells. The present study, conducted on two human HER2-overexpressing EOC cell lines - SKOV3 and its in vivo-passaged SKOV3.ip cell variant characterized by enhanced in vivo tumorigenicity - and on SKOV3.ip xenografts implanted in SCID mice, showed: a) about 2-fold higher PC-PLC and HER2 protein expression levels in SKOV3.ip compared to SKOV3 cells; b) physical association of PC-PLC with HER2 in non-raft domains; c) HER2 internalization and ca. 50% reduction of HER2 mRNA and protein expression levels in SKOV3.ip cells exposed to the PC-PLC inhibitor tricyclodecan-9-yl-potassium xanthate (D609); d) differential effects of D609 and trastuzumab on HER2 protein expression and cell proliferation; e) decreased in vivo tumor growth in SKOV3.ip xenografts during in vivo treatment with D609; f) potential use of in vivo magnetic resonance spectroscopy (MRS) and imaging (MRI) parameters as biomarkers of EOC response to PC-PLC inhibition. Overall, these findings support the view that PC-PLC inhibition may represent an effective means to target the tumorigenic effects of HER2 overexpression in EOC and that in vivo MR approaches can efficiently monitor its effects.

DCE-MRI, DW-MRI, and MRS in Cancer: Challenges and Advantages of Implementing Qualitative and Quantitative Multi-parametric Imaging in the Clinic

Multi-parametric magnetic resonance imaging (mpMRI) offers a unique insight into tumor biology by combining functional MRI techniques that inform on cellularity (diffusion-weighted MRI), vascular properties (dynamic contrast-enhanced MRI), and metabolites (magnetic resonance spectroscopy) and has scope to provide valuable information for prognostication and response assessment. Challenges in the application of mpMRI in the clinic include the technical considerations in acquiring good quality functional MRI data, development of robust techniques for analysis, and clinical interpretation of the results. This article summarizes the technical challenges in acquisition and analysis of multi-parametric MRI data before reviewing the key applications of multi-parametric MRI in clinical research and practice.

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

Diffusion MRI in early cancer therapeutic response assessment

Imaging biomarkers for the predictive assessment of treatment response in patients with cancer earlier than standard tumor volumetric metrics would provide new opportunities to individualize therapy. Diffusion-weighted MRI (DW-MRI), highly sensitive to microenvironmental alterations at the cellular level, has been evaluated extensively as a technique for the generation of quantitative and early imaging biomarkers of therapeutic response and clinical outcome. First demonstrated in a rodent tumor model, subsequent studies have shown that DW-MRI can be applied to many different solid tumors for the detection of changes in cellularity as measured indirectly by an increase in the apparent diffusion coefficient (ADC) of water molecules within the lesion. The introduction of quantitative DW-MRI into the treatment management of patients with cancer may aid physicians to individualize therapy, thereby minimizing unnecessary systemic toxicity associated with ineffective therapies, saving valuable time, reducing patient care costs and ultimately improving clinical outcome. This review covers the theoretical basis behind the application of DW-MRI to monitor therapeutic response in cancer, the analytical techniques used and the results obtained from various clinical studies that have demonstrated the efficacy of DW-MRI for the prediction of cancer treatment response. Copyright © 2016 John Wiley & Sons, Ltd.

The distribution of the apparent diffusion coefficient as an indicator of the response to chemotherapeutics in ovarian tumour xenografts

Diffusion-weighted magnetic resonance imaging (DW-MRI) was used to evaluate the effects of single-agent and combination treatment regimens in a spheroid-based animal model of ovarian cancer. Ovarian tumour xenografts grown in non-obese diabetic/severe-combined-immunodeficiency (NOD/SCID) mice were treated with carboplatin or paclitaxel, or combination carboplatin/paclitaxel chemotherapy regimens. After 4 weeks of treatment, tumours were extracted and underwent DW-MRI, mechanical testing, immunohistochemical and gene expression analyses. The distribution of the apparent diffusion coefficient (ADC) exhibited an upward shift as a result of each treatment regimen. The 99-th percentile of the ADC distribution (“maximum ADC”) exhibited a strong correlation with the tumour size (r² = 0.90) and with the inverse of the elastic modulus (r² = 0.96). Single-agent paclitaxel (n = 5) and combination carboplatin/paclitaxel (n = 2) treatment regimens were more effective in inducing changes in regions of higher cell density than single-agent carboplatin (n = 3) or the no-treatment control (n = 5). The maximum ADC was a good indicator of treatment-induced cell death and changes in the extracellular matrix (ECM). Comparative analysis of the tumours’ ADC distribution, mechanical properties and ECM constituents provides insights into the molecular and cellular response of the ovarian tumour xenografts to chemotherapy. Increased sample sizes are recommended for future studies. We propose experimental approaches to evaluation of the timeline of the tumour’s response to treatment.

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.

Magnetic Resonance Imaging of Gynecological Malignancies: Role in Personalized Management

Gynecological malignancies are a leading cause of mortality and morbidity in women and pose a significant health problem around the world. Currently used staging systems for management of gynecological malignancies have unresolved issues, the most important being recommendations on the use of imaging. Although not mandatory as per the International Federation of Gynecology and Obstetrics recommendations, preoperative cross-sectional imaging is strongly recommended for adequate and optimal management of patients with gynecological malignancies. Standardized disease-specific magnetic resonance imaging protocols help assess disease spread accurately and avoid pitfalls. Multiparametric imaging holds promise as a roadmap to personalized management in gynecological malignancies. In this review, we will highlight the role of magnetic resonance imaging in cervical, endometrial, and ovarian carcinomas.

Diffusion-weighted magnetic resonance neurography for the diagnosis of carpal tunnel syndrome: a pilot study

AIM

To investigate the applicability of diffusion-weighted magnetic resonance neurography (DW-MRN) in the diagnosis of carpal tunnel syndrome (CTS).

MATERIALS AND METHODS

In total, 47 patients with CTS (69 wrists) and 19 normal participants (38 wrists) was included in this study. Cross-sectional area (CSA) and apparent diffusion coefficient (ADC) values of the median nerves in the carpal tunnel were determined using DW-MRN. Receiver operating characteristic (ROC) analysis was performed.

RESULTS

No significant differences in age or body mass index (BMI) were observed between the control and CTS groups. DW-MRN imaging showed obvious hyperintensity in the lesions in CTS wrists, while other nerve regions were related to slight hyperintensity. Interobserver variability analysis indicated excellent agreement regarding both the CSA and ADC measurements for the control and CTS groups. Both the mean CSA and ADC values of the median nerves in carpal tunnel in the CTS group were significantly higher than the control group. According to the ROC analysis, the CSA cut-off value was 11.7 mm², and sensitivity and specificity were 66.7% and 89.5%, respectively. Conversely, the median nerve ADC cut-off value was 1.047×10^-3 mm²/s. The sensitivity and specificity were 91.3% and 76.3.9%, respectively.

CONCLUSION

DW-MRN represents a highly reproducible diagnostic technique for CTS. The ADC value of median nerves in the carpal tunnel is significantly higher in CTS patients, which provides a potential powerful tool for the disease diagnosis.

Therapy Monitoring with Functional and Molecular MR Imaging

Cancer therapy is mainly based on different combinations of surgery, radiotherapy, and chemotherapy. Additionally, targeted therapies (designed to disrupt specific tumor hallmarks, such as angiogenesis, metabolism, proliferation, invasiveness, and immune evasion), hormonotherapy, immunotherapy, and interventional techniques have emerged as alternative oncologic treatments. Conventional imaging techniques and current response criteria do not always provide the necessary information regarding therapy success particularly to targeted therapies. In this setting, MR imaging offers an attractive combination of anatomic, physiologic, and molecular information, which may surpass these limitations, and is being increasingly used for therapy response assessment.

In vivo Magnetic Resonance Metabolic and Morphofunctional Fingerprints in Experimental Models of Human Ovarian Cancer

Epithelial ovarian cancer (EOC) is the gynecological malignancy with the highest death rate, characterized by frequent relapse and onset of drug resistance. Disease diagnosis and therapeutic follow-up could benefit from application of molecular imaging approaches, such as magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS), able to monitor metabolic and functional alterations and investigate the underlying molecular mechanisms. Here, we overview the quantitative alterations that occur during either orthotopic or subcutaneous growth of preclinical EOC models. A common feature of (1)H MR spectra is the presence of a prominent peak due to total choline-containing metabolites (tCho), together with other metabolic alterations and MRI-detected morphofunctional patterns specific for different phenotypes. The tCho signal, already present at early stages of tumor growth, and changes of diffusion-weighted MRI parameters could serve as markers of malignancy and/or tumor response to therapy. The identification by MRS and MRI of biochemical and physiopathological fingerprints of EOC disease in preclinical models can represent a basis for further developments of non-invasive MR approaches in the clinical setting.

Molecular Imaging of Ovarian Cancer

Ovarian cancer is the most lethal gynecologic malignancy and the fifth leading cause of cancer-related death in women. Over the past decade, medical imaging has played an increasingly valuable role in the diagnosis, staging, and treatment planning of the disease. In this "Focus on Molecular Imaging" review, we seek to provide a brief yet informative survey of the current state of the molecular imaging of ovarian cancer. The article is divided into sections according to modality, covering recent advances in the MR, PET, SPECT, ultrasound, and optical imaging of ovarian cancer. Although primary emphasis is given to clinical studies, preclinical investigations that are particularly innovative and promising are discussed as well. Ultimately, we are hopeful that the combination of technologic innovations, novel imaging probes, and further integration of imaging into clinical protocols will lead to significant improvements in the survival rate for ovarian cancer.

Effect of color visualization and display hardware on the visual assessment of pseudocolor medical images

PURPOSE

Even though the use of color in the interpretation of medical images has increased significantly in recent years, the ad hoc manner in which color is handled and the lack of standard approaches have been associated with suboptimal and inconsistent diagnostic decisions with a negative impact on patient treatment and prognosis. The purpose of this study is to determine if the choice of color scale and display device hardware affects the visual assessment of patterns that have the characteristics of functional medical images.

METHODS

Perfusion magnetic resonance imaging (MRI) was the basis for designing and performing experiments. Synthetic images resembling brain dynamic-contrast enhanced MRI consisting of scaled mixtures of white, lumpy, and clustered backgrounds were used to assess the performance of a rainbow ("jet"), a heated black-body ("hot"), and a gray ("gray") color scale with display devices of different quality on the detection of small changes in color intensity. The authors used a two-alternative, forced-choice design where readers were presented with 600 pairs of images. Each pair consisted of two images of the same pattern flipped along the vertical axis with a small difference in intensity. Readers were asked to select the image with the highest intensity. Three differences in intensity were tested on four display devices: a medical-grade three-million-pixel display, a consumer-grade monitor, a tablet device, and a phone.

RESULTS

The estimates of percent correct show that jet outperformed hot and gray in the high and low range of the color scales for all devices with a maximum difference in performance of 18% (confidence intervals: 6%, 30%). Performance with hot was different for high and low intensity, comparable to jet for the high range, and worse than gray for lower intensity values. Similar performance was seen between devices using jet and hot, while gray performance was better for handheld devices. Time of performance was shorter with jet.

CONCLUSIONS

Our findings demonstrate that the choice of color scale and display hardware affects the visual comparative analysis of pseudocolor images. Follow-up studies in clinical settings are being considered to confirm the results with patient images.

Update on Imaging of Ovarian Cancer

This review will make familiar with new concepts in ovarian cancer and their impact on radiological practice. Disseminated peritoneal spread and ascites are typical of the most common (70-80 %) cancer type, high-grade serous ovarian cancer. Other cancer subtypes differ in origin, precursors, and imaging features. Expert sonography allows excellent risk assessment in adnexal masses. Owing to its high specificity, complementary MRI improves characterization of indeterminate lesions. Major changes in the new FIGO staging classification include fusion of fallopian tube and primary ovarian cancer and the subcategory stage IIIA1 for retroperitoneal lymph node metastases only. Inguinal lymph nodes, cardiophrenic lymph nodes, and umbilical metastases are classified as distant metastases (stage IVB). In multidisciplinary conferences (MDC), CT has been used to predict the success of cytoreductive surgery. Resectability criteria have to be specified and agreed on in MDC. Limitations in detection of metastases may be overcome using advanced MRI techniques.

Diffusion-Weighted Imaging of Small Peritoneal Implants in "Potentially" Early-Stage Ovarian Cancer

Introduction. MRI is established modality for the diagnosis of ovarian malignancies. Advances in MRI technology, including DW imaging, could lead to the further increase in the sensitivity of MRI for the detection of peritoneal metastases. The aim of this study was to assess the accuracy of DW imaging for detection of peritoneal metastatic disease in patients suspected of having potentially early ovarian cancer and secondly to evaluate ADC values of peritoneal implants. Materials and Methods. The prospective study group consisted of 26 women with sonographic or/and CT diagnosis of suspected ovarian tumor. Based on the results of the above imaging, in none of them was extraovarian spread of disease or ascites recognized. All patients underwent MRI with DW imaging. Results. Overall, 18 extraovarian peritoneal lesions were found on DW images in 10 from 26 examined patients. All implants had diameter ≤10 mm. The presence of all lesions diagnosed by MRI was confirmed intraoperatively. Histopathologic findings in 17 proofs confirmed ovarian cancer. PPV was 94%. On all DW images (with b values of 0, 50, 100, 150, 200, 400, 800, and 1200 s/mm²) the mean signal intensities of peritoneal lesions were significantly higher than the mean signal intensities of normal adjacent tissue (p = 0.000001).

A framework for optimization of diffusion-weighted MRI protocols for large field-of-view abdominal-pelvic imaging in multicenter studies

PURPOSE

To develop methods for optimization of diffusion-weighted MRI (DW-MRI) in the abdomen and pelvis on 1.5 T MR scanners from three manufacturers and assess repeatability of apparent diffusion coefficient (ADC) estimates in a temperature-controlled phantom and abdominal and pelvic organs in healthy volunteers.

METHODS

Geometric distortion, ghosting, fat suppression, and repeatability and homogeneity of ADC estimates were assessed using phantoms and volunteers. Healthy volunteers (ten per scanner) were each scanned twice on the same scanner. One volunteer traveled to all three institutions in order to provide images for qualitative comparison. The common volunteer was excluded from quantitative analysis of the data from scanners 2 and 3 in order to ensure statistical independence, giving n = 10 on scanner 1 and n = 9 on scanners 2 and 3 for quantitative analysis. Repeatability and interscanner variation of ADC estimates in kidneys, liver, spleen, and uterus were assessed using within-patient coefficient of variation (wCV) and Kruskal-Wallis tests, respectively.

RESULTS

The coefficient of variation of ADC estimates in the temperature-controlled phantom was 1%-4% for all scanners. Images of healthy volunteers from all scanners showed homogeneous fat suppression and no marked ghosting or geometric distortion. The wCV of ADC estimates was 2%-4% for kidneys, 3%-7% for liver, 6%-9% for spleen, and 7%-10% for uterus. ADC estimates in kidneys, spleen, and uterus showed no significant difference between scanners but a significant difference was observed in liver (p < 0.05).

CONCLUSIONS

DW-MRI protocols can be optimized using simple phantom measurements to produce good quality images in the abdomen and pelvis at 1.5 T with repeatable quantitative measurements in a multicenter study.

25 Years of Contrast-Enhanced MRI: Developments, Current Challenges and Future Perspectives

In 1988, the first contrast agent specifically designed for magnetic resonance imaging (MRI), gadopentetate dimeglumine (Magnevist(®)), became available for clinical use. Since then, a plethora of studies have investigated the potential of MRI contrast agents for diagnostic imaging across the body, including the central nervous system, heart and circulation, breast, lungs, the gastrointestinal, genitourinary, musculoskeletal and lymphatic systems, and even the skin. Today, after 25 years of contrast-enhanced (CE-) MRI in clinical practice, the utility of this diagnostic imaging modality has expanded beyond initial expectations to become an essential tool for disease diagnosis and management worldwide. CE-MRI continues to evolve, with new techniques, advanced technologies, and novel contrast agents bringing exciting opportunities for more sensitive, targeted imaging and improved patient management, along with associated clinical challenges. This review aims to provide an overview on the history of MRI and contrast media development, to highlight certain key advances in the clinical development of CE-MRI, to outline current technical trends and clinical challenges, and to suggest some important future perspectives.

FUNDING

Bayer HealthCare.

Modelling DW-MRI data from primary and metastatic ovarian tumours

OBJECTIVES

To assess goodness-of-fit and repeatability of mono-exponential, stretched exponential and bi-exponential models of diffusion-weighted MRI (DW-MRI) data in primary and metastatic ovarian cancer.

METHODS

Thirty-nine primary and metastatic lesions from thirty-one patients with stage III or IV ovarian cancer were examined before and after chemotherapy using DW-MRI with ten diffusion-weightings. The data were fitted with (a) a mono-exponential model to give the apparent diffusion coefficient (ADC), (b) a stretched exponential model to give the distributed diffusion coefficient (DDC) and stretching parameter (α), and (c) a bi-exponential model to give the diffusion coefficient (D), perfusion fraction (f) and pseudodiffusion coefficient (D*).

RESULTS

Coefficients of variation, established from repeated baseline measurements, were: ADC 3.1%, DDC 4.3%, α 7.0%, D 13.2%, f 44.0%, D* 165.1%. The bi-exponential model was unsuitable in these data owing to poor repeatability. After excluding the bi-exponential model, analysis using Akaike Information Criteria showed that the stretched exponential model provided the better fit to the majority of pixels in 64% of lesions.

CONCLUSIONS

The stretched exponential model provides the optimal fit to DW-MRI data from ovarian, omental and peritoneal lesions and lymph nodes in pre-treatment and post-treatment measurements with good repeatability.

KEY POINTS

• DW-MRI data in ovarian cancer show deviation from mono-exponential behaviour • Parameters derived from the stretched exponential model showed good repeatability (CV 7%) • The bi-exponential model was unsuitable because of poor parameter repeatability • The stretched exponential model showed comparable repeatability to the mono-exponential model • The extra parameter (α) provides scope for investigation of heterogeneity or response.