Diffusion-sensitized magnetic resonance imaging highlights placental microstructural damage in patients with previous SARS-CoV-2 pregnancy infection.

INTRODUCTION: Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has been a major global health problem since December 2019. This work aimed to investigate whether pregnant women's mild and moderate SARS-CoV-2 infection was associated with microstructural and vascular changes in the placenta observable in vivo by Intravoxel Incoherent Motion (IVIM) at different gestational ages (GA). METHODS: This was a retrospective, nested case-control of pregnant women during the SARS-CoV-2 pandemic (COVID-19 group, n = 14) compared to pre-pandemic healthy controls (n = 19). MRI IVIM protocol at 1.5T was constituted of diffusion-weighted (DW) images with TR/TE = 3100/76 ms and 10 b-values (0,10,30,50,75,100,200,400,700,1000s/mm2). Differences between IVIM parameters D (diffusion), and f (fractional perfusion) quantified in the two groups were evaluated using the ANOVA test with Bonferroni correction and linear correlation between IVIM metrics and GA, COVID-19 duration, the delay time between a positive SARS-CoV-2 test and MRI examination (delay-time exam+) was studied by Pearson-test. RESULTS: D was significantly higher in the COVID-19 placentas compared to that of the age-matched healthy group (p < 0.04 in fetal and p < 0.007 in maternal site). No significant difference between f values was found in the two groups suggesting no-specific microstructural damage with no perfusion alteration (potentially quantified by f) in mild/moderate SARS-Cov-2 placentas. A significant negative correlation was found between D and GA in the COVID-19 placentas whereas no significant correlation was found in the control placentas reflecting a possible accelerated senescence process due to COVID-19. DISCUSSION: We report impaired microstructural placental development during pregnancy and the absence of perfusion-IVIM parameter changes that may indicate no perfusion changing through microvessels and microvilli in the placentas of pregnancies with mild/moderate SARS-Cov-2 after reaching negativity.

Prediction of the Risk of Malignancy of Adnexal Masses during Pregnancy Comparing Subjective Assessment and Non-Contrast MRI Score (NCMS) in Radiologists with Different Expertise.

Ovarian cancer represents 7% of all cancers in pregnant women. Characterising an ovarian mass during pregnancy is essential to avoid unnecessary treatment and, if treatment is required, to plan it accordingly. Although ultrasonography (US) is the first-line modality to characterise adnexal masses, MRI is indicated when adnexal masses are indeterminate at the US examination. An MRI risk stratification system has been proposed to assign a malignancy probability based on the adnexal lesion's MRI, but features of the scoring system require the administration of intravenous gadolinium-based contrast agents, a method that might have a limited use in pregnant women. The non-contrast MRI score (NCMS) has been used and evaluated in non-pregnant women to characterise adnexal masses indeterminate at the US examination. Therefore, we evaluated the diagnostic accuracy of the NCMS in pregnant women, analysing 20 cases referred to our specialised institution. We also evaluated the diagnostic agreement between two radiologists with different expertise. The two readers classified ovarian masses as benign or malignant using both subjective assessment (SA), based on the interpretive evaluation of imaging findings derived from personal experience, and the NCMS, which includes five categories where 4 and 5 indicate a high probability of a malignant mass. The expert radiologist correctly classified 90% of the diagnoses, using both SA and the NCMS, relying on a sensitivity of 85.7% and a specificity of 92.3%, with a false positive rate of 7.7% and a false negative rate of 14.3%. The non-expert radiologist correctly identified patients at a lower rate, especially using the SA. The analysis of the inter-observer agreement showed a K = 0.47 (95% CI: 0.48-0.94) for the SA (agreement in 71.4% of cases) and a K = 0.8 (95% CI: 0.77-1.00) for the NCMS (agreement in 90% of cases). Although in pregnant patients, non-contrast MRI is used, our results support the use of a quantitative score, i.e., the NCMS, as an accurate tool. This procedure may help less experienced radiologists to reduce the rate of false negatives or positives, especially in centres not specialised in gynaecological imaging, making the MRI interpretation easier and more accurate for radiologists who are not experts in the field, either.

The Utility of Contrast-Enhanced Magnetic Resonance Imaging in Uterine Cervical Cancer: A Systematic Review.

Correct staging of cervical cancer is essential to establish the best therapeutic procedure and prognosis for the patient. MRI is the best imaging modality for local staging and follow-up. According to the latest ESUR guidelines, T2WI and DWI-MR sequences are fundamental in these settings, and CE-MRI remains optional. This systematic review, according to the PRISMA 2020 checklist, aims to give an overview of the literature regarding the use of contrast in MRI in cervical cancer and provide more specific indications of when it may be helpful. Systematic searches on PubMed and Web Of Science (WOS) were performed, and 97 papers were included; 1 paper was added considering the references of included articles. From our literature review, it emerged that many papers about the use of contrast in cervical cancer are dated, especially about staging and detection of tumor recurrence. We did not find strong evidence suggesting that CE-MRI is helpful in any clinical setting for cervical cancer staging and detection of tumor recurrence. There is growing evidence that perfusion parameters and perfusion-derived radiomics models might have a role as prognostic and predictive biomarkers, but the lack of standardization and validation limits their use in a research setting.

Impact of DWI and ADC values in Ovarian-Adnexal Reporting and Data System (O-RADS) MRI score.

PURPOSE: Introduce DWI and quantitative ADC evaluation in O-RADS MRI system and observe how diagnostic performance changes. Assess its validity and reproducibility between readers with different experience in female pelvic imaging. Finally, evaluate any correlation between ADC value and histotype in malignant lesions. MATERIALS AND METHODS: In total, 173 patients with 213 indeterminate adnexal masses (AMs) on ultrasound were subjected to MRI examination, from which 140 patients with 172 AMs were included in the final analysis. Standardised MRI sequences were used, including DWI and DCE sequences. Two readers, blinded to histopathological data, retrospectively classified AMs according to the O-RADS MRI scoring system. A quantitative analysis method was applied by placing a ROI on the ADC maps obtained from single-exponential DWI sequences. AMs considered benign (O-RADS MRI score 2) were excluded from the ADC analysis. RESULTS: Excellent inter-reader agreement was found in the classification of lesions according to the O-RADS MRI score (K = 0.936; 95% CI). Two ROC curves were created to determine the optimal cut-off value for the ADC variable between O-RADS MRI categories 3-4 and 4-5, respectively, 1.411 × 10-3 mm2/sec and 0.849 × 10-3 mm2/sec. Based on these ADC values, 3/45 and 22/62 AMs were upgraded, respectively, to score 4 and 5, while 4/62 AMs were downgraded to score 3. ADC values correlated significantly with the ovarian carcinoma histotype (p value < 0.001). CONCLUSION: Our study demonstrates the prognostic potential of DWI and ADC values in the O-RADS MRI classification for better radiological standardisation and characterisation of AMs.

MRI- and Histologic-Molecular-Based Radio-Genomics Nomogram for Preoperative Assessment of Risk Classes in Endometrial Cancer.

High- and low-risk endometrial carcinoma (EC) differ in whether or not a lymphadenectomy is performed. We aimed to develop MRI-based radio-genomic models able to preoperatively assess lymph-vascular space invasion (LVSI) and discriminate between low- and high-risk EC according to the ESMO-ESGO-ESTRO 2020 guidelines, which include molecular risk classification proposed by "ProMisE". This is a retrospective, multicentric study that included 64 women with EC who underwent 3T-MRI before a hysterectomy. Radiomics features were extracted from T2WI images and apparent diffusion coefficient maps (ADC) after manual segmentation of the gross tumor volume. We constructed a multiple logistic regression approach from the most relevant radiomic features to distinguish between low- and high-risk classes under the ESMO-ESGO-ESTRO 2020 guidelines. A similar approach was taken to assess LVSI. Model diagnostic performance was assessed via ROC curves, accuracy, sensitivity and specificity on training and test sets. The LVSI predictive model used a single feature from ADC as a predictor; the risk class model used two features as predictors from both ADC and T2WI. The low-risk predictive model showed an AUC of 0.74 with an accuracy, sensitivity, and specificity of 0.74, 0.76, 0.94; the LVSI model showed an AUC of 0.59 with an accuracy, sensitivity, and specificity of 0.60, 0.50, 0.61. MRI-based radio-genomic models are useful for preoperative EC risk stratification and may facilitate therapeutic management.

CT imaging phenotypes linked to CA125 and HE4 biomarkers are highly predictive in discriminating between hereditary and sporadic ovarian cancer patients.

BACKGROUND: Hereditary ovarian cancers (HOC) represent about 23% of ovarian cancer (OC) cases: they are most frequently related to germline mutations in the BRCA genes. OBJECTIVE: We aimed to compare CA125/HE4 serum levels and Computed Tomography (CT) features at time of ovarian cancer (OC) diagnosis in two populations: BRCA mutant and BRCA wild-type (WT) OC, and to investigate the relationship between this laboratory and radiological biomarker and BRCA mutation status. METHODS: This retrospective study included 60 newly diagnosed OC patients with FIGO stage IIIC-IV disease, tested for BRCA1/2 germline mutation status of which preoperative CT scan and serum tumor marker assay were available. RESULTS: The median level of CA125 (708 U/mL) was significantly higher (p < 0.002) in BRCA1/2 mutated patients than in WT patients (176 U/mL), whereas the median level of HE4 (492 pmol/L) was significantly higher (p < 0.002) in WT than in BRCA-mutated patients (252 pmol/L). BRCA mutation carriers showed a higher incidence of bilateral ovarian masses (p = 0.0303) characterized by solid structures (p < 0.00001), higher peritoneal tumor load, macronodular implants >2 cm (p = 0.000099), increased frequency of lymphadenopathies (p = 0.019), and metastasis (p = 0.052) compared to patients with BRCA WT. CONCLUSIONS: Tumor markers and CT patterns may help in identifying BRCA mutation status in OC directing patients towards a personalized treatment.

CT-Based Radiomics and Deep Learning for BRCA Mutation and Progression-Free Survival Prediction in Ovarian Cancer Using a Multicentric Dataset.

PURPOSE: Build predictive radiomic models for early relapse and BRCA mutation based on a multicentric database of high-grade serous ovarian cancer (HGSOC) and validate them in a test set coming from different institutions. METHODS: Preoperative CTs of patients with HGSOC treated at four referral centers were retrospectively acquired and manually segmented. Hand-crafted features and deep radiomics features were extracted respectively by dedicated software (MODDICOM) and a dedicated convolutional neural network (CNN). Features were selected with and without prior harmonization (ComBat harmonization), and models were built using different machine learning algorithms, including clinical variables. RESULTS: We included 218 patients. Radiomic models showed low performance in predicting both BRCA mutation (AUC in test set between 0.46 and 0.59) and 1-year relapse (AUC in test set between 0.46 and 0.56); deep learning models demonstrated similar results (AUC in the test of 0.48 for BRCA and 0.50 for relapse). The inclusion of clinical variables improved the performance of the radiomic models to predict BRCA mutation (AUC in the test set of 0.74). CONCLUSIONS: In our multicentric dataset, representative of a real-life clinical scenario, we could not find a good radiomic predicting model for PFS and BRCA mutational status, with both traditional radiomics and deep learning, but the combination of clinical and radiomic models improved model performance for the prediction of BRCA mutation. These findings highlight the need for standardization through the whole radiomic pipelines and robust multicentric external validations of results.

MRI and Adenomyosis: What Can Radiologists Evaluate?

Uterine adenomyosis is a common benign condition defined by the presence of heterotopic endometrial glands and stroma within the myometrium. Adenomyosis is often related to infertility and other adverse pregnancy outcomes. Modern imaging techniques allow the non-invasive diagnosis of adenomyosis and, in this framework, Magnetic Resonance Imaging (MRI) has assumed a central role due to its high diagnostic accuracy in the detection of adenomyosis. Currently, there is still a lack of international consensus on adenomyosis diagnostic criteria and classification, despite the fact that an agreed reporting system would promote treatment outcomes and research. This review aims to emphasize the important contribution of MRI to the diagnosis of adenomyosis and to highlight how, thanks to the great tissue differentiation provided by MRI, it is possible to identify the main direct (cystic component) and indirect (junctional zone features) signs of adenomyosis and to distinguish its various subtypes according to different MRI-based classifications. We also explored the main MRI criteria to identify the most common pitfalls and differential diagnoses of adenomyosis, whose features should be considered to avoid misdiagnosis.

Intravoxel Incoherent Motion (IVIM) MR Quantification in Locally Advanced Cervical Cancer (LACC): Preliminary Study on Assessment of Tumor Aggressiveness and Response to Neoadjuvant Chemotherapy.

The aim of this study was to determine whether quantitative parameters obtained from intravoxel incoherent motion (IVIM) model at baseline magnetic resonance imaging (MRI) correlate with histological parameters and response to neoadjuvant chemotherapy in patients with locally advanced cervical cancer (LACC). METHODS: Twenty patients with biopsy-proven cervical cancer, staged as LACC on baseline MRI and addressed for neoadjuvant chemotherapy were enrolled. At treatment completion, tumor response was assessed with a follow-up MRI evaluated using the revised response evaluation criteria in solid tumors (RECIST; version 1.1), and patients were considered good responders (GR) if they had complete response or partial remission, and poor responders/non-responders (PR/NR) if they had stable or progressive disease. MRI protocol included conventional diffusion-weighted imaging (DWI; b = 0 and 1000 s/mm2) and IVIM acquisition using eight b-values (range: 0-1500 s/mm2). MR-images were analyzed using a dedicated software to obtain quantitative parameters: diffusion (D), pseudo-diffusion (D*), and perfusion fraction (fp) from the IVIM model; apparent diffusion coefficient (ADC) from conventional DWI. Histologic subtype, grading, and tumor-infiltrating lymphocytes (TILs) were assessed in each LACC. RESULTS: D showed significantly higher values in GR patients (p = 0.001) and in moderate/high TILs (p = 0.018). Fp showed significantly higher values in squamous cell tumors (p = 0.006). CONCLUSIONS: D extracted from the IVIM model could represent a promising tool to identify tumor aggressiveness and predict response to therapy.

Human placental microperfusion and microstructural assessment by intra-voxel incoherent motion MRI for discriminating intrauterine growth restriction: a pilot study.

OBJECTIVES: To evaluate the potential of Intravoxel Incoherent Motion (IVIM) Imaging in the quantification of placental micro-perfusion and microstructural features to identify and discriminate different forms of intrauterine growth restriction (IUGR) and normal fetuses pregnancies. METHODS: Small for gestational age SGA (n = 8), fetal growth restriction FGR (n = 10), and normal (n = 49) pregnancies were included in the study. Placental Magnetic Resonance Imaging (MRI) was performed at 1.5 T using a diffusion-weighted sequence with 10 b-values. IVIM fractional perfusion (fp), diffusion (D), and pseudodiffusion (D*) were evaluated on the fetal and maternal placental sides. Correlations between IVIM parameters, Gestational Age (GA), Birth Weight (BW), and the presence or absence of prenatal fetoplacental Doppler abnormalities at the US were investigated in SGA, FGR, and normal placentae. RESULTS: fp and D* of the placental fetal side discriminate between SGA and FGR (p = .021; p = .036, respectively), showing lower values in FGR. SGA showed an intermediate perfusion pattern in terms of fp and D* compared to FGR and normal controls. In the intrauterine growth restriction group (SGA + FGR), a significant positive correlation was found between fp and BW (p < .002) in the fetal placenta and a significant negative correlation was found between D and GA in both the fetal (p < .0009) and maternal (p < .006) placentas. CONCLUSIONS: Perfusion IVIM parameters fp and D* may be useful to discriminate different micro-vascularization patterns in IUGR being helpful to detect microvascular subtle impairment even in fetuses without any sign of US Doppler impairment in utero. Moreover, fp may predict fetuses' body weight in intrauterine growth restriction pregnancies. The diffusion IVIM parameter D may reflect more rapid microstructural rearrangement of the placenta due to aging processes in the IUGR group than in normal controls.

Can New ENZIAN Score 2020 Represent a Staging System Improving MRI Structured Report?

Structured reporting systems for endometriotic disease are gaining a central role in diagnostic imaging: our aim is to evaluate applicability and the feasibility of the recent ENZIAN score (2020) assessed by MRI. A total of 60 patients with suspected tubo-ovarian/deep endometriosis were retrospectively included in our study according to the following criteria: availability of MR examination; histopathological results from laparoscopic or surgical treatment; patients were not assuming estro-progestin or progestin therapy. Three different readers (radiologists with 2-, 5-, and 20-years of experience in pelvic imaging) have separately assigned a score according to the ENZIAN score (revised 2020) for all lesions detected by magnetic resonance imaging (MRI). Our study showed a high interobserver agreement and feasibility of the recent ENZIAN score applied to MRI; on the other hand, our experience highlighted some limitations mainly due to MRI's inability to assess tubal patency and mobility, as required by the recent score (2020). In view of the limitations which arose from our study, we propose a modified MRI-ENZIAN score that provides a complete structured reporting system, more suitable for MRI. The high interobserver agreement of the recent ENZIAN score applied to MRI confirms its validity as a complete staging system for endometriosis, offering a shared language between radiologists and surgeons.

Quantitative diffusion and perfusion MRI in the evaluation of endometrial cancer: validation with histopathological parameters.

OBJECTIVES: To investigate the role of quantitative Magnetic Resonance Imaging (MRI) in preoperative assessment of tumour aggressiveness in patients with endometrial cancer, correlating multiple parameters obtained from diffusion and dynamic contrast-enhanced (DCE) MR sequences with conventional histopathological prognostic factors and inflammatory tumour infiltrate. METHODS: Forty-four patients with biopsy-proven endometrial cancer underwent preoperative MR imaging at 3T scanner, including DCE imaging, diffusion-weighted imaging (DWI) and intravoxel incoherent motion imaging (IVIM). Images were analysed on dedicated post-processing workstations and quantitative parameters were extracted: Ktrans, Kep, Ve and AUC from the DCE; ADC from DWI; diffusion D, pseudo diffusion D*, perfusion fraction f from IVIM and tumour volume from DWI. The following histopathological data were obtained after surgery: histological type, grading (G), lympho-vascular invasion (LVI), lymph node status, FIGO stage and inflammatory infiltrate. RESULTS: ADC was significantly higher in endometrioid histology, G1-G2 (low grade), and stage IA. Significantly higher D* were found in endometrioid subptype, negative lymph nodes and stage IA. The absence of LVI is associated with higher f values. Ktrans and Ve values were significantly higher in low grade. Higher D*, f and AUC occur with the presence of chronic inflammatory cells, D * was also able to distinguish chronic from mixed type of inflammation. Larger volume was significantly correlated with the presence of mixed-type inflammation, LVI, positive lymph nodes and stage ≥IB. CONCLUSIONS: Quantitative biomarkers obtained from pre-operative DWI, IVIM and DCE-MR examination are an in vivo representation of the physiological and microstructural characteristics of endometrial carcinoma allowing to obtain the fundamental parameters for stratification into Risk Classes. ADVANCES IN KNOWLEDGE: Quantitative imaging biomarkers obtained from DWI, DCE and IVIM may improve preoperative prognostic stratification in patients with endometrial cancer leading to a more informed therapeutic choice.

Magnetic Resonance Imaging in endometriosis-associated pain.

INTRODUCTION: Endometriosis affects 10%-15% of women in reproductive age and may cause no-cyclic chronic pelvic pain, dysmenorrhea, dyspareunia, urinary tract symptoms, and it is frequently associated with infertility. The peak of incidence is between 24 and 29 years old and the clinical diagnosis of endometriosis is generally delayed by 6-7 years. Laparoscopy with surgical biopsies is the "gold standard" for the diagnosis of endometriosis, with histological verification of endometrial ectopic glands and/or stroma. However, nowadays two different non-invasive modalities are routinely used for a presumptive diagnosis: Transvaginal Ultrasound (TVUS) and Magnetic Resonance Imaging (MRI). EVIDENCE ACQUISITION: A structured search using PubMed was performed starting from October 2020 and including all relevant original and review articles published since 2000. The search used the following key word combinations: "endometriosis MRI" AND "DIE and MRI" (45); "MRI endometriosis and pelvic pain" OR "endometriosis and MRI technical development" (296). Ultimately, 87 articles were deemed relevant and used as the literature basis of this review. EVIDENCE SYNTHESIS: TVUS represents the first imaging approach for endometriosis showing a good diagnostic performance, but it is highly operator dependent. MRI is a second level examination often used in complex cases indeterminate after TVUS and in preoperative planning. MRI is considered the best imaging technique for mapping endometriosis since it provides a more reliable map of deep infiltrating endometriosis than physical examination and transvaginal ultrasound. We have analyzed and described the main forms of endometriosis: adnexal endometriosis, adenomyosis, peritoneal implants and deep infiltrating endometriosis, showing their appearance in the two imaging modalities. CONCLUSIONS: Endometriosis is one of the most common gynecologic disorders correlated to chronic pelvic pain whose treatment is still today complex and controversial. In this context, MRI has become an important additional non-invasive tool to investigate cases of chronic pelvic pain related to deep infiltrating endometriosis (DIE) with or without neural involvement.