MRI prognosticators for adverse maternal and neonatal clinical outcome in patients at high risk for placenta accreta spectrum (PAS) disorders.

BACKGROUND: Placenta accreta spectrum (PAS) disorders may be associated with significant mortality and morbidity for both mother and fetus. PURPOSE/HYPOTHESIS: To identify MRI risk factors for poor peripartum outcome in gravid patients at risk for PAS. STUDY TYPE: Prospective. POPULATION: One hundred gravid women (mean age: 34.9 years) at third trimester, with placenta previa. FIELD STRENGTH/SEQUENCE: T2 -SSTSE (single-shot turbo spin echo), T2 -TSE, T1 -TSEFS (TSE images with fat-suppression) at 1.5T. ASSESSMENT: Fifteen MRI features considered indicative of PAS were recorded by three radiologists and were tested for any association with the following adverse peripartum maternal and neonatal events: increased operation time, profound blood loss, hysterectomy, bladder repair, ICU admission, prematurity, low birthweight, and 5-minute APGAR score <7. STATISTICAL TESTS: Kappa (K) coefficients were computed as a measure of agreement between intraoperative information/histology and MRI results as well as for interobserver agreement; chi-square and Fisher's exact tests were used to explore the association of the MRI signs with clinical complications. A score was calculated by adding all recorded MRI signs and its predictive ability was tested using receiver operating characteristic (ROC) analysis, against all complications, separately; odds ratios (ORs) for optimal cutoffs were determined with logistic regression analysis. RESULTS: There was excellent agreement (K >0.75, P < 0.001) between MRI and intraoperative findings for invasive placenta, bladder and parametrial involvement. Intraplacental T2 dark bands, myometrial disruption, uterine bulge, and hypervascularity at the utero-placental interface or parametrium, showed significant association (P < 0.005) with poor clinical outcome for both mother and fetus. The MRI score showed significant predictive ability for each adverse maternal event (area under the curve [AUC]: 0.85-0.97, P < 0.001). The presence of ≥3 MRI signs was the cutoff point for a complicated delivery (OR: 19.08, 95% confidence interval [CI]: 6.05-60.13) and ≥6 MRI signs was the cutoff point for massive bleeding (OR: 90.93, 95% CI: 11.3-729.23), hysterectomy (OR: 72.5, 95% CI: 17.9-293.7), or extensive bladder repair (OR: 58.74, 95% CI: 7.35-469.32). The MRI score was not significant for predicting adverse neonatal events including preterm delivery (P = 0.558), low birthweight (P = 0.097), and 5-minute Apgar score (P = 0.078). DATA CONCLUSION: Preoperative identification of specific MRI features may predict peripartum course in high-risk patients for PAS. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2019;50:602-618.

Role of one-pass breast lesion excision system in complete excision of high-risk breast lesions with atypia expressed as clusters of microcalcifications.

PURPOSE: To assess the role of the breast lesion excision system (BLES) in complete removal of clusters of microcalcifications found on mammogram proved histologically to be high-risk lesions with cell atypia. METHODS AND MATERIALS: Three hundred ninety-four consecutive women (mean age 58.5 years, range 39-78 years) with 400 clusters of suspicious microcalcifications underwent stereotactic biopsy using the intact BLES device between January 2014 and January 2016. All cases proved histologically to be high-risk lesions were subsequently assessed for complete removal. The underestimation rate was also assessed. RESULTS: Thirty-eight out of 400 (9.5%) lesions were high-risk lesions with atypia with mean size 7.63 mm (st. dev. = 4.03 mm) which was within the size that the BLES needle can excise (20 mm). Four (10.5%) papillomas with atypia, 14 (36.8%) cases with flat epithelial atypia (FEA), 10 (26.3%) cases with lobular intraepithelial neoplasia (LIN-LIN 1, LIN 2), 8 (21.2%) with atypical ductal hyperplasia (ADH) and 2 (5.3%) cases with mucocele-like lesions (MLL) with atypia were found. Twenty-nine out of 38 lesions had subsequent surgery. Complete excision was achieved in 23/29 lesions (79.3%). No underestimation was found. Two-year mammographic stability was found in all lesions. Non-parametric statistical analysis showed no other significant predictive factor for complete excision apart from the distance of the lesions from the specimen margins (p = 0.031 Mann-Whitney test). CONCLUSION: One-pass BLES intact biopsy technique is a safe method of complete removal of high-risk atypical lesions with high accuracy rates for certain histologies and could be potentially used as an alternative excision method to diagnostic surgery in selected cases. KEY POINTS: • Breast lesion excision system (BLES) is an image-guided biopsy technique that uses radiofrequency to remove an intact piece of tissue including the target breast neoplasm. • Breast lesion excision system (BLES) under stereotactic guidance is able to accurately biopsy high-risk breast lesions expressed mammographically as clusters of suspicious microcalcifications. • BLES under stereotactic guidance is an accurate technique for en bloc excision of selected cases of small clusters of suspicious microcalcifications proved to be high-risk lesions with histopathologically disease-free margins of excision.

Quantitative Diffusion-weighted Imaging of the Bone Marrow: An Adjunct Tool for the Diagnosis of a Diffuse MR Imaging Pattern in Patients with Multiple Myeloma.

Purpose To evaluate the apparent diffusion coefficients (ADCs) of magnetic resonance (MR) imaging patterns in the bone marrow of patients with multiple myeloma (MM) and to determine a threshold ADC that may help distinguish a diffuse from a normal pattern with high accuracy. Materials and Methods This prospective study was approved by the ethics review board, and informed consent was obtained. Ninety-nine patients with newly diagnosed, untreated MM and 16 healthy control subjects underwent spinal MR imaging including diffusion-weighted imaging, and bone marrow ADCs were calculated. Pattern assignment was based on visual assessment of conventional MR images. The Kruskal-Wallis H test, the Mann-Whitney test, and the one-way analysis of variance were used to compare ADCs between patient subsets and control subjects, and a receiver operating characteristic analysis was performed. Results Mean ADCs ± standard deviation in patients with MM for the normal, focal, and diffuse MR imaging patterns were 0.360 × 10-3 mm2/sec ± 0.110, 1.046 × 10-3 mm2/sec ± 0.232, and 0.770 × 10-3 mm2/sec ± 0.135, respectively. There were significant differences in ADCs between diffuse and normal (P < .001), diffuse and focal (P < .001), and focal and normal (P < .001) patterns. Patients with a diffuse pattern had more features of advanced disease, higher international staging system score, increased incidence of high-risk cytogenetics, and higher revised international staging system score. ADCs greater than 0.548 × 10-3 mm2/sec showed 100% sensitivity (26 of 26) and 98% specificity (48 of 49) for the diagnosis of a diffuse (vs normal) MR imaging pattern, whereas an ADC greater than 0.597 × 10-3 mm2/sec showed 96% sensitivity (25 of 26) and 100% specificity (49 of 49). Conclusion ADCs of MR imaging patterns in patients with MM differ significantly. A diffuse MR imaging pattern can be distinguished more objectively from a normal MR imaging pattern by adding quantitative diffusion-weighted imaging to standard MR imaging protocols. © RSNA, 2016 Online supplemental material is available for this article.

Dynamic contrast-enhanced magnetic resonance imaging parameters correlate with advanced revised-ISS and angiopoietin-1/angiopoietin-2 ratio in patients with multiple myeloma.

The aim of the study was to assess the value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in patients with newly diagnosed multiple myeloma (MM) who were treated with novel anti-myeloma agents. We studied 60 previously untreated MM patients at diagnosis, 14 with smoldering MM (SMM) and 5 with MGUS. All patients underwent MRI of the thoracolumbar spine and pelvis before the administration of any kind of therapy, and DCE-MRI was performed. The MRI perfusion parameters evaluated were wash-in (WIN), washout (WOUT), time-to-peak (TTPK), time-to-maximum slope (TMSP), and the WIN/TMSP ratio. The following serum levels of angiogenic cytokines were measured on the day of MRI: VEGF, angiogenin (Ang), angiopoietin-1 (Angp-1), and -2 (Angp-2). Symptomatic MM patients had increased WIN compared to SMM (p < 0.05) and MGUS patients (p = 0.001). TTPK was decreased, and WIN/TMSP was increased in both symptomatic and SMM patients compared to MGUS patients (p < 0.05). Symptomatic MM patients had decreased TMSP compared to MGUS patients. The Angp-1/Angp-2 ratio was reduced in symptomatic MM compared to SMM (p = 0.017) and MGUS patients (p < 0.001). TTPK correlated with Angp-1/Angp-2 ratio and importantly with R-ISS. Patients with R-ISS-3 had lower TTPK median value (23 s, range 18-29 s) compared to patients with R-ISS-2 (48 s, range 27-68 s) and patients with R-ISS-1 MM (54 s, range 42-76 s; p ANOVA = 0.01). A subset of patients with low TTPK (lower quartile) had shorter time to progression compared to all other patients. These data suggest that certain DCE-MRI parameters correlate with R-ISS and adverse prognostic features of angiogenesis, such as the ratio of Angp-1/Angp-2.

Endometrial vs. cervical cancer: development and pilot testing of a magnetic resonance imaging (MRI) scoring system for predicting tumor origin of uterine carcinomas of indeterminate histology.

PURPOSE: To report discriminant MRI features between cervical and endometrial carcinomas and to design an MRI- scoring system, with the potential to predict the origin of uterine cancer (cervix or endometrium) in histologically indeterminate cases. MATERIALS AND METHODS: Dedicated pelvic MRIs of 77 patients with uterine tumors involving both cervix and corpus were retrospectively analyzed by two experts in female imaging. Seven MRI tumor characteristics were statistically tested for their discriminant ability for tumor origin compared to final histology: tumor location, perfusion pattern, rim enhancement, depth of myometrial invasion, cervical stromal integrity, intracavitary mass, and retained endometrial secretions. Kappa values were estimated to assess the levels of inter-rater reliability. On the basis of positive likelihood ratio values, an MRI-score was assigned. RESULTS: K value was excellent for most of the imaging criteria. Using ROC curve analysis, the estimated optimal cut-off for the MRI-scoring system was 4 with 96.6% sensitivity and 100% specificity. Using a ≥4 cut-off for cervical cancers and <4 for endometrial cancers, 97.4% of the patients were correctly classified. 2/58 patients with cervical cancer had MRI score <4 and none of the patients with endometrial cancer had MRI score >4. The area under curve of the MRI-scoring system was 0.99 (95% CI 0.98-1.00). When the MRI-score was applied to 20/77 patients with indeterminate initial biopsy and to 5/26 surgically treated patients with erroneous pre-op histology, all cases were correctly classified. CONCLUSION: The produced MRI-scoring system may be a reliable problem-solving tool for the differential diagnosis of cervical vs. endometrial cancer in cases of equivocal histology.

"The emerging role of capivasertib in breast cancer".

Over 50% of breast tumors harbor alterations in one or more genes of the phosphatidylinositol 3-kinase (PI3K) pathway including PIK3CA mutations (31%), PTEN loss (34%), PTEN mutations (5%) and AKT1 mutations (3%). While PI3K and mTOR inhibitors are already approved in advanced breast cancer, AKT inhibitors have been recently developed as a new therapeutic approach. Capivasertib (AZD5363) is a novel, selective ATP-competitive pan-AKT kinase inhibitor that exerts similar activity against the three AKT isoforms, AKT1, AKT2, and AKT3. Preclinical studies demonstrated efficacy of capivasertib in breast cancer cell lines as a single agent or in combination with anti-HER2 agents and endocrine treatment, especially in tumors with PIK3CA or MTOR alterations. Phase I/II studies demonstrated greater efficacy when capivasertib was co-administered with paclitaxel, fulvestrant in hormone receptor (HR)-positive, HER2-negative breast cancer or olaparib. The recommended phase II dose of capivasertib as monotherapy was 480 mg bid on a 4-days-on, 3-days-off dosing schedule. Toxicity profile proved to be manageable with hyperglycemia (20-24%), diarrhea (14-17%) and maculopapular rash (11-16%) being the most common grade ≥3 adverse events. Ongoing Phase III trials of capivasertib in combination with fulvestrant (CAPItello-291), CDK4/6 inhibitor palbociclib (CAPItello-292) and paclitaxel (CAPItello- 290) will better clarify the therapeutic role of capivasertib in breast cancer.

Comparison between 1.5-T and 3.0-T MRI for the diagnosis of placenta accreta spectrum disorders.

PURPOSE: Accurate antenatal diagnosis of placenta accreta spectrum (PAS) is important for optimal management. The purpose of this study was to compare the respective capabilities of 1.5-T and 3.0-T MRI in the diagnosis of PAS. MATERIALS AND METHODS: Between March 2016-March 2021, 190 pregnant women at high risk for PAS underwent dedicated prenatal MRI with either 1.5-T or 3.0-T units at a tertiary imaging center. Cesarian section and MRI were performed less than 6 weeks from each other. Prospectively collected data were evaluated by two experienced genitourinary radiologists for presence and extent of PAS. A comparative study was designed to investigate differences in predictive ability between 1.5-T and 3.0-T MRI groups. Sensitivity, specificity, accuracy, negative and positive prognostic values relative to intraoperative/histological findings, were computed for both groups and were compared with chi-square (χ 2) test. Interobserver agreement was estimated using Kappa test. RESULTS: One hundred-eighty-two gravid women were included in the study; of these, 91/182 (50%) women were evaluated with 1.5-T (mean age, 35 ± 5.1 [SD] years; mean gestational age: 32.5 weeks) and 91/182 (50%) with 3.0-T MRI (mean age, 34.9 ± 4.9 [SD] years; mean gestational age, 32.1 weeks). 1.5-T MRI yielded 95.7% sensitivity (95% CI: 87.8-99.1) and 81.8% specificity (95% CI: 59.8) and 3.0-T MRI 93.8% sensitivity (95% CI: 86.0-97.9) and 83.3% specificity (95% CI: 48.2-97.7) for PAS identification, with no differences between the two groups (P = 0.725 and P >0.999, respectively). MRI showed excellent predictive ability for detecting extrauterine placental spread with 100% sensitivity (95% CI: 89.4-100.0), 96.7% specificity (95% CI: 88.1-99.6) for 1.5-T and 97% sensitivity (95% CI: 84.2-99.9), 96.7% specificity (95% CI: 88.1-99.6) for 3.0-T without differences between the two groups (P > 0.999). Interobserver agreement was excellent for both groups. The most frequently detected MRI signs of PAS for both 1.5-T and 3.0-T groups were placental heterogeneity (n = 85, 93.5% vs. n = 90, 98.9%; P = 0.413), and intraplacental fetal vessels (n = 64, 70.3% vs. n = 65, 71.4%; P = 0.870). CONCLUSION: This study suggests that 3.0-T MRI and 1.5-T MRI are equivalent for the diagnosis of PAS.

Αdnexal cystic lymphangiomas in patients with massive leiomyomatous uterus: a not so uncommon finding on pelvic MRI.

PURPOSE: To investigate any association between the presence of an adnexal cystic lymphangioma (ACL) and an enlarged leiomyomatous uterus. METHODS: A retrospective observational study was conducted by two expert radiologists using a 10-year MRI database (2008-2018); 85 patients (mean age: 45.5 years ± 10.9) were considered eligible due to the presence of a single (n = 31) or multiple (n = 54) leiomyomas causing distortion of the uterine contour and uterine enlargement. The association of specific leiomyoma features (longest diameter (Dmax), location, number) and uterine volume with the presence of ACL was statistically tested. Diagnosis of ACL was based on typical imaging features (n = 14) and intraoperative/histological findings (n = 3). RESULTS: ACL (unilateral = 9, bilateral = 8) was recorded in 17/85 (20%) of patients; it was more frequently observed when the largest leiomyoma was located in the uterine fundus (33.3%). Patients with ACL had significantly more leiomyomas (median: 5 vs. 2, p = 0.043), greater Dmax of largest leiomyoma (median: 13.3 vs. 7.2 cm, p < 0.001), and larger uterine volumes (median: 676.7 vs. 223.1 cm3, p < 0.001) compared to patients without ACL. ROC curve analysis for a number of leiomyomas showed that the optimal cut-off for the prediction of ACL was the presence of 5 leiomyomas with 53.8% sensitivity and 84% specificity (AUC = 0.65, 95% CI 0.51-0.83, p = 0.049), Dmax of largest leiomyoma 9.1 cm with 76.5% sensitivity and 77.9% specificity (AUC = 0.83, 95% CI 0.73-0.94, p < 0.001), and uterine volume 311 cm3 with 71% sensitivity and 75% specificity (AUC = 0.79, 95% CI 0.66-0.92, p < 0.001). CONCLUSIONS: The presence of ACL is significantly associated with number of leiomyomas, Dmax of largest leiomyoma, and uterine volume; prospective evaluation of our results is needed to investigate its clinical significance.

Performance of breast lesion excision system (BLES) in complete removal of papillomas presented mammographically as groups of calcifications.

OBJECTIVES: To retrospectively assess the stereotactic one-pass BLES performance in excision of small groups of calcifications seen on mammogram that proved to be papillomas. METHODS: Between January 2014 and January 2016, 37/400 cases (9.2%) of stereotactic BLES biopsies performed in our department due to suspicious calcifications proved to be papillomas. Lesions with atypia underwent surgical removal and lesions with no atypia were followed up for 2 years. BLES and surgical histology results, radiological removal and 2-years stability were statistically analysed to assess BLES performance in biopsy and excision of papillomas. RESULTS: The mean mammographic size of papillomas was 6.54 mm (st dev = 3.85, range 2 mm-17 mm) and within the size excised by the BLES needle (20 mm). 4/37 cases (10.8%) showed atypia. BLES excision was achieved in 29/37 cases (78.4%); radiological removal based on post BLES mammogram was achieved in 25/29 cases (86.2%). In the remaining 8/37 cases the papillomas were seen at the ink of the specimens' margins; 3/8 cases showed residual calcifications on post-BLES mammogram. The BLES histology result of removal and the mammographic size of the papillomas were found to be statistically significant predictive factors of excision (p < 0,001, Fisher's exact test, Mann Whitney test). Follow up mammograms showed no change for a period of 2 years. CONCLUSION: BLES is a safe and accurate technique to biopsy papillomas with high success rates of excision which could potentially minimize the need of subsequent radiological or surgical excision.

MR imaging features and tumor biomarkers of screen-detected and non-screen detected breast cancers: preliminary results of a comparative study.

PURPOSE: To investigate differences in clinical features, MRI findings and tumor biomarker characteristics in screen-detected (SCD) and non-screendetected (NSCD) cancers. MATERIAL AND METHODS: A total of 62 women (mean age, 48.4 years; range, 33-68 years) with biopsy confirmed breast cancer who underwent preoperative breast MRI were retrospectively evaluated by two expert radiologists. The women were divided into two groups according to the mode of cancer detection (Group A: screen- detected, Group B: non-screen/symptomatic cancer) and clinical, histopathological, MRI characteristics and biomarker features in each group were evaluated. RESULTS: NSCD tumors had significantly greater size (3.5 cm vs. 2.1 cm) and Ki-67 expression (68.4% vs. 41.7%) in comparison to SCD cancers. NSCD cancers were less likely to have strongly positive progesterone receptors (Pr) and more likely to have Ki-67 > 15% or positive nodal status (47.4% vs. 8.3%). Increased breast density (ACR C and D: 78.9% vs. 50%ACR A and B) and intense background parenchymal enhancement (BPE, moderate/marked: 42.1% vs. 8.3% minimal/mild) were significantly more frequent in NSCD cases. CONCLUSION: NSCD cancers had higher prevalence of poor prognostic characteristics in comparison to SCD tumors, including larger tumor size, higher Ki-67 index, and positive nodes. Increased fibroglandular tissue and intense BPE were both strongly associated with NSCD cancers, supporting their use as potential MR biomarkers in breast cancer risk models.

Correlation Between Contrast-enhanced Ultrasound Characteristics (Qualitative and Quantitative) and Pathological Prognostic Factors in Breast Cancer.

BACKGROUND/AIM: Little is known about the correlation between contrast-enhanced ultrasound (CEUS) characteristics and pathological prognostic factors in breast cancer. The aim of this study was to explore the correlation between CEUS characteristics and pathological prognostic factors. PATIENTS AND METHODS: A retrospective study with 34 malignant breast lesions was conducted. CEUS characteristics included qualitative characteristics (e.g. lesion's enhancement degree and order, internal lesion homogeneity etc.) and quantitative characteristics (e.g. peak intensity, time to peak etc.). Also, pathological prognostic factors were included (e.g. tumor grade, estrogen receptor status etc.). RESULTS: Blurred lesion margins were observed more often in tumors of high histological grade (p=0.01) and in estrogen receptor-negative tumors (p=0.049). Furthermore, perilesional enhancement was associated with positive Ki-67 expression (p=0.049), while heterogeneous internal sentinel lymph node enhancement was associated with malignant infiltration of the node (p=0.002). CONCLUSION: CEUS has the potential to provide a prevision of pathological prognostic factors in malignant breast lesions, helping in the better early patient management.

Breast tumor malignancy modelling using evolutionary neural logic networks.

The present work proposes a computer assisted methodology for the effective modelling of the diagnostic decision for breast tumor malignancy. The suggested approach is based on innovative hybrid computational intelligence algorithms properly applied in related cytological data contained in past medical records. The experimental data used in this study were gathered in the early 1990s in the University of Wisconsin, based in post diagnostic cytological observations performed by expert medical staff. Data were properly encoded in a computer database and accordingly, various alternative modelling techniques were applied on them, in an attempt to form diagnostic models. Previous methods included standard optimisation techniques, as well as artificial intelligence approaches, in a way that a variety of related publications exists in modern literature on the subject. In this report, a hybrid computational intelligence approach is suggested, which effectively combines modern mathematical logic principles, neural computation and genetic programming in an effective manner. The approach proves promising either in terms of diagnostic accuracy and generalization capabilities, or in terms of comprehensibility and practical importance for the related medical staff.

Computational intelligence for the detection and classification of malignant lesions in screening mammography.

This report deals with the discussion of the findings obtained from the application of two computational intelligence methodologies for the detection of microcalcifications in screening mammography data. Genetic programming and inductive machine learning have been applied, in order to produce meaningful diagnostic rules for the medical staff. The data used in the experiments correspond to information acquired from two images of each breast of the patient, along with some associated patient information such as the age at time of study. Similar datasets have been previously used in an attempt to facilitate the development of computer algorithms to aid screening. Experienced screening radiologists have double-read the screening mammograms, they have weighted the malignancy ratings and averaged out the levels of suspiciousness assigned to each finding in the screenings. The diagnostic rules which were obtained from both genetic programming and machine learning have been evaluated in detail and then analyzed and discussed by collaborative medical experts, in parallel to findings from related literature. Results seem encouraging for further use and analysis by medical staff specializing in screening mammography.