ABSTRACT
BACKGROUND: Differential diagnosis between benign uterine smooth muscle tumors and malignant counterpart is challenging. We evaluated the accuracy of a clinical and ultrasound based algorithm in predicting mesenchimal uterine malignancies (MUMs), including smooth muscle tumors of uncertain malignant potential (STUMPs). METHODS: We report the twelve-months follow-up of an observational, prospective, single-centre study that included women with at least one myometrial lesion ≥3 cm on ultrasound examination. These patients were classified according to a three-class diagnostic algorithm, using symptoms and ultrasound features. "White" patients underwent annual telephone follow-up for 2 years, "Green" patients underwent a clinical and ultrasound follow-up at 6, 12 and 24 months and "Orange" patients underwent surgery. We further developed a risk class system to stratify the malignancy risk. FINDINGS: 2,268 women were included andtarget lesion was classified as benign in 2,158 (95.1%), as other malignancies in 58 (2.6%) an as mesenchymal uterine malignancies in 52 (2.3%) patients. At multivariable analysis, age (OR 1.05 (95% CI 1.03-1.07), tumor diameter >8 cm (OR 5.92 (95% CI 2.87-12.24), irregular margins (OR 2.34 (95% CI 1.09-4.98), color score=4 (OR 2.73 (95% CI 1.28-5.82), were identified as independent risk factors for malignancies, whereas acoustic shadow resulted in an independent protective factor (OR 0.39 (95% CI 0.19-0.82). The model, which included age as a continuous variable and lesion diameter as a dichotomized variable (cut-off 81 mm), provided the best AUC (0.87 (95% CI 0.82-0.91)). A risk class system was developed, and patients were classified as low-risk (predictive model value <0.39%: 0/606 malignancies, risk 0%), intermediate risk (predictive model value 0.40%-2.2%: 9/1,093 malignancies, risk 0.8%), high risk (predictive model value ≥2.3%: 43/566 malignancies, risk 7.6%). CONCLUSION: The preoperative three-class diagnostic algorithm and risk class system can stratify women according to risk of malignancy. Our findings, if confirmed in a multicentre study, will permit differentiation between benign and MUMs allowing a personalized clinical approach. FUNDING: Nothing to declare.
ABSTRACT
This book, based on the experience of a singlelarge referral center, presents the characteristic findingsobtained when using MR imaging and MR cholangiopancreatography(MRCP) to image the biliary tree and pancreatic ducts in a varietyof disease settings. An introductory chapter is devoted totechnical considerations, anatomy, and developmental anomalies.Subsequent chapters then present in detail the MR imaging and MRCPfindings observed in choledocholithiasis, inflammatory andneoplastic disorders of the bile ducts, acute and chronicpancreatitis (according to etiology), and different pancreaticneoplasms. Dynamic MRCP with secretin stimulation is alsoillustrated, documenting both normal and abnormal responses of thepancreatic duct system to secretin. Readers will find this book tobe an excellent aid to the interpretation of MR imaging and MRCPfindings in patients with biliary and pancreatic disease.