This study aimed to develop a diagnostic algorithm for preoperative differentiating uterine sarcoma from leiomyoma through a supervised machine-learning method using multi-parametric MRI. A total of 65 participants with 105 myometrial tumors were included: 84 benign and 21 malignant lesions (belonged to 51 and 14 patients, respectively; based on their postoperative tissue diagnosis). Multi-parametric MRI including T1-, T2-, and diffusion-weighted (DW) sequences with ADC-map, contrast-enhanced images, as well as MR spectroscopy (MRS), was performed for each lesion. Thirteen singular MRI features were extracted from the mentioned sequences. Various combination sets of selective features were fed into a machine classifier (coarse decision-tree) to predict malignant or benign tumors. The accuracy metrics of either singular or combinational models were assessed. Eventually, two diagnostic algorithms, a simple decision-tree and a complex one were proposed using the most accurate models. Our final simple decision-tree obtained accuracy = 96.2%, sensitivity = 100% and specificity = 95%; while the complex tree yielded accuracy, sensitivity and specificity of 100%. To summarise, the complex diagnostic algorithm, compared to the simple one, can differentiate tumors with equal sensitivity, but a higher specificity and accuracy. However, it needs some further time-consuming modalities and difficult imaging calculations. Trading-off costs and benefits in appropriate situations must be determinative.

Background HPV testing has been integrated in cervical cancer screening program. Patient-providers relationship is extremely important to improve cervical cancer screening outcomes. This qualitative study aims to understand HPV-positive women’s needs and preferences about HCPs and patient-provider communication based on their experiences of accessing primary and specialized care. Methods We conducted 40 semi-structured interviews with HPV-positive women. Recorded interviews transcribed and analyzed using conventional content analysis approach. Results The analysis of the data led to the extraction of three main categories, including: provider’s communication and counseling skills, commitment to professional principles, and knowledgeable and competent provider. Women needed understandable discussion about HPV, emotional support and acceptance, receiving HPV-related guidance and advice, and some considerations during clinical appointments. Women needed HCPs to treat them respectfully, gently and with non-judgmental attitude. “Precancerous” and “high-risk” words and watching colposcopy monitor during procedure had made women anxious. Weak referral system and limited interactions among gynecologists and other HCPs highlighted by participants. Conclusion The results of this study, based on the experiences and perceptions of HPV women receiving health care, contain messages and practical tips to healthcare providers at the primary and specialized levels of care to facilitate patient-provider communication around HPV. Providers need to approach the discussion of HPV with sensitivity and take individual needs and preferences into account to improve the HPV-positive women’s healthcare experience.

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