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OBJECTIVES: The objective of this multicenter retrospective study aimed to evaluate the association of clinical variables and the incidence of ovarian cancer in patients with BRCA 1-2 mutation carriers who underwent risk-reducing salpingo-oophorectomy (RRSO). DESIGN: Patients with a pathogenic mutation of BRCA 1-2 genes and with no evidence of disease are considered eligible. The exclusion criterion was the refusal to undergo the surgery. The retrospective study included all RRSO performed from May 2015 to April 2022 in the three gynecological Institutions of Southern Italy for were included in this retrospective study. PARTICIPANTS/MATERIALS, SETTING, METHODS: Age, menarche age, BMI, menopause at time of RRSO, breast cancer first- and second-degree relatives, ovarian cancer first- and second-degree relatives, estroprogestin use, pregnancy normal full-term delivery, history of endometriosis, previous breast cancer and histologic type, previous abdominal/pelvic surgery, BRCA 1 or BRCA 2 status, preoperative serum CA-125 levels (IU/mL), age at time of RRSO and histological analysis were collected. RESULTS: 184 were recruited. One was excluded. To assess cancer risk, the outcome variable was classified into three classes: no event, cancer, and other conditions excluding cancer. 14 women presented ovarian cancer and tubal intraepithelial carcinoma (STIC) on histopathologic final report. Ovarian cancer was found in 8 patients, whereas the presence of STIC was found in 6 of them. LIMITATIONS: The low incidence of patients diagnosed with ovarian cancer or STIC compared with the total number of patients undergoing RRSO is a potential bias. CONCLUSIONS: Our study did not demonstrate a correlation between clinical features and the occurrence of precancerous or cancerous lesions in BRCA mutation carrier patients.
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Proteína BRCA1 , Proteína BRCA2 , Neoplasias da Mama , Neoplasias Ovarianas , Feminino , Humanos , Neoplasias da Mama/epidemiologia , Neoplasias da Mama/genética , Neoplasias da Mama/patologia , Causalidade , Predisposição Genética para Doença , Mutação , Neoplasias Ovarianas/epidemiologia , Neoplasias Ovarianas/genética , Neoplasias Ovarianas/patologia , Ovariectomia , Estudos Retrospectivos , Proteína BRCA1/genética , Proteína BRCA2/genéticaRESUMO
PURPOSE: Concurrent cisplatin-based chemotherapy and radiotherapy (CCRT) plus brachytherapy is the standard treatment for locally advanced cervical cancer (LACC). Platinum-based neoadjuvant chemotherapy (NACT) followed by radical hysterectomy is an alternative for patients with stage IB2-IIB disease. Therefore, the correct pre-treatment staging is essential to the proper management of this disease. Pelvic magnetic resonance imaging (MRI) is the gold standard examination but studies about MRI accuracy in the detection of lymph node metastasis (LNM) in LACC patients show conflicting data. Machine learning (ML) is emerging as a promising tool for unraveling complex non-linear relationships between patient attributes that cannot be solved by traditional statistical methods. Here we investigated whether ML might improve the accuracy of MRI in the detection of LNM in LACC patients. METHODS: We analyzed retrospectively LACC patients who underwent NACT and radical hysterectomy from 2015 to 2020. Demographic, clinical and MRI characteristics before and after NACT were collected, as well as information about post-surgery histopathology. Random features elimination wrapper was used to determine an attribute core set. A ML algorithm, namely Extreme Gradient Boosting (XGBoost) was trained and validated with tenfold cross-validation. The performances of the algorithm were assessed. RESULTS: Our analysis included n.92 patients. FIGO stage was IB2 in n.4/92 (4.3%), IB3 in n.42/92 (45%), IIA1 in n.1/92 (1.1%), IIA2 in n.16/92 (17.4%) and IIB in n.29/92 (31.5%). Despite detected neither at pre-treatment and post-treatment MRI in any patients, LNM occurred in n.16/92 (17%) patients. The attribute core set used to train ML algorithms included grading, histotypes, age, parity, largest diameter of lesion at either pre- and post-treatment MRI, presence/absence of fornix infiltration at pre-treatment MRI and FIGO stage. XGBoost showed a good performance (accuracy 89%, precision 83%, recall 78%, AUROC 0.79). CONCLUSIONS: We developed an accurate model to predict LNM in LACC patients in NACT, based on a ML algorithm requiring few easy-to-collect attributes.
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Carcinoma de Células Escamosas , Neoplasias do Colo do Útero , Feminino , Humanos , Terapia Neoadjuvante/métodos , Carcinoma de Células Escamosas/patologia , Neoplasias do Colo do Útero/diagnóstico por imagem , Neoplasias do Colo do Útero/tratamento farmacológico , Estudos Retrospectivos , Metástase Linfática/diagnóstico por imagem , Excisão de Linfonodo , Protocolos de Quimioterapia Combinada Antineoplásica/uso terapêutico , Quimioterapia Adjuvante/métodos , Estadiamento de Neoplasias , Histerectomia/métodosRESUMO
Digital Breast Tomosynthesis (DBT) is a cutting-edge technology introduced in recent years as an in-depth analysis of breast cancer diagnostics. Compared with 2D Full-Field Digital Mammography, DBT has demonstrated greater sensitivity and specificity in detecting breast tumors. This work aims to quantitatively evaluate the impact of the systematic introduction of DBT in terms of Biopsy Rate and Positive Predictive Values for the number of biopsies performed (PPV-3). For this purpose, we collected 69,384 mammograms and 7894 biopsies, of which 6484 were Core Biopsies and 1410 were stereotactic Vacuum-assisted Breast Biopsies (VABBs), performed on female patients afferent to the Breast Unit of the Istituto Tumori "Giovanni Paolo II" of Bari from 2012 to 2021, thus, in the period before, during and after the systematic introduction of DBT. Linear regression analysis was then implemented to investigate how the Biopsy Rate had changed over the 10 year screening. The next step was to focus on VABBs, which were generally performed during in-depth examinations of mammogram detected lesions. Finally, three radiologists from the institute's Breast Unit underwent a comparative study to ascertain their performances in terms of breast cancer detection rates before and after the introduction of DBT. As a result, it was demonstrated that both the overall Biopsy Rate and the VABBs Biopsy Rate significantly decreased following the introduction of DBT, with the diagnosis of an equal number of tumors. Besides, no statistically significant differences were observed among the three operators evaluated. In conclusion, this work highlights how the systematic introduction of DBT has significantly impacted the breast cancer diagnostic procedure, by improving the diagnostic quality and thereby reducing needless biopsies, resulting in a consequent reduction in costs.
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Neoplasias da Mama , Detecção Precoce de Câncer , Feminino , Humanos , Detecção Precoce de Câncer/métodos , Estudos Retrospectivos , Mama/diagnóstico por imagem , Mamografia/métodos , Neoplasias da Mama/patologia , Biópsia Guiada por Imagem/métodos , Biópsia com Agulha de Grande CalibreRESUMO
Oocyte donation (OD) has greatly improved over the last three decades, becoming a preferred practice of assisted reproductive technology (ART) for infertile women wishing for motherhood. Through OD, indeed, it has become possible to overcome the physiological limitation due to the ovarian reserve (OR) exhaustion as well as the poor gamete reliability which parallels the increasing age of women. However, despite the great scientific contribution related to the success of OD in the field of infertility, this practice seems to be associated with a higher rate of major risky events during pregnancy as recurrent miscarriage, infections and placental diseases including gestational hypertension, pre-eclampsia and post-partum hemorrhage, as well as several maternal-fetal complications due to gametes manipulation and immune system interaction. Here, we will revisit this questioned topic since a number of studies in the medical literature focus on the successful aspects of the OD procedure in terms of pregnancy rate without, however, neglecting the risks and complications potentially linked to external manipulation or heterologous implantation.
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All cancers develop as a result of mutations in genes. DNA damage induces genomic instability and subsequently increases susceptibility to tumorigenesis. Women who carry mutations of BRCA 1 and BRCA2 genes have an augmented risk of breast and ovarian cancer and a markedly augmented probability of dying because of cancer compared to the general population. As a result, international guidelines recommend that all BRCA1\2 mutation carriers be offered risk-reducing bilateral salpingo-oophorectomy at an early age to reduce the risk of cancer and decrease the mortality rate of this high-risk population. NCCN guidelines recommend risk-reducing bilateral salpingo-oophorectomy in pre-menopausal women, between 35-40 years in BRCA1 mutation carriers and between 40-45 years in BRCA2 mutation carriers. Unfortunately, the well-documented reduction of cancer risk is counterbalanced by early sterility and premature ovarian failure with an early onset of secondary menopausal syndromes such as neuromotor, cardiovascular, cognitive and urogenital deficiency. Hormonal replacement therapy significantly compensates for hormonal deprivation and counteracts menopausal syndrome morbidity and mortality; however, some data suggest a possible correlation between hormonal medications and cancer risk, especially in BRCA1\2 carriers who undergo long-term regimens. Conversely, short-term treatment before the age of natural menopause does not appear to increase the cancer risk in BRCA1 mutation carriers without a personal history of breast cancer after prophylactic surgery. Few data are available on BRCA2 mutation carriers and more well-designed studies are needed. In conclusion, clinicians should propose short-term hormone replacement therapy to BRCA 1 carriers to counteract hormonal deprivation; personalized counselling should be offered to BRCA2 mutation carriers for a balance between the risks and benefits of the treatment.
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Neoplasias da Mama , Neoplasias Ovarianas , Humanos , Feminino , Terapia de Reposição Hormonal/efeitos adversos , Salpingo-Ooforectomia , Proteína BRCA1/genética , Genes BRCA2 , Menopausa , Neoplasias da Mama/genética , Neoplasias da Mama/prevenção & controle , Mutação , Neoplasias Ovarianas/genética , Neoplasias Ovarianas/prevenção & controle , Ovariectomia , Proteína BRCA2/genética , Predisposição Genética para DoençaRESUMO
In a growing number of social and clinical scenarios, machine learning (ML) is emerging as a promising tool for implementing complex multi-parametric decision-making algorithms. Regarding ovarian cancer (OC), despite the standardization of features that can support the discrimination of ovarian masses into benign and malignant, there is a lack of accurate predictive modeling based on ultrasound (US) examination for progression-free survival (PFS). This retrospective observational study analyzed patients with epithelial ovarian cancer (EOC) who were followed in a tertiary center from 2018 to 2019. Demographic features, clinical characteristics, information about the surgery and post-surgery histopathology were collected. Additionally, we recorded data about US examinations according to the International Ovarian Tumor Analysis (IOTA) classification. Our study aimed to realize a tool to predict 12 month PFS in patients with OC based on a ML algorithm applied to gynecological ultrasound assessment. Proper feature selection was used to determine an attribute core set. Three different machine learning algorithms, namely Logistic Regression (LR), Random Forest (RFF), and K-nearest neighbors (KNN), were then trained and validated with five-fold cross-validation to predict 12 month PFS. Our analysis included n. 64 patients and 12 month PFS was achieved by 46/64 patients (71.9%). The attribute core set used to train machine learning algorithms included age, menopause, CA-125 value, histotype, FIGO stage and US characteristics, such as major lesion diameter, side, echogenicity, color score, major solid component diameter, presence of carcinosis. RFF showed the best performance (accuracy 93.7%, precision 90%, recall 90%, area under receiver operating characteristic curve (AUROC) 0.92). We developed an accurate ML model to predict 12 month PFS.
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Aprendizado de Máquina , Neoplasias Ovarianas , Humanos , Feminino , Carcinoma Epitelial do Ovário/diagnóstico por imagem , Intervalo Livre de Progressão , Neoplasias Ovarianas/diagnóstico por imagem , Neoplasias Ovarianas/cirurgia , Neoplasias Ovarianas/patologia , UltrassonografiaRESUMO
Ovarian cancer is the seventh most common cancer in women in the world, with an estimated worldwide mortality of over 207'000 women every year. This cancer, due to the current lack of adequate screening techniques, is commonly diagnosed late and has a poor prognosis. The oral contraceptive pill is considered the most effective prevention strategy for ovarian cancer in the general population, being associated with a decreased incidence while also having a substantial positive impact on the mortality rate, which is reduced by up to 50%. BRCA1 and BRCA2 germline mutated women have an augmented risk of ovary and breast cancer: despite international guidelines that consider prophylactic surgery as the gold standard for ovarian cancer prevention, there are currently no effective non-invasive preventive methods. In BRCA1\2 mutated patients, clinicians should weigh the benefits of contraceptive pills against the risk of long-term thromboembolic side effects and hormonal malignancies such as breast and cervical cancer. A multidisciplinary team should counsel patients on the most appropriate risk-reduction strategy tailored to their needs and expectations, proposing the oral contraceptive pill to selected patients after balancing the risks of adverse effects and the benefits on both contraception and chemoprevention.
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Proteína BRCA1 , Proteína BRCA2 , Neoplasias Ovarianas , Humanos , Feminino , Neoplasias Ovarianas/prevenção & controle , Neoplasias Ovarianas/genética , Proteína BRCA2/genética , Proteína BRCA1/genética , Anticoncepção/métodos , Quimioprevenção/métodos , Anticoncepcionais Orais/uso terapêuticoRESUMO
BRCA1 and BRCA2 mutations are responsible for a higher incidence of breast and ovarian cancer (from 55% up to 70% vs. 12% in the general population). If their functions have been widely investigated in the onset of these malignancies, still little is known about their role in fertility impairment. Cancer patients treated with antineoplastic drugs can be susceptible to their gonadotoxicity and, in women, some of them can induce apoptotic program in premature ovarian follicles, progressive depletion of ovarian reserve and, consequently, cancer treatment-related infertility (CTRI). BRCA variants seem to be associated with early infertility, thus accelerating treatment impairment of ovaries and making women face the concrete possibility of an early pregnancy. In this regard, fertility preservation (FP) procedures should be discussed in oncofertility counseling-from the first line of prevention with risk-reducing salpingo-oophorectomy (RRSO) to the new experimental ovarian stem cells (OSCs) model as a new way to obtain in vitro-differentiated oocytes, several techniques may represent a valid option to BRCA-mutated patients. In this review, we revisit knowledge about BRCA involvement in lower fertility, pregnancy feasibility, and the fertility preservation (FP) options available.
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BACKGROUND: Accurate characterization of newly diagnosed a solid adnexal lesion is a key step in defining the most appropriate therapeutic approach. Despite guidance from the International Ovarian Tumor Analyzes Panel, the evaluation of these lesions can be challenging. Recent studies have demonstrated how machine learning techniques can be applied to clinical data to solve this diagnostic problem. However, ML models can often consider as black-boxes due to the difficulty of understanding the decision-making process used by the algorithm to obtain a specific result. AIMS: For this purpose, we propose an Explainable Artificial Intelligence model trained on clinical characteristics and qualitative ultrasound indicators to predict solid adnexal masses diagnosis. MATERIALS & METHODS: Since the diagnostic task was a three-class problem (benign tumor, invasive cancer, or ovarian metastasis), we proposed a waterfall classification model: a first model was trained and validated to discriminate benign versus malignant, a second model was trained to distinguish nonmetastatic versus metastatic malignant lesion which occurs when a patient is predicted to be malignant by the first model. Firstly, a stepwise feature selection procedure was implemented. The classification performances were validated on Leave One Out scheme. RESULTS: The accuracy of the three-class model reaches an overall accuracy of 86.36%, and the precision per-class of the benign, nonmetastatic malignant, and metastatic malignant classes were 86.96%, 87.27%, and 77.78%, respectively. DISCUSSION: SHapley Additive exPlanations were performed to visually show how the machine learning model made a specific decision. For each patient, the SHAP values expressed how each characteristic contributed to the classification result. Such information represents an added value for the clinical usability of a diagnostic system. CONCLUSIONS: This is the first work that attempts to design an explainable machine-learning tool for the histological diagnosis of solid masses of the ovary.
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Doenças dos Anexos , Aprendizado de Máquina , Neoplasias Ovarianas , Ultrassonografia , Humanos , Feminino , Ultrassonografia/métodos , Neoplasias Ovarianas/diagnóstico por imagem , Neoplasias Ovarianas/patologia , Neoplasias Ovarianas/diagnóstico , Pessoa de Meia-Idade , Adulto , Doenças dos Anexos/diagnóstico por imagem , Doenças dos Anexos/patologia , Idoso , Algoritmos , Diagnóstico DiferencialRESUMO
Background: Arteriovenous malformation of umbilical cord is an extremely rare congenital malformation. Causes of this condition are unknown. AVM of umbilical cord can cause significant complications in the developing fetus. Methods: We report our management of the case with accurate ultrasound study that could improve and facilitate the approach to this pathology due to the lack of literature and with an overview of the available literature. Results: There are only two cases of umbilical AVM diagnosed in the prenatal period with associated pathology. The mainstay of prenatal detection is the accurate study of umbilical cord also even if it is not requested from the actual guide lines in a way to improve the perinatal morbidity and mortality.
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Leiomyosarcoma (LMS) is a rare type of mesenchymal tumor. Suspecting LMS before surgery is crucial for proper patient management. Ultrasound is the primary method for assessing myometrial lesions. The overlapping of clinical, laboratory, as well as ultrasound features between fibroids and LMS makes differential diagnosis difficult. We report our single-center experience in ultrasound imaging assessment of LMS patients, highlighting that misleading findings such as shadowing and absent or minimal vascularization may also occur in LMS. To avoid mistakes, a comprehensive evaluation of potentially overlapping ultrasound features is necessary in preoperative ultrasound evaluations of all myometrial tumors.
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Women with a BRCA mutation have an increased risk of developing breast and ovarian cancer. Bilateral salpingo-oophorectomy is the only effective strategy to reduce this risk. Risk-reducing bilateral salpingo-oophorectomy (RRSO) is recommended between the ages of 35 and 40 for women carriers of BRCA1 and between the ages of 40 and 45 for women carriers of BRCA1 and BRCA2 mutations. Most women undergo this procedure prior to their natural menopause subsequently developing an anticipated lack of hormones. This condition affects the quality of life and longevity, while it is more pronounced in women carrying a BRCA1 mutation compared to BRCA2 because they are likely to have surgery earlier. Hormone replacement therapy (HRT) is the only strategy able to significantly compensate for the loss of ovarian hormone production and counteract menopausal symptoms. There is strong evidence that short-term HRT use does not increase the risk of breast cancer among women with a BRCA1 mutation. Few data are available on BRCA2 mutation carriers. Therefore, BRCA mutation carriers require careful counseling about the outcomes of their RRSO, including menopausal symptoms and/or the fear associated with HRT use.
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Neoplasias da Mama , Neoplasias Ovarianas , Feminino , Humanos , Adulto , Pessoa de Meia-Idade , Qualidade de Vida , Genes BRCA2 , Mutação , Terapia de Reposição Hormonal/efeitos adversos , Salpingo-Ooforectomia/métodos , Neoplasias da Mama/genética , Neoplasias da Mama/prevenção & controle , Neoplasias Ovarianas/genética , Neoplasias Ovarianas/prevenção & controle , Ovariectomia , Predisposição Genética para DoençaRESUMO
Introduction: It has been estimated that 19,880 new cases of ovarian cancer had been diagnosed in 2022. Most epithelial ovarian cancer are sporadic, while in 15%-25% of cases, there is evidence of a familial or inherited component. Approximately 20%-25% of high-grade serous carcinoma cases are caused by germline mutations in the BRCA1 and BRCA2 genes. However, owing to a lack of effective early detection methods, women with BRCA mutations are recommended to undergo bilateral risk-reducing salpingo-oophorectomy (RRSO) after childbearing. Determining the right timing for this procedure is a difficult decision. It is crucial to find a clinical signature to identify high-risk BRCA-mutated patients and determine the appropriate timing for performing RRSO. Methods: In this work, clinical data referred to a cohort of 184 patients, of whom 7.6% were affected by adnexal tumors including invasive carcinomas and intraepithelial lesions after RSSO has been analyzed. Thus, we proposed an explainable machine learning (ML) ensemble approach using clinical data commonly collected in clinical practice to early identify BRCA-mutated patients at high risk of ovarian cancer and consequentially establish the correct timing for RRSO. Results: The ensemble model was able to handle imbalanced data achieving an accuracy value of 83.2%, a specificity value of 85.3%, a sensitivity value of 57.1%, a G-mean value of 69.8%, and an AUC value of 71.1%. Discussion: In agreement with the promising results achieved, the application of suitable ML techniques could play a key role in the definition of a BRCA-mutated patient-centric clinical signature for ovarian cancer risk and consequently personalize the management of these patients. As far as we know, this is the first work addressing this task from an ML perspective.
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Background: Cervical cancer (CC) is characterized by genomic alterations in DNA repair genes, which could favor treatment with agents causing DNA double-strand breaks (DSBs), such as trabectedin. Hence, we evaluated the capability of trabectedin to inhibit CC viability and used ovarian cancer (OC) models as a reference. Since chronic stress may promote gynecological cancer and may hinder the efficacy of therapy, we investigated the potential of targeting ß-adrenergic receptors with propranolol to enhance trabectedin efficacy and change tumor immunogenicity. Methods: OC cell lines, Caov-3 and SK-OV-3, CC cell lines, HeLa and OV2008, and patient-derived organoids were used as study models. MTT and 3D cell viability assays were used for drug(s) IC50 determination. The analysis of apoptosis, JC-1 mitochondrial membrane depolarization, cell cycle, and protein expression was performed by flow cytometry. Cell target modulation analyses were carried out by gene expression, Western blotting, immunofluorescence, and immunocytochemistry. Results: Trabectedin reduced the proliferation of both CC and OC cell lines and notably of CC patient-derived organoids. Mechanistically, trabectedin caused DNA DSBs and S-phase cell cycle arrest. Despite DNA DSBs, cells failed the formation of nuclear RAD51 foci and underwent apoptosis. Under norepinephrine stimulation, propranolol enhanced trabectedin efficacy, further inducing apoptosis through the involvement of mitochondria, Erk1/2 activation, and the increase of inducible COX-2. Notably, trabectedin and propranolol affected the expression of PD1 in both CC and OC cell lines. Conclusion: Overall, our results show that CC is responsive to trabectedin and provide translational evidence that could benefit CC treatment options. Our study pointed out that combined treatment offset trabectedin resistance caused by ß-adrenergic receptor activation in both ovarian and cervical cancer models.
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The advent of vaccines represented a milestone to allow the slowing down and then containing of the exponential increase in ongoing infections and deaths of COVID-19. Since the first months of the vaccination campaign in various continents, there has been a certain number of reports of adverse events, including skin reactions. We conducted a systematic review, searching on PubMed, Web of Science, Scopus, and Cochrane Library for the words: COVID vaccine, dermatopathology, skin, eruptions, rash, cutaneous, BNT162b2 (Pfizer-BioNTech), ChAdOX1 (AstraZeneca), and mRNA-1273 (Moderna). A total of 28 records were initially identified in the literature search of which two were duplicates. After screening for eligibility and inclusion criteria, 18 publications were ultimately included. Various clinical cutaneous manifestations and histopathological patterns following vaccination have been described in literature. The most frequent clinical-pathological presentations were erythematous maculo-papular eruptions in different way of distribution with histopathological pictures mostly represented by interface changes and mixed peri-vascular and peri-adnexal cell infiltrate. Other presentations included new onset of pemphigoid bullous disease (n = 15), delayed T-cell-mediated hypersensitivity reaction (injection site reactions) (n = 10), purpuric skin rash (n = 13), mostly localized on the legs bilaterally and symmetrically with histological pictures characterized by extravasation of erythrocytes in the superficial and middle dermis, and other types of reactions. New studies with large case series and further literature reviews are needed to improve the clinical management of patients and optimize the timeline for carrying out histological biopsy for confirmatory, supportive, and differential diagnosis purposes.
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T cell immunoglobulin and mucin domain 3 (TIM-3) is an inhibitory immunocheckpoint that belongs to the TIM gene family. Monney et al. first discovered it about 20 years ago and linked it to some autoimmune diseases; subsequent studies have revealed that some tumours, including melanoma, have the capacity to produce inhibitory ligands that bind to these receptor checkpoints on tumour-specific immune cells. We conducted a literature search using PubMed, Web of Science (WoS), Scopus, Google Scholar, and Cochrane, searching for the following keywords: "T cell immunoglobulin and mucin-domain containing-3", "TIM-3" and/or "Immunocheckpoint inhibitors" in combination with "malignant melanoma" or "human malignant melanoma" or "cutaneous melanoma". The literature search initially turned up 117 documents, 23 of which were duplicates. After verifying eligibility and inclusion criteria, 17 publications were ultimately included. A growing body of scientific evidence considers TIM-3 a valid inhibitory immuno-checkpoint with a very interesting potential in the field of melanoma. However, other recent studies have discovered new roles for TIM-3 that seem almost to contradict previous findings in this regard. All this demonstrates how common and valid the concept of 'pleiotropism' is in the TME field, in that the same molecule can behave completely or partially differently depending on the cell type considered or on temporary conditions. Further studies, large case series, and a special focus on the immunophenotype of TIM-3 are absolutely necessary in order to explore this highly promising topic in the near future.
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Recent advances in anticancer treatment have significantly improved the survival rate of young females; unfortunately, in about one third of cancer survivors the risk of ovarian insufficiency and infertility is still quite relevant. As the possibility of becoming a mother after recovery from a juvenile cancer is an important part of the quality of life, several procedures to preserve fertility have been developed: ovarian surgical transposition, induction of ovarian quiescence by gonadotropin-releasing hormone agonists (GnRH-a) treatment, and oocyte and/or ovarian cortical tissue cryopreservation. Ovarian tissue cryostorage and allografting is a valuable technique that applies even to prepubertal girls; however, some patients cannot benefit from it due to the high risk of reintroducing cancer cells during allograft in cases of ovary-metastasizing neoplasias, such as leukemias or NH lymphomas. Innovative techniques are now under investigation, as in the construction of an artificial ovary made of isolated follicles inserted into an artificial matrix scaffold, and the use of stem cells, including ovarian stem cells (OSCs), to obtain neo-folliculogenesis and the development of fertilizable oocytes from the exhausted ovarian tissue. This review synthesizes and discusses these innovative techniques, which potentially represent interesting strategies in oncofertility programs and a new hope for young female cancer survivors.
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The preoperative evaluation of myometrial tumors is essential to avoid delayed treatment and to establish the appropriate surgical approach. Specifically, the differential diagnosis of leiomyosarcoma (LMS) is particularly challenging due to the overlapping of clinical, laboratory and ultrasound features between fibroids and LMS. In this work, we present a human-interpretable machine learning (ML) pipeline to support the preoperative differential diagnosis of LMS from leiomyomas, based on both clinical data and gynecological ultrasound assessment of 68 patients (8 with LMS diagnosis). The pipeline provides the following novel contributions: (i) end-users have been involved both in the definition of the ML tasks and in the evaluation of the overall approach; (ii) clinical specialists get a full understanding of both the decision-making mechanisms of the ML algorithms and the impact of the features on each automatic decision. Moreover, the proposed pipeline addresses some of the problems concerning both the imbalance of the two classes by analyzing and selecting the best combination of the synthetic oversampling strategy of the minority class and the classification algorithm among different choices, and the explainability of the features at global and local levels. The results show very high performance of the best strategy (AUC = 0.99, F1 = 0.87) and the strong and stable impact of two ultrasound-based features (i.e., tumor borders and consistency of the lesions). Furthermore, the SHAP algorithm was exploited to quantify the impact of the features at the local level and a specific module was developed to provide a template-based natural language (NL) translation of the explanations for enhancing their interpretability and fostering the use of ML in the clinical setting.