Combining Sclerotherapy with CO2 Laser Ablation for the Laparoscopic Management of Large Endometrioma: Advantages and Pitfalls.

STUDY OBJECTIVE: To demonstrate the feasibility of management of large endometrioma laparoscopically. DESIGN: Stepwise demonstration with narrated video footage of the laparoscopic 2-step procedure starting with alcohol sclerotherapy of the large endometrioma followed by CO2 laser ablation and 6-month follow-up. SETTING: The debate surrounding the best approach for the management of large endometriomas has been ongoing. Cystectomy especially when treating large endometriomas has been shown to decrease ovarian reserve proportionally to the endometrioma's size.2,4 This is why 2-step approaches have been considered to preserve the ovarian reserve.1,3 We present the case of a 22-year-old nulliparous woman who has primary severe dysmenorrhea resistant to medical treatment. Magnetic resonance imaging shows uterine adenomyosis and a 10 cm large endometrioma of the left ovary and no signs of deep infiltrative endometriosis. She has a desire for pregnancy in the distant future. INTERVENTION: The first step is the laparoscopic ethanol sclerotherapy. After emptying and rinsing the endometrioma's cavity through a 5 mm suction cannula, it is then filled with ethanol through a 14 French Foley catheter to avoid any overflow.5,6 After a time exposure of 10 minutes, the ethanol is withdrawn and the cavity rinsed (Figure 2). The second step of the surgery is performed 12 weeks later (Figure 3). Using CO2 laser, the untreated portion of the inner wall of the remaining endometrioma is vaporized along with remaining superficial endometriosis lesions (Figure 1). CONCLUSION: Laparoscopy sclerotherapy combined to CO2 laser ablation is a feasible technique for the management of a large endometrioma. Further research is still required to evaluate the benefit of a 2-step surgery approach over standard cystectomy and to understand the long-term effects of ethanol-induced ovarian fibrosis.

Tracheal agenesis: optimization of computed tomography diagnosis by airway ventilation.

Tracheal agenesis is a rare and often lethal congenital defect that leads to airway emergency at birth. Computed tomography (CT) is the modality of choice to evaluate anomalous tracheal anatomy. The absence of spontaneous aeration of the tracheobronchial tree in children with tracheal agenesis makes CT interpretation difficult. We describe a procedure of airway management applied in two newborns with suspected tracheal agenesis. Correct airway management was performed immediately prior to CT examination by airway ventilation, with bag-valve mask alone in one case, and attached to an endotracheal tube placed into the esophagus in the other case. The images allowed for classification of tracheal agenesis. Computed tomography with appropriate airway ventilation is fundamental for the diagnosis of tracheal agenesis.

A distributed feature selection pipeline for survival analysis using radiomics in non-small cell lung cancer patients.

Predictive modelling of cancer outcomes using radiomics faces dimensionality problems and data limitations, as radiomics features often number in the hundreds, and multi-institutional data sharing is ()often unfeasible. Federated learning (FL) and feature selection (FS) techniques combined can help overcome these issues, as one provides the means of training models without exchanging sensitive data, while the other identifies the most informative features, reduces overfitting, and improves model interpretability. Our proposed FS pipeline based on FL principles targets data-driven radiomics FS in a multivariate survival study of non-small cell lung cancer patients. The pipeline was run across datasets from three institutions without patient-level data exchange. It includes two FS techniques, Correlation-based Feature Selection and LASSO regularization, and Cox Proportional-Hazard regression with Overall Survival as endpoint. Trained and validated on 828 patients overall, our pipeline yielded a radiomic signature comprising "intensity-based energy" and "mean discretised intensity". Validation resulted in a mean Harrell C-index of 0.59, showcasing fair efficacy in risk stratification. In conclusion, we suggest a distributed radiomics approach that incorporates preliminary feature selection to systematically decrease the feature set based on data-driven considerations. This aims to address dimensionality challenges beyond those associated with data constraints and interpretability concerns.

Implementation of Artificial Intelligence in Personalized Prognostic Assessment of Lung Cancer: A Narrative Review.

Artificial Intelligence (AI) has revolutionized the management of non-small-cell lung cancer (NSCLC) by enhancing different aspects, including staging, prognosis assessment, treatment prediction, response evaluation, recurrence/prognosis prediction, and personalized prognostic assessment. AI algorithms may accurately classify NSCLC stages using machine learning techniques and deep imaging data analysis. This could potentially improve precision and efficiency in staging, facilitating personalized treatment decisions. Furthermore, there are data suggesting the potential application of AI-based models in predicting prognosis in terms of survival rates and disease progression by integrating clinical, imaging and molecular data. In the present narrative review, we will analyze the preliminary studies reporting on how AI algorithms could predict responses to various treatment modalities, such as surgery, radiotherapy, chemotherapy, targeted therapy, and immunotherapy. There is robust evidence suggesting that AI also plays a crucial role in predicting the likelihood of tumor recurrence after surgery and the pattern of failure, which has significant implications for tailoring adjuvant treatments. The successful implementation of AI in personalized prognostic assessment requires the integration of different data sources, including clinical, molecular, and imaging data. Machine learning (ML) and deep learning (DL) techniques enable AI models to analyze these data and generate personalized prognostic predictions, allowing for a precise and individualized approach to patient care. However, challenges relating to data quality, interpretability, and the ability of AI models to generalize need to be addressed. Collaboration among clinicians, data scientists, and regulators is critical for the responsible implementation of AI and for maximizing its benefits in providing a more personalized prognostic assessment. Continued research, validation, and collaboration are essential to fully exploit the potential of AI in NSCLC management and improve patient outcomes. Herein, we have summarized the state of the art of applications of AI in lung cancer for predicting staging, prognosis, and pattern of recurrence after treatment in order to provide to the readers a large comprehensive overview of this challenging issue.

Sterotactic Ablative Radiotherapy in a Multicentric Series of Oligometastatic SCLC: The SAMOS Cohort.

AIMS: SCLC is the most aggressive lung cancer histology with a 5-year OS <10%. At the diagnosis, almost two-thirds of the SCLC an Extended Disease presentation. Two randomized studies (CASPIAN and ImPower133) demonstrated an OS improvement, when immunotherapy was prescribed as maintenance therapy after standard chemotherapy. To date, SABR has had a limited indication in managing metastatic SCLC, although recent reports proposed it as a valid treatment option in selected patients. We propose a retrospective multicentric analysis of patients treated with SABR for oligometastatic SCLC. METHOD: Data of patients affected by oligometastatic-SCLC treated with SABR between 2017 and 2022 in 11 Italian centers were collected. Clinical and therapeutic variables together with OS and time to next treatment were analyzed. Univariate analysis with Kaplan-Meier curve were calculated, and log-rank test were applied. Cox proportional hazard model was used for multivariate analysis. RESULTS: Data from 93 patients and 132 metastatic lesions were analyzed. The median age was 64 years (36-86) and all but 1 had Performance Status 0 or 1. Fifty-two patients presented ED at diagnosis. The first line treatment was radiochemotherapy in 42%, CHT alone in 24% and CHT-IO in 28%, others treatment accounts for 4% and only 2% of patients underwent best supportive care. Of the 132 lesions treated with SBRT 55 were in brain, 27 in lung, 11 in liver, 10 in lymph nodes, 8 in bones and 20 in adrenal gland. Median OS was 14 months, 1 year-OS and 2 years OS were 53% and 27%, respectively. The median TtNT was 14 months for the entire population. Of all the analyzed variables only, the anatomical site of the metastases and their number showed statistical significance in the univariate analysist, confirmed in the subsequent multivariate. CONCLUSION: SABR seems to play a role in delaying further systemic lines in oligometastatic disease and to extend the use of ongoing treatment in oligoprogressive state. Prospective studies are needed to confirm these findings.

Case report Iatrogenic parasitic leiomyoma: the surgeon's invisible hand.

Uterine leiomyoma is the most common benign tumour of the uterus in women of reproductive age. When removed surgically, a mini-invasive procedure is preferentially used (laparoscopic or robotic) and the extraction of the specimen can be managed by power morcellation. In this consecutive case-series, we present three cases of parasitic leiomyoma that appeared following previous surgical management of leiomyoma using the technique of laparoscopic myomectomy with uncontained power morcellation. The time frame in between the initial surgery and the diagnosis of the parasitic leiomyoma was 5.7 years. All three patients were diagnosed with endometriosis: 2 cases prior to the initial surgery and 1 case after the initial surgery. One hypothesis could be that, due to pelvic inflammation, endometriosis is a risk factor for iatrogenic parasitic leiomyoma development in case of uncontained morcellation of leiomyoma during myomectomy.

May we routinely spare hippocampal region in primary central nervous system lymphoma during whole brain radiotherapy?

PURPOSE: One of the main limiting factors of whole-brain radiation therapy (WBRT) for primary central nervous system lymphoma (PCNSL) is the impairment of neurocognitive functions (NCFs), which is mainly caused by radiation-induced injury to the hippocampus. With a view to preventing NCF impairment and personalizing treatment, we explored the feasibility of sparing the hippocampus during WBRT by correlating the sites of PCNSL lesions with the hippocampus. METHODS AND MATERIALS: Pre-treatment MR images from patients who underwent WBRT between 2010 and January 2020-and post-radiotherapy images in cases of relapse-were imported into the Varian Eclipse treatment-planning system and registered with the simulation CT. We constructed three 3-dimensional envelopes around the hippocampus at distances of 5, 10 and 15 mm and also contoured primary lesions and recurrences. RESULTS: We analyzed 43 patients with 66 primary lesions: 9/66 (13.6%) involved the hippocampus and 11/66 (16.7%) were located within 5 mm of it. Thirty-six lesions (54.5%) were situated more than 15 mm from the hippocampus, while 10/66 (15.2%) were between 5 and 15 mm from it. The most common location was in deep brain structures (31%). Thirty-five of the 66 lesions relapsed: in field in 14/35 (40%) and outfield in 21/35 (60%) in different sites. Globally, 16/35 recurrences (45.7%) were located in the hippocampus or within 5 mm of it. CONCLUSION: These data show that routinely sparing the hippocampus is not feasible. This approach could be considered in selected patients, when the lesion is more than 15 mm from the hippocampus.

Clinical and NGS predictors of response to regorafenib in recurrent glioblastoma.

Predictive factors for response to regorafenib in recurrent glioblastoma, IDH-wildtype, are scarcely recognized. The objective of this study was to identify molecular predictive factors for response to regorafenib using a clinically available platform. We analyzed a prospective cohort of 30 patients harboring recurrent glioblastoma, IDH-wildtype, and treated with regorafenib. Next-generation sequencing (NGS) analysis was performed on DNA extracted from paraffin-embedded tissues using a clinically available platform. Moreover, MGMT methylation and EGFRvIII expression analyses were performed. Six-month progression-free survival (PFS) was 30% and median overall survival (OS) was 7.5 months, in line with literature data. NGS analysis revealed a mutation in the EGFR pathway in 18% of cases and a mutation in the mitogen-activated protein-kinase (MAPK) pathway in 18% of cases. In the remaining cases, no mutations were detected. Patients carrying MAPK pathway mutation had a poor response to regorafenib treatment, with a significantly shorter PFS and a nonsignificantly shorter OS compared to EGFR-mutated patients (for PFS, 2.5 vs 4.5 months, p = 0.0061; for OS, 7 vs 9 months, p = 0.1076). Multivariate analysis confirmed that MAPK pathway mutations independently predicted a shorter PFS after regorafenib treatment (p = 0.0188). The negative prognostic role of MAPK pathway alteration was reinforced when we combined EGFR-mutated with EGFRvIII-positive cases. Recurrent glioblastoma tumors with an alteration in MAPK pathway could belong to the mesenchymal subtype and respond poorly to regorafenib treatment, while EGFR-altered cases have a better response to regorafenib. We thus provide a molecular selection criterion easy to implement in the clinical practice.

Clinical Stage III NSCLC Patients Treated with Neoadjuvant Therapy and Surgery: The Prognostic Role of Nodal Characteristics.

BACKGROUND: The aim of this study is to analyze the prognostic factors in patients that underwent induction therapy and surgery for clinical stage III NSCLC. METHODS: Clinical and pathological characteristics of stage III NSCLC patients for N2 involvement that underwent neoadjuvant treatment (NAD) and surgery from 1/01/1998 to 31/12/2017 were collected and retrospectively analyzed. Tumor characteristics, yClinical, yPathological stage and lymph node characteristics were correlated to Overall Survival (OS). RESULTS: The analysis was conducted on 180 patients. Five-year OS (5YOS) was 50.9%. Univariable analysis results revealed old age (p = 0.003), clinical N2 post-NAD (p = 0.01), pneumonectomy (0.005), persistent pathological N2 (p = 0.039, HR 1.9, 95% CI 1.09−2.68) and adjuvant therapy absence (p = 0.049) as significant negative prognostic factors. Multivariable analysis confirmed pN0N1 (p = 0.02, HR 0.29, 95% CI 0.13−0.62) as a favorable independent prognostic factor and adjuvant therapy absence (p = 0.012, HR 2.61, 95% CI 1.23−5.50) as a negative prognostic factor. Patients with persistent N2 presented a 5YOS of 35.3% vs. 55.8% in pN0N1 patients. Regarding lymph node parameters, the lymph node ratio (NR) significantly correlated with OS: 5YOS of 67.6% in patients with NR < 50% vs. 29.5% in NR > 50% (p = 0.029). CONCLUSION: Clinical response aided the stratification of prognosis in patients that underwent multimodal treatment for stage III NSCLC. Adjuvant therapy seemed to be an important option in these patients, while node ratio was a strong prognosticator in patients with persistent nodal involvement.

Predicting Radiotherapy Impact on Late Bladder Toxicity in Prostate Cancer Patients: An Observational Study.

BACKGROUND AND PURPOSE: The aim of our study was to elaborate a suitable model on bladder late toxicity in prostate cancer (PC) patients treated by radiotherapy with volumetric technique. MATERIALS AND METHODS: PC patients treated between September 2010 and April 2017 were included in the analysis. An observational study was performed collecting late toxicity data of any grade, according to RTOG and CTCAE 4.03 scales, cumulative dose volumes histograms were exported for each patient. Vdose, the value of dose to a specific volume of organ at risk (OAR), impact was analyzed through the Mann-Whitney rank-sum test. Logistic regression was used as the final model. The model performance was estimated by taking 1000 samples with replacement from the original dataset and calculating the AUC average. In addition, the calibration plot (Hosmer-Lemeshow goodness-of-fit test) was used to evaluate the performance of internal validation. RStudio Software version 3.3.1 and an in house developed software package "Moddicom" were used. RESULTS: Data from 175 patients were collected. The median follow-up was 39 months (min-max 3.00-113.00). We performed Mann-Whitney rank-sum test with continuity correction in the subset of patients with late bladder toxicity grade ≥ 2: a statistically significant p-value with a Vdose of 51.43 Gy by applying a logistic regression model (coefficient 4.3, p value 0.025) for the prediction of the development of late G ≥ 2 GU toxicity was observed. The performance for the model's internal validation was evaluated, with an AUC equal to 0.626. Accuracy was estimated through the elaboration of a calibration plot. CONCLUSIONS: Our preliminary results could help to optimize treatment planning procedures and customize treatments.

CT Radiomics Signature of Tumor and Peritumoral Lung Parenchyma to Predict Nonsmall Cell Lung Cancer Postsurgical Recurrence Risk.

RATIONALE AND OBJECTIVES: To estimate recurrence risk after surgery in nonsmall cell lung cancer (NSCLC) patients by employing tumoral and peritumoral radiomics analysis. MATERIALS AND METHODS: One-hundred twenty-four surgically treated stage IA-IIB NSCLC patients' data from 2008 to 2013 were retrospectively collected. Patient outcome was defined as local recurrence (LR), distant metastasis (DM), and (sum of LR and DM) total recurrence (TR) at follow-up. Volumetric region of interests (ROIs) were drawn for the tumor, peritumoral lung parenchyma (2 cm around the tumor) and involved lobe on CT images. Ninety-four (morphological, first-order, textural, fractal-based) radiomics features were extracted from the ROIs and datasets were created from single or combined ROIs. Predictive models were built with radiomics signature (RS) and clinicopathological data, and the area under the curve (AUC) was used to evaluate the performance. Radiomics score was calculated with the best models' feature coefficients, low- and high-risk groups of patients defined accordingly. Kaplan-Meier curves were built, and the log-rank test was used for comparison among low- and high-risk groups. Differences in recurrence risk among the two risk groups were calculated (chi-square test). RESULTS: Fifty-six patients developed TR (25 LR, 31 DM). The tumor-node-metastasis (TNM) stage recurrence predictability (AUCTR 0.680; AUCDM 0.672; AUCLR 0.580) was substantially improved when RS was added to the predictive model (AUCTR 0.760; AUCDM 0.759; AUCLR 0.750). Seventy-five percent of high-risk patients developed TR. Recurrence risk of the high-risk group was 16-fold higher than that of the low-risk group (p < 0.001). CONCLUSION: Combination of the tumoral and peritumoral RS with TNM staging system outperformed TNM staging alone in individualized recurrence risk estimation of patients with surgically treated NSCLC.

Reducing heart dose during left breast cancer radiotherapy: comparison among 3 radiation techniques.

PURPOSE: Breast cancer survivors have a high risk of cardiac death as a consequence of heart irradiation during left breast tangential radiotherapy (RT). This study compares the cardiac dose delivered by standard 3D conformal tangential RT (CRT) to that delivered by prospective-gating RT (PGRT) or 5-field intensity-modulated RT (IMRT). METHODS: Patients with early left breast cancer, referred for adjuvant RT to our institution, were enrolled in this study. For each patient, 2 simulation computed tomography scans were acquired: the first during free breathing, and the second on prospective gating during deep inspiration breath-hold. The scans were monitored by the Varian RPM™ respiratory gating system. For each patient, 3 treatment plans were performed: a 3D-CRT and an IMRT plan, each based on the free-breathing scan, and a PGRT plan, based on the deep inspiration breath-hold scan. Dose-volume histograms were compared by means of the Friedman test. RESULTS: The median mean heart dose was 3 Gy (range 0.9-7.3 Gy) in the CRT plans, 1.9 Gy (range 0.5-3.6 Gy) in the PGRT plans, and 4.5 Gy (range 1.1-10.5 Gy) in the IMRT plans (p = 0.001). The mean heart V25 was 1.2% (range 0%-9.7%), 0% (range 0%-2.0%), and 0.2% (range 0%-7.3%) for CRT, PGRT, and IMRT plans, respectively (p<0.001). CONCLUSIONS: Prospective-gating RT to the left breast offered the best protection of heart and lung, as well as a lower irradiation of the contralateral breast, compared to CRT or IMRT.