Aneurysmal artery supplying pulmonary sequestration: successful combined approach.

A 62-year-old man was diagnosed with an asymptomatic intralobar pulmonary sequestration supplied by a short-neck proximal 57×25 mm aneurysmal artery originating from the mid-descending aorta. The patient underwent thoracic endovascular aneurysm repair; an aortic endograft was released to entirely restore the aberrant vessel. Then, pulmonary resection was performed. A triportal video-assisted left lower lobectomy was carried out. The thoracic endovascular aneurysm repair minimized the risk of bleeding and allowed a safe pulmonary resection with a minimally invasive approach.

A Rare Case of Cervico-Mediastinal Thyroid Teratoma.

Teratomas are rare germ cell tumors derived from multiple germinal cell layers. Thyroid teratomas, specifically, are exceptionally uncommon and present unique diagnostic and therapeutic challenges. Here, we report a case of cervico-mediastinal thyroid teratoma, highlighting diagnostic difficulties and surgical management. A 37-year-old woman presented with right lateral cervical swelling, leading to radiological imaging suggesting a thymic teratoma. However, cytology indicated a colloid cyst. Surgical removal was performed, revealing a mixed-type teratoma originating from the thyroid gland. Thyroid teratomas pose diagnostic and therapeutic challenges due to their rarity and complex nature. Further research is needed to establish standardized guidelines for their management.

Are the Efficacy and Safety of Chest Tubes in Uniportal Video-Assisted Thoracic Surgery Related to the Level of Intercostal Space Insertion or to the Drain Type? A Prospective Multicenter Study.

OBJECTIVES: The aim of this study is to evaluate if the efficacy and safety of chest tube placement are influenced by the level of intercostal space insertion (uniportal VATS vs. biportal VATS) or by the type of drain employed (standard vs. smart coaxial drain). METHODS: Data on patients who underwent either uniportal or biportal VATS upper lobectomies with lymphadenectomy were prospectively collected in three European centers. The uniportal VATS group with a 28 Fr standard chest tube (U-VATS standard) was compared with the uniportal VATS group with a 28 Fr smart drain (U-VATS smart), and U-VATS smart was also compared with biportal VATS with a 28 Fr smart drain inserted in the VIII intercostal space (Bi-VATS smart). RESULTS: When comparing the U-VATS standard group with the U-VATS smart, a higher fluid output was recorded in the U-VATS smart (p: 0.004) in the III post-operative day (p.o.) and overall (p: 0.027), with a lower 90-day re-admission in the U-VATS smart (p: 0.04). The Bi-VATS smart group compared to U-VATS smart showed a higher fluid output in the I p.o. (p < 0.001), with no difference in total fluid amount or hospitalization. The Bi-VATS smart recorded a lower incidence (p < 0.001) of residual pleural space or effusion (p: 0.004) at chest X-rays prior to drain removal but a higher level of pain and chronic intercostal neuralgia (p: 0.03). CONCLUSIONS: Chest tube insertion through the same incision space in uniportal VATS seems to be safe and effective. Smart drains can improve the fluid output in uniportal VATS, as if the drainage were inserted in a lower space (i.e., biportal VATS), but with less discomfort.

Congenital Malformations of the Eye: A Pictorial Review and Clinico-Radiological Correlations.

Congenital malformations of the eye represent a wide and heterogeneous spectrum of abnormalities that may be part of a complex syndrome or be isolated. Ocular malformation severity depends on the timing of the causative event during eye formation, ranging from the complete absence of the eye if injury occurs during the first weeks of gestation, to subtle abnormalities if the cause occurs later on. Knowledge of ocular malformations is crucial to performing a tailored imaging protocol and correctly reporting imaging findings. Together with the ophthalmologic evaluation, imaging may help frame ocular malformations and identify underlying genetic conditions. The purpose of this pictorial review is to describe the imaging features of the main ocular malformations and the related ophthalmologic findings in order to provide a clinico-radiological overview of these abnormalities to the clinical radiologist. Sight is a crucial sense for children to explore the world and relate with their parents from birth. Vision impairment or even blindness secondary to ocular malformations deeply affects children's growth and quality of life.

Morphometric network-based abnormalities correlate with psychiatric comorbidities and gene expression in PCDH19-related developmental and epileptic encephalopathy.

Protocadherin-19 (PCDH19) developmental and epileptic encephalopathy causes an early-onset epilepsy syndrome with limbic seizures, typically occurring in clusters and variably associated with intellectual disability and a range of psychiatric disorders including hyperactive, obsessive-compulsive and autistic features. Previous quantitative neuroimaging studies revealed abnormal cortical areas in the limbic formation (parahippocampal and fusiform gyri) and underlying white-matter fibers. In this study, we adopted morphometric, network-based and multivariate statistical methods to examine the cortex and substructure of the hippocampus and amygdala in a cohort of 20 PCDH19-mutated patients and evaluated the relation between structural patterns and clinical variables at individual level. We also correlated morphometric alterations with known patterns of PCDH19 expression levels. We found patients to exhibit high-significant reductions of cortical surface area at a whole-brain level (left/right pvalue = 0.045/0.084), and particularly in the regions of the limbic network (left/right parahippocampal gyri pvalue = 0.230/0.016; left/right entorhinal gyri pvalue = 0.002/0.327), and bilateral atrophy of several subunits of the amygdala and hippocampus, particularly in the CA regions (head of the left CA3 pvalue = 0.002; body of the right CA3 pvalue = 0.004), and differences in the shape of hippocampal structures. More severe psychiatric comorbidities correlated with more significant altered patterns, with the entorhinal gyrus (pvalue = 0.013) and body of hippocampus (pvalue = 0.048) being more severely affected. Morphometric alterations correlated significantly with the known expression patterns of PCDH19 (rvalue = -0.26, pspin = 0.092). PCDH19 encephalopathy represents a model of genetically determined neural network based neuropsychiatric disease in which quantitative MRI-based findings correlate with the severity of clinical manifestations and had have a potential predictive value if analyzed early.

Fit of biokinetic data in molecular radiotherapy: a machine learning approach.

BACKGROUND: In literature are reported different analytical methods (AM) to choose the proper fit model and to fit data of the time-activity curve (TAC). On the other hand, Machine Learning algorithms (ML) are increasingly used for both classification and regression tasks. The aim of this work was to investigate the possibility of employing ML both to classify the most appropriate fit model and to predict the area under the curve (τ). METHODS: Two different ML systems have been developed for classifying the fit model and to predict the biokinetic parameters. The two systems were trained and tested with synthetic TACs simulating a whole-body Fraction Injected Activity for patients affected by metastatic Differentiated Thyroid Carcinoma, administered with [131I]I-NaI. Test performances, defined as classification accuracy (CA) and percentage difference between the actual and the estimated area under the curve (Δτ), were compared with those obtained using AM varying the number of points (N) of the TACs. A comparison between AM and ML were performed using data of 20 real patients. RESULTS: As N varies, CA remains constant for ML (about 98%), while it improves for F-test (from 62 to 92%) and AICc (from 50 to 92%), as N increases. With AM, [Formula: see text] can reach down to - 67%, while using ML [Formula: see text] ranges within ± 25%. Using real TACs, there is a good agreement between τ obtained with ML system and AM. CONCLUSIONS: The employing of ML systems may be feasible, having both a better classification and a better estimation of biokinetic parameters.

Machine Learning Analysis in Diffusion Kurtosis Imaging for Discriminating Pediatric Posterior Fossa Tumors: A Repeatability and Accuracy Pilot Study.

Background and purpose: Differentiating pediatric posterior fossa (PF) tumors such as medulloblastoma (MB), ependymoma (EP), and pilocytic astrocytoma (PA) remains relevant, because of important treatment and prognostic implications. Diffusion kurtosis imaging (DKI) has not yet been investigated for discrimination of pediatric PF tumors. Estimating diffusion values from whole-tumor-based (VOI) segmentations may improve diffusion measurement repeatability compared to conventional region-of-interest (ROI) approaches. Our purpose was to compare repeatability between ROI and VOI DKI-derived diffusion measurements and assess DKI accuracy in discriminating among pediatric PF tumors. Materials and methods: We retrospectively analyzed 34 children (M, F, mean age 7.48 years) with PF tumors who underwent preoperative examination on a 3 Tesla magnet, including DKI. For each patient, two neuroradiologists independently segmented the whole solid tumor, the ROI of the area of maximum tumor diameter, and a small 5 mm ROI. The automated analysis pipeline included inter-observer variability, statistical, and machine learning (ML) analyses. We evaluated inter-observer variability with coefficient of variation (COV) and Bland-Altman plots. We estimated DKI metrics accuracy in discriminating among tumor histology with MANOVA analysis. In order to account for class imbalances, we applied SMOTE to balance the dataset. Finally, we performed a Random Forest (RF) machine learning classification analysis based on all DKI metrics from the SMOTE dataset by partitioning 70/30 the training and testing cohort. Results: Tumor histology included medulloblastoma (15), pilocytic astrocytoma (14), and ependymoma (5). VOI-based measurements presented lower variability than ROI-based measurements across all DKI metrics and were used for the analysis. DKI-derived metrics could accurately discriminate between tumor subtypes (Pillai's trace: p < 0.001). SMOTE generated 11 synthetic observations (10 EP and 1 PA), resulting in a balanced dataset with 45 instances (34 original and 11 synthetic). ML analysis yielded an accuracy of 0.928, which correctly predicted all but one lesion in the testing set. Conclusions: VOI-based measurements presented improved repeatability compared to ROI-based measurements across all diffusion metrics. An ML classification algorithm resulted accurate in discriminating PF tumors on a SMOTE-generated dataset. ML techniques based on DKI-derived metrics are useful for the discrimination of pediatric PF tumors.

Vertical Parasagittal Hemispherotomy in a Pediatric Case of Epilepsy Due to Rasmussen Encephalitis: 2-Dimensional Operative Video.

Hemispherotomy is an effective disconnection technique for the treatment of different forms of drug-resistant epilepsy due to encephalopathies with unilateral hemispheric involvement.1-8 We describe the case of a 6-year-old child affected by Rasmussen encephalitis who underwent right vertical parasagittal hemispherotomy.9 The goal of the procedure was to isolate the basal ganglia region by interrupting the interhemispheric and intrahemispheric white matter connectivity. The main surgical steps include the transcortical approach to the lateral ventricle, the posterior callosotomy, the fimbria-fornix incision, the laterothalamic vertical incision, the anterior callosotomy, the frontobasal disconnection, and the transcaudate lateral incision to the anterior temporal horn.7,10 At 10-month follow-up, the patient was seizure free with a stable left hemiparesis. The antiepileptic therapy was progressively interrupted. The video describes the main surgical steps, using both intraoperative videos and advanced three-dimensional modeling of neuroimaging pictures. Patient' parents consented to the procedure. The participants and any identifiable individuals consented to publication of his/her image. Approval from the ethics committee was acquired.

Thymoma resection and myasthenia gravis: what is the neurological outcome in patients older than 65 years?

To increase the neurological results in patients older than 65 years with myasthenia gravis after thymectomy, we retrospectively analysed this outcome in a large bicentric cohort of patients with myasthenia gravis (MG)years, for which surgery was indicated for a concurrent thymoma. From 1/2000 to 2/2022, 502 patients underwent thymectomy for thymic epithelial tumours (TETs) in two high-volume Institutions (167aged more than 65 years). Among them, 66 patients were affected by TET and MG, representing our final study group. The mean age for MG onset was 68.3 ± 6 years.At surgery, the Osserman score 2 was the most diffuse in our cohort (43, 65.1%), followed by 1 (20, 30.3%). In 11 cases, the MG diagnosis coincided with thymoma diagnosis. In the other cases, the interval between MG diagnosis and surgery was 1.7 years ± 1.9. The most common surgical approach was sternotomy (41,62.1%), followed by RATS (14,21.2%). The most frequent TNM stage was T1N0 (75.7%) and most patients had WHO type-B tumour. After radical thymectomy, 58 patients (88%) reported a significant neurological improvement. According to MGFA-PIS, after surgery we had 4 (6%) complete stable remission, 11 (16.7%) pharmacological remission, 43 (65.2%) minimal manifestation, 2 (3%) worsening/death for MG, and 5 (7.6%) unchanged. No association was found between neurological outcome and age of MG onset, kind of pharmacological therapy before surgery, surgical approach (sternotomy vs others), tumour dimension, the ITMIG stage and the preoperative Osserman score. For MG and thymoma-afftected patients over 65 years, thymectomy seems to be an effective treatment to improve neurological symptoms. We suggest to set up clinical trials to explore the neurological efficacy of mini-invasive thymectomy in clinically selected MG patients aged over 65 years.

Uniportal Video-Assisted Thoracoscopic Surgery Completion Lobectomy Long after Wedge Resection or Segmentectomy in the Same Lobe: A Bicenter Study.

BACKGROUND: Completion lobectomy (CL) following a prior resection in the same lobe may be complicated by severe pleural or hilar adhesions. The role of uniportal video-assisted thoracoscopic surgery (U-VATS) has never been evaluated in this setting. METHODS: Data were collected from two Italian centers. Between 2015 and 2022, 122 patients (60 men and 62 women, median age 67.7 ± 8.913) underwent U-VATS CL at least 4 weeks after previous lung surgery. RESULTS: Twenty-eight (22.9%) patients were affected by chronic obstructive pulmonary disease (COPD) and twenty-five (20.4%) were active smokers. Among the cohort, the initial surgery was performed using U-VATS in 103 (84.4%) patients, triportal-VATS in 8 (6.6%), and thoracotomy in 11 (9.0%). Anatomical segmentectomy was the initial surgery in 46 (37.7%) patients, while hilar lymphadenectomy was performed in 16 (13.1%) cases. CL was performed on 110 (90.2%) patients, segmentectomy on 10 (8.2%), and completion pneumonectomy on 2 (1.6%). Upon reoperation, moderate pleural adhesions were observed in 38 (31.1%) patients, with 2 (1.6%) exhibiting strong adhesions. Moderate hilar adhesions were found in 18 (14.8%) patients and strong adhesions in 11 (9.0%). The median operative time was 203.93 ± 74.4 min. In four (3.3%) patients, PA taping was performed. One patient experienced intraoperative bleeding that did not require conversion to thoracotomy. Conversion to thoracotomy was necessary in three (2.5%) patients. The median postoperative drainage stay and postoperative hospital stay were 5.67 ± 4.44 and 5.52 ± 2.66 days, respectively. Postoperative complications occurred in 34 (27.9%) patients. Thirty-day mortality was null. Histology was the only factor found to negatively influence intraoperative outcomes (p = 0.000). Factors identified as negatively impacting postoperative outcomes at univariate analyses were male sex (p = 0.003), age > 60 years (p = 0.003), COPD (p = 0.014), previous thoracotomy (p = 0.000), previous S2 segmentectomy (p = 0.001), previous S8 segmentectomy (p = 0.008), and interval between operations > 5 weeks (p= 0.005). In multivariate analysis, only COPD confirmed its role as an independent risk factor for postoperative complications (HR: 5.12, 95% CI (1.07-24.50), p = 0.04). CONCLUSIONS: U-VATS CL seems feasible and safe after wedge resection and anatomical segmentectomy.

Machine Learning Algorithm: Texture Analysis in CNO and Application in Distinguishing CNO and Bone Marrow Growth-Related Changes on Whole-Body MRI.

OBJECTIVE: The purpose of this study is to analyze the texture characteristics of chronic non-bacterial osteomyelitis (CNO) bone lesions, identified as areas of altered signal intensity on short tau inversion recovery (STIR) sequences, and to distinguish them from bone marrow growth-related changes through Machine Learning (ML) and Deep Learning (DL) analysis. MATERIALS AND METHODS: We included a group of 66 patients with confirmed diagnosis of CNO and a group of 28 patients with suspected extra-skeletal systemic disease. All examinations were performed on a 1.5 T MRI scanner. Using the opensource 3D Slicer software version 4.10.2, the ROIs on CNO lesions and on the red bone marrow were sampled. Texture analysis (TA) was carried out using Pyradiomics. We applied an optimization search grid algorithm on nine classic ML classifiers and a Deep Learning (DL) Neural Network (NN). The model's performance was evaluated using Accuracy (ACC), AUC-ROC curves, F1-score, Positive Predictive Value (PPV), Mean Absolute Error (MAE) and Root-Mean-Square Error (RMSE). Furthermore, we used Shapley additive explanations to gain insight into the behavior of the prediction model. RESULTS: Most predictive characteristics were selected by Boruta algorithm for each combination of ROI sequences for the characterization and classification of the two types of signal hyperintensity. The overall best classification result was obtained by the NN with ACC = 0.91, AUC = 0.93 with 95% CI 0.91-0.94, F1-score = 0.94 and PPV = 93.8%. Between classic ML methods, ensemble learners showed high model performance; specifically, the best-performing classifier was the Stack (ST) with ACC = 0.85, AUC = 0.81 with 95% CI 0.8-0.84, F1-score = 0.9, PPV = 90%. CONCLUSIONS: Our results show the potential of ML methods in discerning edema-like lesions, in particular by distinguishing CNO lesions from hematopoietic bone marrow changes in a pediatric population. The Neural Network showed the overall best results, while a Stacking classifier, based on Gradient Boosting and Random Forest as principal estimators and Logistic Regressor as final estimator, achieved the best results between the other ML methods.

Dosimetric impact of applying a model-based dose calculation algorithm for skin cancer brachytherapy (interventional radiotherapy).

Purpose: Brachytherapy (BT, interventional radiotherapy) is a well-established radiotherapy technique capable of delivering high doses to tumors while sparing organs at risk (OARs). Currently, the clinically accepted dose calculation algorithm used is TG-43. In the TG-186 report, new model-based dose calculation algorithms (MBDCA), such as Elekta's advanced collapsed cone engine (ACE), have been introduced, although their clinical application is yet to be fully realized. This study aimed to investigate two aspects of TG-186: firstly, a comparison of dose distributions calculated with TG-43 and TG-186 for skin tumors; and secondly, an exploration of the impact of using a water bolus on the coverage of clinical target volume (CTV) and OARs. Material and methods: Ten treatment plans for high-dose-rate IRT were developed. All plans were initially calculated using the TG-43 algorithm, and were subsequently re-calculated with TG-186. In addition, one of the treatment plans was assessed with both TG-43 and TG-186, using 10 different water bolus thicknesses ranging from 0 to 5 cm. To assess dose variations, the following dose-volume histogram (DVH) parameters were compared: D2cc and D0.01cc for OARs, and V150, V100, V95 and V90 for CTV coverage. Results and conclusions: The average dosimetric results for CTV and OARs, as calculated by both algorithms, revealed statistically significant lower values for TG-186 when compared with TG-43. The presence of a bolus was observed to enhance CTV coverage for the TG-186 algorithm, with a bolus thickness of 2 cm being the point at which ACE calculations matched those of TG-43. This study identified significant differences in dosimetric parameters for skin tumors when comparing the TG-43 and TG-186 algorithms. Moreover, it was demonstrated that the inclusion of a water bolus increased CTV coverage in TG-186 calculations.

Assessing cortical features in early stage ASD children.

Autism Spectrum Disorder (ASD) is defined as a neurodevelopmental disorder largely investigated in the neurologic field. Recently, neuroimaging studies have been conducted in order to investigate cerebral morphologic alterations in ASD patients, demonstrating an atypical brain development before the clinical manifestations of the disorder. Cortical Thickness (CT) and Local Gyrification Index (LGI) distribution for ASD children were investigated in this study, with the aim to evaluate possible relationship between brain measures and individual characteristics (i.e., IQ and verbal ability). 3D T1-w sequences from 129 ASD and 58 age-matched Healthy Controls (HC) were acquired and processed in order to assess CT and LGI for each subject. Intergroup differences between ASD and HC were investigated, including analyses of 2 ASD subgroups, split according to patient verbal ability and IQ. When compared to HC, ASD showed increased CT and LGI within several brain areas, both as an overall group and as verbal ability an IQ subgroups. Moreover, when comparing language characteristics of the ASD subjects, those patients with verbal ability exhibit significant CT and LGI increase was found within the occipital lobe of right hemisphere. No significant results occurred when comparing ASD patients according to their IQ value. These results support the hypothesis of abnormal brain maturation in ASD since early childhood with differences among clinical subgroups suggesting different anatomical substrates underlying an aberrant connectivity.