Glioblastoma (GBM) is regarded as an aggressive brain tumor that rarely develops extracranial metastases. Despite well-investigated molecular alterations in GBM, there is a limited understanding of these associated with the metastatic potential. We herein present a case report of a 43-year-old woman with frontal GBM with primitive neuronal component who underwent gross total resection followed by chemoradiation. Five months after surgery, the patient was diagnosed with an intraspinal GBM metastasis. Next-generation sequencing analysis of both the primary and metastatic GBM tissues was performed using the Illumina TruSight Tumor 170 assay. The number of single nucleotide variants observed in the metastatic sample was more than two times higher. Mutations in TP53, PTEN, and RB1 found in the primary and metastatic tissue samples indicated the mesenchymal molecular GBM subtype. Among others, there were two inactivating mutations (Arg1026Ile, Trp1831Ter) detected in the NF1 gene, two novel NOTCH3 variants of unknown significance predicted to be damaging (Pro1505Thr, Cys1099Tyr), one novel ARID1A variant of unknown significance (Arg1046Ser), and one gene fusion of unknown significance, EIF2B5-KIF5B, in the metastatic sample. Based on the literature evidence, the alterations of NF1, NOTCH3, and ARID1A could explain, at least in part, the acquired invasiveness and metastatic potential in this particular GBM case. Full article

In many cardiac diseases, right and left ventricular volumes in systole and diastole are diagnostically and prognostically relevant. Measurements are made by segmentation of the myocardial borders on cardiac magnetic resonance (CMR) images. Automatic detection of myocardial contours is possible by signal thresholding techniques, but must be validated before use in clinical settings. Biventricular volumes were measured in end-diastole (EDVi) and in end-systole (ESVi) both manually and with the MassK application, with signal thresholds at 30%, 50%, and 70%. Stroke volumes (SV) and cardiac indices (CI) were calculated from volumetric measurements and from flow measured in the ascending aorta and the main pulmonary artery, and both methods were compared. Reproducibility of volumetric measurements was tested in 20 patients. Measurements were acquired in 94 patients aged 15 ± 9 years referred for various conditions. EDVi and ESVi of both ventricles were largest with manual segmentation and inversely proportional to the MassK threshold. Manual and k30 SV and CI corresponded best to flow measurements. Interobserver variability was low for all volumes manually and with MassK. In conclusion, manual and 30% threshold-based biventricular volume segmentation agree best with two-dimensional, phantom-corrected phase contrast flow measurements in a young cardiac referral population and are well reproducible. Full article

A gigahertz (GHz) range antenna formed by a coaxial probe has been applied for sensing cancerous breast lesions in the scanning platform with the assistance of a suction tube. The sensor structure was a planar central layer and a metallic sheath of size of 3 cm² connected to a network analyzer (keySight FieldFox N9918A) with operational bandwidth up to 26.5 GHz. Cancer tumor cells have significantly higher water content (as a dipolar molecule) than normal breast cells, changing their polarization responses and dielectric losses to incoming GHz-based stimulation. Principal component analysis named S₁₁, related to the dispersion ratio of the input signal, is used as a parameter to identify malignant tumor cells in a mouse model (in vivo) and tumor specimens of breast cancer patients (in vitro) (both central and marginal parts). The results showed that S₁₁ values in the frequency range from 5 to 6 GHz were significantly higher in cancer-involved breast lesions. Histopathological analysis was the gold standard for achieving the S₁₁ calibration to distinguish normal from cancerous lesions. Our calibration on tumor specimens presented 82% positive predictive value (PPV), 100% negative predictive value (NPV), and 86% accuracy. Our goal is to apply this system as an in vivo non-invasive tumor margin scanner after further investigations in the future. Full article

Breast mass identification is a crucial procedure during mammogram-based early breast cancer diagnosis. However, it is difficult to determine whether a breast lump is benign or cancerous at early stages. Convolutional neural networks (CNNs) have been used to solve this problem and have provided useful advancements. However, CNNs focus only on a certain portion of the mammogram while ignoring the remaining and present computational complexity because of multiple convolutions. Recently, vision transformers have been developed as a technique to overcome such limitations of CNNs, ensuring better or comparable performance in natural image classification. However, the utility of this technique has not been thoroughly investigated in the medical image domain. In this study, we developed a transfer learning technique based on vision transformers to classify breast mass mammograms. The area under the receiver operating curve of the new model was estimated as 1 ± 0, thus outperforming the CNN-based transfer-learning models and vision transformer models trained from scratch. The technique can, hence, be applied in a clinical setting, to improve the early diagnosis of breast cancer. Full article

Background: Follitropin delta is the third recombinant human follicle-stimulating hormone (r-hFSH) expressed in a host cell line of human fetal retinal origin that currently emphasizes that the actual tendency of administration is a personalized dosing algorithm based on the anti-Müllerian hormone (AMH) and body mass index (BMI) for ovarian stimulation. Methods: In this context, we aimed, in the present manuscript, to gather all available data published between 2018–2022 regarding the co-administration and administration of follitropin delta and the clinical outcomes reported following an in vitro fertilization (IVF). Results: Follitropin delta is non-inferior in contrast to its previously launched agents for ovarian stimulation, enhancing a similar-to-superior response reflected by both the reproductive and pregnancy outcomes in parallel with a low risk of ovarian hyperstimulation syndrome (OHSS), being well tolerated. The body weight and AMH level are factors that may influence the outcome in a patient. Despite controversy and results that refute these arguments on several occasions, follitropin delta exceeds the benefits of conventional dosing with either follitropin alfa or follitropin beta. Thus, all post hoc, derived analyses and subsets of patients that participated in subsequent studies support this statement. Conclusions: Despite the relatively limited spectrum of data in the current literature, most authors brought potent proof, supporting the subsequent use of this drug depending on the patient’s profile and overcoming ethnic-related limitations. Although others contradict these observations, this topic and drug possess substantial potential, which is why additional studies are mandatory to fill the existing gaps in our knowledge and expand these experiences at a larger scale supported by the obtained reproductive and clinical outcomes that clearly indicate an overcoming of all limitations. Full article

Colposcopic patterns of Vaginal Intraepithelial Neoplasia (VAIN) are not definitively related to histological grade. The aim of the present study was to investigate any correlation between clinical and colposcopic features and the development of high-grade VAIN. Two hundred and fifty-five women diagnosed with VAIN (52 VAIN1, 55 VAIN2 and 148 VAIN3) at the European Institute of Oncology, Milan, Italy, from January 2000 to June 2022, were selected for a retrospective analysis. Multivariate logistic regression was performed to estimate the association of risk factors and colposcopic patterns with VAIN grade. Smoking was associated with the development of VAIN (34.1%, p = 0.01). Most women diagnosed with VAIN3 (45.3%, p = 0.02) had a previous history of hysterectomy for CIN2+. At multivariate analysis, colposcopic grade G2 (OR = 20.4, 95%CI: 6.67–61.4, p < 0.001), papillary lesion (OR = 4.33, 95%CI: 1.79–10.5, p = 0.001) and vascularity (OR = 14.4, 95%CI: 1.86–112, p = 0.01) were significantly associated with a greater risk of VAIN3. The risk of high-grade VAIN should not be underestimated in women with a history of smoking and previous hysterectomy for CIN2+, especially when colposcopic findings reveal vaginal lesions characterized by grade 2, papillary and vascular patterns. Accurate diagnosis is crucial for an optimal personalized management, based on risk factors, colposcopic patterns and histologic grade of VAIN. Full article

Metastatic lesions of the spine occur in up to 40% of cancer patients and are a frequent source of pain and neurologic deficit due to cord compression. Palliative radiotherapy is the main first-intent local treatment in the form of single-fraction radiotherapy or fractionated courses. Reirradiation is a viable option for inoperable patients where spinal decompression is needed but with an increased risk of radiation-induced myelopathy (RM) and subsequent neurologic damage. This review summarizes reported data on local treatment options after initial irradiation in patients with relapsed spine metastasis and key dosimetric correlations between the risk of spinal cord injury and reirradiation technique, total dose, and time between treatments. The Linear Quadratic (LQ) model was used to convert all the published doses into biologically effective doses and normalize them to EQD2. For 3D radiotherapy, authors used cumulative doses from 55.2 Gy2/2 to 65.5 Gy2/2 EQD2 with no cases of RM mentioned. We found little evidence of RM after SBRT in the papers that met our criteria of inclusion, usually at the median reported dose to critical neural tissue around 93.5 Gy2/2. There is a lack of consistency in reporting the spinal cord dose, which leads to difficulty in pooling data. Full article

Growing evidence suggests that intracranial pressure (ICP) plays an important role in the pathophysiology of glaucoma, especially in normal-tension glaucoma (NTG) patients. Controversial results exist about ICP’s relationship to visual field (VF) changes. With the aim to assess the relationship between ICP and VF zones in NTG patients, 80 NTG patients (age 59.5 (11.6) years) with early-stage glaucoma were included in this prospective study. Intraocular pressure (IOP) (Goldmann), visual perimetry (Humphrey) and non-invasive ICP (via a two-depth Transcranial Doppler, Vittamed UAB, Lithuania) were evaluated. Translaminar pressure difference (TPD) was calculated according to the formula TPD = IOP − ICP. The VFs of each patient were divided into five zones: nasal, temporal, peripheral, central, and paracentral. The average pattern deviation (PD) scores were calculated in each zone. The level of significance p < 0.05 was considered significant. NTG patients had a mean ICP of 8.5 (2.4) mmHg. Higher TPD was related with lower mean deviation (MD) (p = 0.01) and higher pattern standard deviation (PSD) (p = 0.01). ICP was significantly associated with the lowest averaged PD scores in the nasal VF zone (p < 0.001). There were no significant correlations between ICP and other VF zones with the most negative mean PD value. (p > 0.05). Further studies are needed to analyze the involvement of ICP in NTG management. Full article

Background: The study was undertaken to compare the diagnostic performance of diffusion kurtosis imaging (DKI) with the standard monoexponential (ME) apparent diffusion coefficient (ADC) model in the detection of significant prostate cancer (PCa), using whole-mount histopathology of radical prostatectomy specimens as a reference standard. Methods: 155 patients with prostate cancer had undergone multiparametric magnetic resonance imaging (mpMRI) at 3T before prostatectomy. Quantitative diffusion parameters—the apparent diffusion coefficient corrected for non-Gaussian behavior (D_app), kurtosis (K), ADC₁₂₀₀, and ADC₂₀₀₀ were correlated with Gleason score and compared between cancerous and benign tissue and between GS ≤ 3 + 3 and GS ≥ 3 + 4 tumors. Results: The mean values of all diffusion parameters (D_app, K, ADC₁₂₀₀, ADC₂₀₀₀) were significantly different both between malignant and benign tissue and between GS ≤ 3 + 3 and GS ≥ 3 + 4 tumors. Although the kurtosis model was better fitted to DWI data, the diagnostic performance in receiver operating characteristic (ROC) analysis of DKI and the standard ADC model in the detection of significant PCa was similar in the peripheral zone (PZ) and in peripheral and transitional zones (TZ) together. In conclusion, our study was not able to demonstrate a clear superiority of the kurtosis model over standard ADC in the diagnosis of significant PCa in PZ and in both zones combined. Full article

The assessment of bruxism relies on clinical examinations, questionnaires, and polysomnography. The additional use of colored foils (BruxChecker^®) could enable a more precise evaluation of bruxing patterns. To assess differences between use of the foils during stress periods or just on consecutive nights and to determine a reasonable duration of using the foils, 28 patients were classified according to the Research Diagnostic Criteria for Temporomandibular Disorders (RDC/TMD) and were randomly assigned to wearing the 12 foils for six consecutive nights (alternately in the upper and lower jaw; “consecutive”) or six nights within one month following days of high stress (“stress”) in a crossover design. The sizes of the attrition areas were measured with ImageJ. Stress was evaluated using the Perceived Stress Scale. The Stress Coping Questionnaire (SVF-120) was used for assessing habitual stress coping strategies. Areas of attrition increased significantly from day 1/2 to 5/6, both for the upper and lower jaw. Molars in the mandible had significantly larger attrition areas than in the maxilla. No significant differences were detected between “consecutive” and “stress” phases. The foils were suitable for differentiating teeth more or less affected by bruxism and were able to show that areas of attrition increased with days, indicating that some adaptation takes place and several days of wearing the foils are required to show the full picture. However, no differences between low/moderate- and high-stress phases were detected. Full article

One of the most serious and dangerous ocular problems in premature infants is retinopathy of prematurity (ROP), a proliferative vascular disease. Ophthalmologists can use automatic computer-assisted diagnostic (CAD) tools to help them make a safe, accurate, and low-cost diagnosis of ROP. All previous CAD tools for ROP diagnosis use the original fundus images. Unfortunately, learning the discriminative representation from ROP-related fundus images is difficult. Textural analysis techniques, such as Gabor wavelets (GW), can demonstrate significant texture information that can help artificial intelligence (AI) based models to improve diagnostic accuracy. In this paper, an effective and automated CAD tool, namely GabROP, based on GW and multiple deep learning (DL) models is proposed. Initially, GabROP analyzes fundus images using GW and generates several sets of GW images. Next, these sets of images are used to train three convolutional neural networks (CNNs) models independently. Additionally, the actual fundus pictures are used to build these networks. Using the discrete wavelet transform (DWT), texture features retrieved from every CNN trained with various sets of GW images are combined to create a textural-spectral-temporal demonstration. Afterward, for each CNN, these features are concatenated with spatial deep features obtained from the original fundus images. Finally, the previous concatenated features of all three CNN are incorporated using the discrete cosine transform (DCT) to lessen the size of features caused by the fusion process. The outcomes of GabROP show that it is accurate and efficient for ophthalmologists. Additionally, the effectiveness of GabROP is compared to recently developed ROP diagnostic techniques. Due to GabROP’s superior performance compared to competing tools, ophthalmologists may be able to identify ROP more reliably and precisely, which could result in a reduction in diagnostic effort and examination time. Full article

Using a deep learning algorithm in the development of a computer-aided system for colon polyp detection is effective in reducing the miss rate. This study aimed to develop a system for colon polyp detection and classification. We used a data augmentation technique and conditional GAN to generate polyp images for YOLO training to improve the polyp detection ability. After testing the model five times, a model with 300 GANs (GAN 300) achieved the highest average precision (AP) of 54.60% for SSA and 75.41% for TA. These results were better than those of the data augmentation method, which showed AP of 53.56% for SSA and 72.55% for TA. The AP, mAP, and IoU for the 300 GAN model for the HP were 80.97%, 70.07%, and 57.24%, and the data increased in comparison with the data augmentation technique by 76.98%, 67.70%, and 55.26%, respectively. We also used Gaussian blurring to simulate the blurred images during colonoscopy and then applied DeblurGAN-v2 to deblur the images. Further, we trained the dataset using YOLO to classify polyps. After using DeblurGAN-v2, the mAP increased from 25.64% to 30.74%. This method effectively improved the accuracy of polyp detection and classification. Full article