Laparoscopic Ovarian-Sparing Surgery for the Management of Benign Ovarian Lesions in Pediatric Patients: A Retrospective Analysis.

INTRODUCTION: Laparoscopic ovarian-sparing surgery (OSS) is safe and effective management approach for benign ovarian lesions in pediatric patients. This study evaluates the outcomes of females younger than 18 years who underwent the OSS procedure between December 2013 and November 2022 at a single institution. MATERIAL AND METHODS: We conducted a retrospective analysis of records from 82 females who underwent OSS for ovarian lesions. OSS was performed based on diagnostic imaging that suggested the benign nature of the lesion. RESULTS: Of the 82 patients studied, 78 had unilateral lesions and 4 had bilateral synchronous lesions. The mean age was 14 years. The majority (62 cases) of the surgeries were laparoscopic, with 20 requiring conversion to open surgery due to factors such as indistinguishable edges and large size of the lesion. We identified 8 cases of ovarian torsion. The surgical specimens revealed that 46 were ovarian teratomas, 2 were granulosa cell tumors, 15 were cystadenomas, and 23 were functional cysts. There were no intraoperative complications. Two recurrences were observed in patients who were initially treated for bilateral ovarian teratomas. One patient developed a pelvic abscess. Additionally, three patients had metachronous ovarian tumors during the follow-up period. In patients followed with ultrasound imaging, the viable ovary was visualized in 83.6% of the cases (61 out of 73). CONCLUSION: Our findings demonstrate the effectiveness of laparoscopic OSS in preserving ovarian function and providing clinical benefits in patients with benign ovarian lesions. We recommend regular follow-up with ultrasound to exclude metachronous lesions or recurrence. LEVEL OF EVIDENCE: III.

Author Correction: Comparison of spectral and spatial denoising techniques in the context of High Definition FT-IR imaging hyperspectral data.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Influence of denoising on classification results in the context of hyperspectral data: High Definition FT-IR imaging.

Owing to the high information content about the biochemical composition of the sample, the implementation of Fourier-Transform Infrared Spectroscopy (FT-IR) in the clinic is currently under investigation by many researchers. Cancer biology with the use of histopathological models is one of the most explored application areas. Most of the publications show sensitivity of the method to be above 90%, however, it is still often not enough for clinical standards. Robust denoising techniques with an optimized classification model allow to shorten the experimental acquisition times which still are a bottleneck for FT-IR translation into the clinic. The main premise of this work is to evaluate denoising impact on classification results using spectral techniques: Savitzky Golay (SG), Wavelets (WV), Principal Component Analysis (PCA) and Minimum Noise Fraction (MNF); and spatial techniques: Deep Neural Network (DNN), Median Filter. Using denoising methods, especially MNF and PCA, gave significant improvement of the classification and prediction results. Moreover, the increase in pixel level accuracy for High Definition data (1.1 µm projected pixel size) was found to be dependent on the complexity of the histopathological class and reached even 43-44% level, while core level increase reached around 28%. Moreover, we investigated the impact of denoising methods on the spectral input to better understand the mechanism of such large improvement. The results presented here highlight the benefits and the importance of proper denoising for classification purposes of FT-IR imaging data.

Denoising influence on discrete frequency classification results for quantum cascade laser based infrared microscopy.

Currently, there is great interest in bringing the application of IR spectroscopy into the clinic. This however will require a significant reduction in measurement time as Fourier Transform Infrared (FT-IR) imaging takes hours to days to scan a clinically relevant specimen. A potential remedy for this issue is the use of Quantum Cascade Laser Infrared (QCL IR) microscopy performed in Discrete Frequency (DF) mode for maximum speed gain. This gain could be furthermore improved by applying a proper denoising algorithm that takes into account the specific data structure. We have recently compared spectral and spatial denoising techniques in the context of Fourier Transform IR (FT-IR) imaging and showed that the optimal methods depend heavily on the exact data structure. In general multivariate denoising methods such as Principal Component Analysis (PCA) and Minimum Noise Fraction (MNF) are the most effective for a dataset containing multiple bands. Histologic classification of QCL IR images of pancreatic tissue using Random Forest was therefore performed to investigate which denoising schemes are the most optimal for such experimental data structure. This work is the first to show the effects of denoising on classification accuracy of QCL data and is likely to be transferable to other QCL microscopes and other modalities using DF imaging, e.g. AFM-IR or CARS/SRS imaging.

Comparison of spectral and spatial denoising techniques in the context of High Definition FT-IR imaging hyperspectral data.

The recent emergence of High Definition (HD) FT-IR and Quantum Cascade Laser (QCL) Microscopes elevated the IR imaging field very close to clinical timescales. However, the speed of acquisition and data quality are still the critical factors in reaching the clinic. Denoising offers aide in both aspects if performed properly. However, there is a lack of a direct comparison of the efficiency of denoising techniques in IR imaging in general. To achieve such comparison within a rigorous framework and obtaining the critical information about signal loss, a simulated dataset strongly bound by experimental parameters was created. Using experimental structural and spectral information and experimental noise levels data as an input for the simulation, a direct comparison of spatial (Fourier transform, Mean Filter, Weighted Mean Filter, Gauss Filter, Median Filter, spatial Wavelets and Deep Neural Networks) and spectral (Savitzky-Golay, Fourier transform, Principal Component Analysis, Minimum Noise Fraction and spectral Wavelets) denoising schemes was enabled. All of these techniques were compared on the simulated dataset, taking into account SNR gain, signal distortion and sensitivity to tuning parameters as comparison metrics. Later, the best techniques were applied to experimental data for validation. The results presented here clearly show the benefit of using hyperspectral denoising schemes such as PCA and MNF which outperform other methods.

Review on Retinal Gliosis Illustrated with a Series of Massive Glioses and Focal Nodular Gliosis Cases in Regard to Potential Pitfalls of Ocular Reactive Tumor-like Lesions of this Type.

This paper presents a review on retinal gliosis illustrated by series of three cases of patients (a 39-year-old man and a 35-year-old woman with massive retinal gliosis (MRG) and a 51-year-old man with truly focal nodular gliosis of retina) with intraocular tumor-like masses and loss of vision, who recently suffered from painful inflammation of eyeball and who classically had a history of remote ocular trauma, onset of blindness early in lifetime or gradual but progressive loss of sight. The diagnosis of this pathological entity is given for the lesions that are composed of GFAP strongly positive, elongated, fusiform cells consistent with fibrillary astrocytes. As illustrated in cases from our pathological practice, PAS gave positive patchy disseminated reaction in form of cellular densely purplish granules in minority of cells representing glycogen storing. This feature could be consistent with PAS-positive Müller cells that also constitute retinal gliosis as one of cellular components of normal retina that is induced to reactive proliferation. Thus, the paper presents histological background and differential diagnosis of the entity.

Malignant gastrointestinal neuroectodermal tumor (clear cell sarcoma-like tumor of the gastrointestinal tract) of the small intestine in a 12-year-old boy.

The aim of this paper is a clinical and anatomopathological demonstration of a malignant lesion, a gastrointestinal neuroectodermal tumor (GNET), as an exceedingly rare cause of ileus in the pediatric population. Specifically, we present the case of a 12-year-old boy who showed dramatic weight loss, hypochromic anemia, fever, dehydration, exaggerated granulation of the terminal ileum, and mechanical ileus due to the obstruction by an intramural tumor of the small intestine. A 50cm-long part of the small intestine with pathological stricture was surgically removed, sampled and routinely fixed and stained with hematoxylin and eosin. The additional immunostains that were preformed were: PAS, S-100, HMB-45, NSE, LCA, CK AE1 / AE3, desmin, SMA, vimentin, CD99, NSE, synaptophysin, WT-1, calretinin, and DOG-1. Moreover, fluorescent in situ hybridization (FISH) with the EWSR1 Break Apart FISH Probe was applied. The neoplasm was composed of nests and alveolar patterns of frankly malignant clear cells with immunoreactivity to S-100, vimentin, and CD 99. The FISH technique detected chromosomal breaking at 22q12. The tumor metastasized to both the mesenteric lymph nodes and a number of hepatic segments. With several chemotherapy protocols, repeat laparotomies, and liver thermal ablations, the patient had a 1.5-year-long survival from the moment of diagnosis. The diagnosis of this malignancy requires both histopathological evaluation and molecular analysis, and the follow-up is based on careful clinical imaging of the neoplastic spread in order to apply proper surgical and oncological treatments. In conclusion, the clinical course of GNET was highly aggressive.

Adenoid basal carcinoma-like tumor combined with invasive squamous cell carcinoma foci of uterine cervix - a case report of 55-year-old woman with literature review.

BACKGROUND: Adenoid basal carcinoma (ABC) of uterine cervix is an extraordinary example of carcinoma with both basal and glandular cell types. Here we present such a case of ABC combined with invasive squamous cell carcinoma (SCC) of 55-year-old woman. METHODS: The tumor was stained with Hematoxylin-Eosin (HE), Mucicarmine, PAS/Alcian Blue, CK AE1/AE3, CK7, CD117 and Ki67. RESULTS: The whitish-grey 1 cm in-depth infiltration of endocervix was composed of infiltrative coalescing areas of CK AE1/AE3 positive carcinoma with peripheral palisading of basal cell type with spaces lined by Mucicarmine- and Alcian Blue-positive benign looking, glandular epithelium. There were also foci of apparently malignant squamous epithelium with evident dyskeratosis. Thus, a lesion was diagnosed of adenoid basal carcinoma combined with invasive squamous cell carcinoma foci of uterine cervix. The tumor was further CD117 negative what favored diagnosis of ABC over adenoid cystic carcinoma (ACC). There were rare mitoses on HE slides but 60% of all tumor cells were positive for Ki67 that would partially contradict reported benign nature of ABC lesion. Moreover, tumor was CK7-positive and this finding was controversial and according to one report favored diagnosis of ABC-like adenosquamous carcinoma (ACC). Due to CK7 positivity and high index of Ki67, the neoplasm was re-classified as adenoid basal carcinoma-like tumor. CONCLUSIONS: It seems reasonable to treat the patient in the same manner as in case of pure simple invasive squamous cell carcinoma because much more aggressive, minor component of invasive SCC was found within ABC in our case.