Breast-conserving surgery (BCS) followed by radiotherapy is preferred for early-stage breast cancer because its survival rate is equivalent to that of mastectomy. Achieving negative surgical margins in BCS is crucial to minimize the risk of recurrence. Intraoperative ultrasound (IOUS) enhances surgical accuracy, but its efficacy is operator dependent. This study aimed to compare the success of achieving negative margins using IOUS between an experienced breast surgeon and general surgical residents and to evaluate the learning curve for the residents. A prospective study involving 96 patients with BCS who underwent IOUS guidance was conducted. Both the breast surgeon and residents assessed the surgical margins using IOUS, with the breast surgeon making the final margin adequacy decision. Permanent histopathological analysis was used to confirm the status of the margins and was considered the gold standard for comparison. The breast surgeon accurately assessed the margin status in all 96 cases (100% accuracy), with 93 negative and three positive margins. All of these were ductal carcinomas in situ. Initially, the residents demonstrated low accuracy rates in predicting margin positivity using intraoperative ultrasonography. However, the learning curves of the three residents demonstrated that, with an average 12th case onwards, a significant improvement in the cumulative accuracy rates was observed, which reached the level of the breast surgeon. IOUS is an effective tool for accurately predicting the margin status in BCS, with an acceptable learning curve for novice surgeons. Training and experience are pivotal for optimizing surgical outcomes. These findings support the integration of IOUS training into surgical education programs to enhance proficiency and improve patient outcomes.

BACKGROUND: Intraoperative ultrasound (IOUS) is a profitable tool for neurosurgical procedures\' assistance, especially in neuro-oncology. It is a rapid, ergonomic and reproducible technique. However, its known handicap is a steep learning curve for neurosurgeons. Here, we describe an interesting postoperative analysis that provides extra feedback after surgery, accelerating the learning process.
METHODS: We conducted a descriptive retrospective unicenter study including patients operated from intra-axial brain tumors using neuronavigation (Curve, Brainlab) and IOUS (BK-5000, BK medical) guidance. All patients had preoperative Magnetic Resonance Imaging (MRI) prior to tumor resection. During surgery, 3D neuronavigated IOUS studies (n3DUS) were obtained through craniotomy N13C5 transducer\'s integration to the neuronavigation system. At least two n3DUS studies were obtained: prior to tumor resection and at the resection conclusion. A postoperative MRI was performed within 48 h. MRI and n3DUS studies were posteriorly fused and analyzed with Elements (Brainlab) planning software, permitting two comparative analyses: preoperative MRI compared to pre-resection n3DUS and postoperative MRI to post-resection n3DUS. Cases with incomplete MRI or n3DUS studies were withdrawn from the study.
RESULTS: From April 2022 to March 2024, 73 patients were operated assisted by IOUS. From them, 39 were included in the study. Analyses comparing preoperative MRI and pre-resection n3DUS showed great concordance of tumor volume (p < 0,001) between both modalities. Analysis comparing postoperative MRI and post-resection n3DUS also showed good concordance in residual tumor volume (RTV) in cases where gross total resection (GTR) was not achieved (p < 0,001). In two cases, RTV detected on MRI that was not detected intra-operatively with IOUS could be reviewed in detail to recheck its appearance.
CONCLUSIONS: Post-operative comparative analyses between IOUS and MRI is a valuable tool for novel ultrasound users, as it enhances the amount of feedback provided by cases and could accelerate the learning process, flattening this technique\'s learning curve.

Surgery is a crucial component of pediatric cancer treatment, but conventional methods may lack precision. Image-guided surgery, including fluorescent and radioguided techniques, offers promise for enhancing tumor localization and facilitating precise resection. Intraoperative molecular imaging utilizes agents like indocyanine green to direct surgeons to occult deposits of tumor and to delineate tumor margins. Next-generation agents target tumors directly to improve specificity. Radioguided surgery, employing tracers like metaiodobenzylguanidine (MIBG), complements fluorescent techniques by allowing for detection of tumors at a greater depth. Dual-labeled agents combining both modalities are under development. Three-dimensional modeling and virtual/augmented reality aid in preoperative planning and intraoperative guidance. The above techniques show great promise to benefit patients with pediatric tumors, and their continued development will almost certainly improve surgical outcomes.

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Objective - Addressing the challenges that come with identifying and delineating brain tumours in intraoperative ultrasound. Our goal is to both qualitatively and quantitatively assess the interobserver variation, amongst experienced neuro-oncological intraoperative ultrasound users (neurosurgeons and neuroradiologists), in detecting and segmenting brain tumours on ultrasound. We then propose that, due to the inherent challenges of this task, annotation by localisation of the entire tumour mass with a bounding box could serve as an ancillary solution to segmentation for clinical training, encompassing margin uncertainty and the curation of large datasets. Methods - 30 ultrasound images of brain lesions in 30 patients were annotated by 4 annotators - 1 neuroradiologist and 3 neurosurgeons. The annotation variation of the 3 neurosurgeons was first measured, and then the annotations of each neurosurgeon were individually compared to the neuroradiologist\'s, which served as a reference standard as their segmentations were further refined by cross-reference to the preoperative magnetic resonance imaging (MRI). The following statistical metrics were used: Intersection Over Union (IoU), Sørensen-Dice Similarity Coefficient (DSC) and Hausdorff Distance (HD). These annotations were then converted into bounding boxes for the same evaluation. Results - There was a moderate level of interobserver variance between the neurosurgeons [ I o U : 0.789 , D S C : 0.876 , H D : 103.227 ] and a larger level of variance when compared against the MRI-informed reference standard annotations by the neuroradiologist, mean across annotators [ I o U : 0.723 , D S C : 0.813 , H D : 115.675 ] . After converting the segments to bounding boxes, all metrics improve, most significantly, the interquartile range drops by [ I o U : 37 % , D S C : 41 % , H D : 54 % ] . Conclusion - This study highlights the current challenges with detecting and defining tumour boundaries in neuro-oncological intraoperative brain ultrasound. We then show that bounding box annotation could serve as a useful complementary approach for both clinical and technical reasons.

Laparoscopic cholecystectomy is one of the most frequently performed operations by general surgeons, with up to 1 million cholecystectomies performed annually in the United States alone. Despite familiarity, common bile duct injury occurs in no less than 0.2% of cholecystectomies, with significant associated morbidity. Understanding biliary anatomy, surgical techniques, pitfalls, and bailout maneuvers is critical to optimizing outcomes when encountering the horrible gallbladder. This article describes normal and aberrant biliary anatomy, complicated cholelithiasis, ways to recognize cholecystitis, and considerations of surgical approach.

OBJECTIVE: Registration and segmentation of magnetic resonance (MR) and ultrasound (US) images could play an essential role in surgical planning and resectioning brain tumors. However, validating these techniques is challenging due to the scarcity of publicly accessible sources with high-quality ground truth information. To this end, we propose a unique set of segmentations (RESECT-SEG) of cerebral structures from the previously published RESECT dataset to encourage a more rigorous development and assessment of image-processing techniques for neurosurgery.
METHODS: The RESECT database consists of MR and intraoperative US (iUS) images of 23 patients who underwent brain tumor resection surgeries. The proposed RESECT-SEG dataset contains segmentations of tumor tissues, sulci, falx cerebri, and resection cavity of the RESECT iUS images. Two highly experienced neurosurgeons validated the quality of the segmentations.
METHODS: Segmentations are provided in 3D NIFTI format in the OSF open-science platform: https://osf.io/jv8bk.
CONCLUSIONS: The proposed RESECT-SEG dataset includes segmentations of real-world clinical US brain images that could be used to develop and evaluate segmentation and registration methods. Eventually, this dataset could further improve the quality of image guidance in neurosurgery.

OBJECTIVE: Pediatric low-grade gliomas (pLGG) are the most common brain tumors in children and achieving complete resection (CR) in pLGG is the most important prognostic factor. There are multiple intraoperative tools to optimize the extent of resection (EOR). This article investigates and discusses the role of intraoperative ultrasound (iUS) and intraoperative magnetic resonance imaging (iMRI) in the surgical treatment of pLGG.
METHODS: The tumor registries at Tuebingen, Rome and Pretoria were searched for pLGG with the use of iUS and data on EOR. The tumor registries at Liverpool and Tuebingen were searched for pLGG with the use of iMRI where preoperative CR was the surgical intent. Different iUS and iMRI machines were used in the 4 centers.
RESULTS: We included 111 operations which used iUS and 182 operations using iMRI. Both modalities facilitated intended CR in hemispheric supra- and infratentorial location in almost all cases. In more deep-seated tumor location like supratentorial midline tumors, iMRI has advantages over iUS to visualize residual tumor. Functional limitations limiting CR arising from eloquent involved or neighboring brain tissue apply to both modalities in the same way. In the long-term follow-up, both iUS and iMRI show that achieving a complete resection on intraoperative imaging significantly lowers recurrence of disease (chi-square test, p < 0.01).
CONCLUSIONS: iUS and iMRI have specific pros and cons, but both have been proven to improve achieving CR in pLGG. Due to advances in image quality, cost- and time-efficiency, and efforts to improve the user interface, iUS has emerged as the most accessible surgical adjunct to date to aid and guide tumor resection. Since the EOR has the most important effect on long-term outcome and disease control of pLGG in most locations, we strongly recommend taking all possible efforts to use iUS in any surgery, independent of intended resection extent and iMRI if locally available.

BACKGROUND: Although the use of transcranial ultrasound dates to the mid-20th century, the main purpose of this research work is to standardize its use in the resection of brain tumors. This is due to its wide availability, low cost, lack of contraindications, and absence of harmful effects for the patient and medical staff, along with the possibility of real-time verification of the complete resection of tumor lesions and minimization of vascular injuries or damage to adjacent structures.
METHODS: A retrospective study was conducted from June to December 2022. The study included eight patients (three men and five women) aged between 32 and 76 years. Histological examination revealed two high-grade gliomas, one low-grade glioma, and five metastatic lesions.
RESULTS: The low-grade glioma appeared as a homogeneously echogenic structure and easily distinguishable from brain parenchyma, whereas metastases and high-grade gliomas showed higher echogenicity, being identified as malignant lesions due to areas of low echogenicity necrosis and peritumoral edema identified as a hyperechogenic structure.
CONCLUSIONS: The use of intraoperative transcranial ultrasound constitutes an important tool for neurosurgeons during tumor resection. Although it is easy to use, intraoperative ultrasound requires a relatively short learning curve and a good understanding of the fundamentals of ultrasound. Its main advantage over neuronavigation is that it is not affected by the \"brain shift\" phenomenon that commonly occurs during tumor resection, since the ultrasound images are updated during surgery.

During neurosurgical procedures, the neuro-navigation system\'s accuracy is affected by the brain shift phenomenon. One popular strategy is to compensate for brain shift using intraoperative ultrasound (iUS) registration with pre-operative magnetic resonance (MR) scans. This requires a satisfactory multimodal image registration method, which is challenging due to the low image quality of ultrasound and the unpredictable nature of brain deformation during surgery. In this paper, we propose an automatic unsupervised end-to-end MR-iUS registration approach named the Dual Discriminator Bayesian Generative Adversarial Network (D2BGAN). The proposed network consists of two discriminators and a generator optimized by a Bayesian loss function to improve the functionality of the generator, and we add a mutual information loss function to the discriminator for similarity measurements. Extensive validation was performed on the RESECT and BITE datasets, where the mean target registration error (mTRE) of MR-iUS registration using D2BGAN was determined to be 0.75 ± 0.3 mm. The D2BGAN illustrated a clear advantage by achieving an 85% improvement in the mTRE over the initial error. Moreover, the results confirmed that the proposed Bayesian loss function, rather than the typical loss function, improved the accuracy of MR-iUS registration by 23%. The improvement in registration accuracy was further enhanced by the preservation of the intensity and anatomical information of the input images.