Reproducibility in Radiomics: A Comparison of Feature Extraction Methods and Two Independent Datasets.

Radiomics involves the extraction of information from medical images that are not visible to the human eye. There is evidence that these features can be used for treatment stratification and outcome prediction. However, there is much discussion about the reproducibility of results between different studies.

Is radiomics a useful addition to magnetic resonance imaging in the preoperative classification of PitNETs?

Background: The WHO 2021 introduced the term pituitary neuroendocrine tumours (PitNETs) for pituitary adenomas and incorporated transcription factors for subtyping, prompting the need for fresh diagnostic methods. Current biomarkers struggle to distinguish between high- and low-risk non-functioning PitNETs. We explored if radiomics can enhance preoperative decision-making.

Multi-centre radiomics for prediction of recurrence following radical radiotherapy for head and neck cancers: Consequences of feature selection, machine learning classifiers and batch-effect harmonization.

Background And Purpose: Radiomics models trained with limited single institution data are often not reproducible and generalisable. We developed radiomics models that predict loco-regional recurrence within two years of radiotherapy with private and public datasets and their combinations, to simulate small and multi-institutional studies and study the responsiveness of the models to feature selection, machine learning algorithms, centre-effect harmonization and increased dataset sizes.

Materials And Methods: 562 patients histologically confirmed and treated for locally advanced head-and-neck cancer (LA-HNC) from two public and two private datasets; one private dataset exclusively reserved for validation.

Framework for Machine Learning of CT and PET Radiomics to Predict Local Failure after Radiotherapy in Locally Advanced Head and Neck Cancers.

Context: Cancer Radiomics is an emerging field in medical imaging and refers to the process of converting routine radiological images that are typically qualitatively interpreted to quantifiable descriptions of the tumor phenotypes and when combined with statistical analytics can improve the accuracy of clinical outcome prediction models. However, to understand the radiomic features and their correlation to molecular changes in the tumor, first, there is a need for the development of robust image analysis methods, software tools and statistical prediction models which is often limited in low- and middle-income countries (LMIC).

Aims: The aim is to build a framework for machine learning of radiomic features of planning computed tomography (CT) and positron emission tomography (PET) using open source radiomics and data analytics platforms to make it widely accessible to clinical groups.

Accuracy of the freehand (fennell) technique using a uniform entry point and sagittal trajectory for insertion of thoracic pedicle screws: A computed tomography-based virtual simulation study.

Background: Thoracic spine has complex pedicle anatomy with a narrow canal diameter which makes pedicle screw insertion challenging. Fennell et al. have described a simple freehand technique of thoracic pedicle screw placement.

Patient-specific interactive software module for virtual preoperative planning and visualization of pedicle screw entry point and trajectories in spine surgery.

Background: Lumbar pedicle screw insertion involves a steep learning curve for novice spine surgeons and requires image guidance or navigation. Small volume centers may be handicapped by the lack of cost-effective user-friendly tools for preoperative planning, guidance, and decision making.

Objective: We describe a patient-specific interactive software module, pedicle screw simulator (PSS), for virtual preoperative planning to determine the entry point and visualize the trajectories of pedicle screws.

Hybrid positron emission tomography segmentation of heterogeneous lung tumors using 3D Slicer: improved GrowCut algorithm with threshold initialization.

This paper presents an improved GrowCut (IGC), a positron emission tomography-based segmentation algorithm, and tests its clinical applicability. Contrary to the traditional method that requires the user to provide the initial seeds, the IGC algorithm starts with a threshold-based estimate of the tumor and a three-dimensional morphologically grown shell around the tumor as the foreground and background seeds, respectively. The repeatability of IGC from the same observer at multiple time points was compared with the traditional GrowCut algorithm.

Adaptive threshold segmentation of pituitary adenomas from FDG PET images for radiosurgery.

In this study we have attempted to optimize a PET based adaptive threshold seg- mentation method for delineating small tumors, particularly in a background of high tracer activity. The metabolic nature of pituitary adenomas and the constraints of MRI imaging in the postoperative setting to delineate these tumors during radio- surgical procedures motivated us to develop this method. Phantom experiments were done to establish a relationship between the threshold required for segmenting the PET images and the target size and the activity concentration within the target in relation to its background.

PET imaging of EGFR expression in nude mice bearing MDA-MB-468, a human breast adenocarcinoma.

Background And Objective: Cetuximab is a monoclonal antibody that binds to and inhibits the epidermal growth factor receptor (EGFR). EGFR overexpression has been observed in a subset of breast cancers. The purpose of this study was to evaluate 64Cu-labeled cetuximab as an imaging agent using MDA-MB-468 breast cancer cells.

Targeting apoptosis for optical imaging of infection.

Purpose: Infection is ubiquitous and a major cause of morbidity and mortality. The most reliable method for localizing infection requires radiolabeling autologous white blood cells ex vivo. A compound that can be injected directly into a patient and can selectively image infectious foci will eliminate the drawbacks.

Three dimensional projection environment for molecular design and surgical simulation.

We are developing agents for positron emission tomography (PET) imaging of cancer gene mRNA expression and software to fuse mRNA PET images with anatomical computerized tomography (CT) images to enable volumetric (3D) haptic (touch-and-feel) simulation of pancreatic cancer and surrounding organs prior to surgery in a particular patient. We have identified a novel ligand specific for epidermal growth factor receptor (EGFR) to direct PET agent uptake specifically into cancer cells, and created a volumetric haptic surgical simulation of human pancreatic cancer reconstructed from patient CT data. Young's modulus and the Poisson ratio for each tissue will be adjusted to fit the experience of participating surgeons.

Apoptotic abscess imaging with 99mTc-HYNIC-rh-Annexin-V.

Abscess formation causes systemic and localized up-regulation of neutrophil [polymorphonuclear leukocytes (PMNs)] signaling pathways. In the abscess, following bacterial ingestion or PMN activation by inflammatory mediators, PMN apoptosis is elevated and leads to the externalization of phosphatidylserine. Annexin-V (AnxV) has been shown to have high affinity to externalized phosphatidylserine.

Imaging spontaneous MMTVneu transgenic murine mammary tumors: targeting metabolic activity versus genetic products.

Unlabelled: Despite the great strides made in imaging breast cancer (BC) in humans, the current imaging modalities miss up to 30% of BC, do not distinguish malignant lesions from benign ones, and require histologic examinations for which invasive biopsy must be performed. Annually in the United States, approximately 5.6 million biopsies find benign lesions.

In-house preparation of iodine -131 metaiodo benzyl guanidine for scintigraphy of neuroendocrine tumors. Fourteen years experience in South India.

Iodine-131 metaiodobenzyl guanidine ((131)I-MIBG) is routinely used for imaging and treatment of neuroendocrine tumors (NET). As the commercially available radiopharmaceutical was very expensive, we developed an in-house method of labeling MIBG with (131)I in 1993. A total of 247 batches of (131)I-MIBG were prepared and used in our hospital between April 1993 and September 2006.