Adaptive segmentation-to-survival learning for survival prediction from multi-modality medical images.

Early survival prediction is vital for the clinical management of cancer patients, as tumors can be better controlled with personalized treatment planning. Traditional survival prediction methods are based on radiomics feature engineering and/or clinical indicators (e.g.

Presenilin-1 mutation position influences amyloidosis, small vessel disease, and dementia with disease stage.

Introduction: Amyloidosis, including cerebral amyloid angiopathy, and markers of small vessel disease (SVD) vary across dominantly inherited Alzheimer's disease (DIAD) presenilin-1 (PSEN1) mutation carriers. We investigated how mutation position relative to codon 200 (pre-/postcodon 200) influences these pathologic features and dementia at different stages.

Methods: Individuals from families with known PSEN1 mutations (n = 393) underwent neuroimaging and clinical assessments.

Robotic Anatomical Pulmonary Resections: An Australian Experience.

Background: Robotic thoracic surgery is a minimally invasive technique that allows the surgeon to perform delicate, accurate surgical manoeuvres within the chest cavity without rib spreading. Previous studies have suggested potential benefits of the robotic platform in nodal upstaging due to its versatility, seven degrees of freedom of movement, and superior vision. However, there is currently a paucity of robust clinical data from Australia.

Late-onset epilepsy with cognitive symptoms: Comparison of cognitive and imaging profiles with probable Alzheimer's disease.

Objective: We aimed to (i) compare the clinical, neuropsychological, and neuroimaging characteristics of unprovoked late-onset epilepsy (LOE) patients with cognitive symptoms against probable Alzheimer's disease (AD) patients; (ii) clarify how neurodegeneration and other processes could be implicated in the cognitive symptoms of unprovoked LOE patients; and (iii) characterize the longitudinal trajectory of unprovoked LOE patients with cognitive symptoms.

Methods: Twenty-six unprovoked LOE patients with cognitive symptoms and 26 probable AD were retrospectively recruited from epilepsy and memory clinics at a single tertiary referral center. The patients underwent comprehensive clinical, neuropsychological, and Fluorodeoxyglucose PET-CT assessments.

CT-based Radiogenomics Framework for COVID-19 Using ACE2 Imaging Representations.

Coronavirus disease 2019 (COVID-19) is caused by Severe Acute Respiratory Syndrome Coronavirus 2 which enters the body via the angiotensin-converting enzyme 2 (ACE2) and altering its gene expression. Altered ACE2 plays a crucial role in the pathogenesis of COVID-19. Gene expression profiling, however, is invasive and costly, and is not routinely performed.

Synthesis and structure-activity relationship (SAR) studies of 1,2,3-triazole, amide, and ester-based benzothiazole derivatives as potential molecular probes for tau protein.

The pyridinyl-butadienyl-benzothiazole (PBB3 15) scaffold was used to develop tau ligands with improved and properties for imaging applications to provide insights into the etiology and characteristics of Alzheimer's disease. The photoisomerisable -butadiene bridge of PBB3 was replaced with 1,2,3-triazole, amide, and ester moieties and fluorescence staining studies revealed that triazole derivatives showed good visualisation of Aβ plaques, but failed to detect the neurofibrillary tangles (NFTs) in human brain sections. However, NFTs could be observed using the amide 110 and ester 129.

Pearls & Oy-sters: Huntington Disease Presenting as Primary Progressive Aphasia: A Case of Semantics.

We present a case of semantic variant primary progressive aphasia as the presenting feature in a patient with Huntington disease (HD). The patient initially developed progressive language impairment including impaired naming and object knowledge and single-word comprehension and then developed chorea and behavioral changes. An MRI of the brain showed left anterior temporal lobe and hippocampal atrophy.

PSMA PET-CT in the Diagnosis and Staging of Prostate Cancer.

Prostate cancer is the most common cancer and the second leading cause of cancer death in men. The imaging assessment and treatment of prostate cancer has vastly improved over the past decade. The introduction of PSMA PET-CT has improved the detection of loco-regional and metastatic disease.

Deep multi-scale resemblance network for the sub-class differentiation of adrenal masses on computed tomography images.

Objective: The accurate classification of mass lesions in the adrenal glands ('adrenal masses'), detected with computed tomography (CT), is important for diagnosis and patient management. Adrenal masses can be benign or malignant and benign masses have varying prevalence. Classification methods based on convolutional neural networks (CNNs) are the state-of-the-art in maximizing inter-class differences in large medical imaging training datasets.

Enhancing medical image registration via appearance adjustment networks.

Deformable image registration is fundamental for many medical image analyses. A key obstacle for accurate image registration lies in image appearance variations such as the variations in texture, intensities, and noise. These variations are readily apparent in medical images, especially in brain images where registration is frequently used.

Graph-Based Intercategory and Intermodality Network for Multilabel Classification and Melanoma Diagnosis of Skin Lesions in Dermoscopy and Clinical Images.

The identification of melanoma involves an integrated analysis of skin lesion images acquired using clinical and dermoscopy modalities. Dermoscopic images provide a detailed view of the subsurface visual structures that supplement the macroscopic details from clinical images. Visual melanoma diagnosis is commonly based on the 7-point visual category checklist (7PC), which involves identifying specific characteristics of skin lesions.

Biomarker clustering in autosomal dominant Alzheimer's disease.

Introduction: As the number of biomarkers used to study Alzheimer's disease (AD) continues to increase, it is important to understand the utility of any given biomarker, as well as what additional information a biomarker provides when compared to others.

Methods: We used hierarchical clustering to group 19 cross-sectional biomarkers in autosomal dominant AD. Feature selection identified biomarkers that were the strongest predictors of mutation status and estimated years from symptom onset (EYO).

Synthesis of Ga-radiopharmaceuticals using both generator-derived and cyclotron-produced Ga as exemplified by [Ga]Ga-PSMA-11 for prostate cancer PET imaging.

[Ga]Ga-PSMA-11, a urea-based peptidomimetic, is a diagnostic radiopharmaceutical for positron emission tomography (PET) imaging that targets the prostate-specific membrane antigen (PSMA). The recent Food and Drug Administration approval of [Ga]Ga-PSMA-11 for PET imaging of patients with prostate cancer, expected follow-up approval of companion radiotherapeutics (e.g.

Fused feature signatures to probe tumour radiogenomics relationships.

Radiogenomics relationships (RRs) aims to identify statistically significant correlations between medical image features and molecular characteristics from analysing tissue samples. Previous radiogenomics studies mainly relied on a single category of image feature extraction techniques (ETs); these are (i) handcrafted ETs that encompass visual imaging characteristics, curated from knowledge of human experts and, (ii) deep ETs that quantify abstract-level imaging characteristics from large data. Prior studies therefore failed to leverage the complementary information that are accessible from fusing the ETs.

Hyper-fusion network for semi-automatic segmentation of skin lesions.

Segmentation of skin lesions is an important step for imaging-based clinical decision support systems. Automatic skin lesion segmentation methods based on fully convolutional networks (FCNs) are regarded as the state-of-the-art for accuracy. When there are, however, insufficient training data to cover all the variations in skin lesions, where lesions from different patients may have major differences in size/shape/texture, these methods failed to segment the lesions that have image characteristics, which are less common in the training datasets.

Predicting distant metastases in soft-tissue sarcomas from PET-CT scans using constrained hierarchical multi-modality feature learning.

Positron emission tomography-computed tomography (PET-CT) is regarded as the imaging modality of choice for the management of soft-tissue sarcomas (STSs). Distant metastases (DM) are the leading cause of death in STS patients and early detection is important to effectively manage tumors with surgery, radiotherapy and chemotherapy. In this study, we aim to early detect DM in patients with STS using their PET-CT data.

Malignant Peritoneal Mesothelioma With EWSR1-ATF1 Fusion: A Case Report.

Malignant mesothelioma with EWSR1-ATF1 fusion is a rare malignancy described in young adults without asbestos exposure. To the best of our knowledge, outcomes to local and systemic therapies for this subtype of malignant mesothelioma have not been described. This case report describes the clinical course of a 19-year-old man diagnosed with malignant peritoneal mesothelioma with EWSR1-ATF1 fusion localized to the abdomen.

Imaging of patients with multiple myeloma and associated plasma cell disorders: consensus practice statement by the Medical Scientific Advisory Group to Myeloma Australia.

Imaging modalities for multiple myeloma (MM) have evolved to enable earlier detection of disease. Furthermore, the diagnosis of MM requiring therapy has recently changed to include disease prior to bone destruction, specifically the detection of focal bone lesions. Focal lesions are early, abnormal areas in the bone marrow, which may signal the development of subsequent lytic lesions that typically occur within the next 18-24 months.