Background: Ischemic heart disease (IHD) is the most common cause of heart failure (HF); however, the role of revascularization in these patients is still unclear. Consensus on proper use of cardiac imaging to help determine which candidates should be considered for revascularization has been hindered by the absence of clinical studies that objectively and prospectively compare the prognostic information of each test obtained using both standard and advanced imaging. Methods/Design: This paper describes the design and methods to be used in the Alternative Imaging Modalities in Ischemic Heart Failure (AIMI-HF) multi-center trial. The primary objective is to compare the effect of HF imaging strategies on the composite clinical endpoint of cardiac death, myocardial infarction (MI), cardiac arrest and re-hospitalization for cardiac causes. In AIMI-HF, patients with HF of ischemic etiology (n = 1,261) will follow HF imaging strategy algorithms according to the question(s) asked by the physicians (for example, Is there ischemia and/or viability?), in agreement with local practices. Patients will be randomized to either standard (SPECT, Single photon emission computed tomography) imaging modalities for ischemia and/or viability or advanced imaging modalities: cardiac magnetic resonance imaging (CMR) or positron emission tomography (PET). In addition, eligible and consenting patients who could not be randomized, but were allocated to standard or advanced imaging based on clinical decisions, will be included in a registry. Discussion: AIMI-HF will be the largest randomized trial evaluating the role of standard and advanced imaging modalities in the management of ischemic cardiomyopathy and heart failure. This trial will complement the results of the Surgical Treatment for Ischemic Heart Failure (STICH) viability substudy and the PET and Recovery Following Revascularization (PARR-2) trial. The results will provide policy makers with data to support (or not) further investment in and wider dissemination of alternative ‘advanced’ imaging technologies. Trial registration: NCT01288560

Trastuzumab (T) and anthracycline (A)-based chemotherapy is considered the standard of care in human epidermal growth factor receptor-2+ overexpressing breast cancer, but requires monitoring for known cardiotoxicity using left ventricular (LV) ejection fraction (EF) every 3–4 months during treatment. It is not conclusively established whether diastolic dysfunction (DD) precedes LVEF decrease in patients developing trastuzumab-induced cardiotoxicity (TIC). The aim was to elucidate whether DD precedes LVEF decrease in trastuzumab-treated patients being monitored with radionuclide multigated acquisition for TIC. Patients treated with T±A-based chemotherapy who had undergone multigated acquisition were selected by date range (January 2006–September 2015). Up to four scans were analyzed per patient: (a) pre-A therapy, (b) pre-T therapy, (c) 4 months into T therapy, and (d) at end of T therapy. Baseline referred to the first scan of each patient (i.e. pre-A or pre-T). LV systolic and DD were defined as follows: EF less than 50% or a 10-point decrease from baseline and LV peak filling rate (PFR) less than 2.5 end-diastolic volume/s and time to peak LV filling rates (TPFR) greater than 180 ms, respectively. A total of 202 patients were screened for this study, of whom 153 had received A therapy (5.1±4.1 months duration) before T, 192 had 4 months of follow-up data, and 146 had 4 months of follow-up data and beyond (10.5±5.0 months). LVEF decreased with A and T therapy (P0.1), nor did TPFR (P>0.3). Patients with normal diastolic function at baseline receiving trastuzumab±anthracycline adjuvant therapy may develop DD before SD, therefore offering an opportunity for early referral to cardiologists to optimize cardiovascular risk factors and manage cardiotoxicity.

Ventilation-perfusion (V/Q) lung scans constitute one of the oldest nuclear medicine procedures, remain one of the few studies performed in the acute setting, and are amongst the few performed in the emergency setting. V/Q studies have witnessed a long fluctuation in adoption rates in parallel to continuous advances in image processing and computer vision techniques. This review provides an overview on the status of artificial intelligence (AI) in V/Q scintigraphy. To clearly assess the past, current, and future role of AI in V/Q scans, we conducted a systematic Ovid MEDLINE(R) literature search from 1946 to August 5, 2022 in addition to a manual search. The literature was reviewed and summarized in terms of methodologies and results for the various applications of AI to V/Q scans. The PRISMA guidelines were followed. Thirty-one publications fulfilled our search criteria and were grouped into two distinct categories: (1) disease diagnosis/detection (N = 22, 71.0%) and (2) cross-modality image translation into V/Q images (N = 9, 29.0%). Studies on disease diagnosis and detection relied heavily on shallow artificial neural networks for acute pulmonary embolism (PE) diagnosis and were primarily published between the mid-1990s and early 2000s. Recent applications almost exclusively regard image translation tasks from CT to ventilation or perfusion images with modern algorithms, such as convolutional neural networks, and were published between 2019 and 2022. AI research in V/Q scintigraphy for acute PE diagnosis in the mid-90s to early 2000s yielded promising results but has since been largely neglected and thus have yet to benefit from today's state-of-the art machine-learning techniques, such as deep neural networks. Recently, the main application of AI for V/Q has shifted towards generating synthetic ventilation and perfusion images from CT. There is therefore considerable potential to expand and modernize the use of real V/Q studies with state-of-the-art deep learning approaches, especially for workflow optimization and PE detection at both acute and chronic stages. We discuss future challenges and potential directions to compensate for the lag in this domain and enhance the value of this traditional nuclear medicine scan.