An accurate and time-efficient deep learning-based system for automated segmentation and reporting of cardiac magnetic resonance-detected ischemic scar

Background and objectives: Myocardial infarction scar (MIS) assessment by cardiac magnetic resonance provides prognostic information and guides patients' clinical management. However, MIS segmentation is time-consuming and not performed routinely. This study presents a deep-learning-based computational workflow for the segmentation of left ventricular (LV) MIS, for the first time performed on state-of-the-art dark-blood late gadolinium enhancement (DB-LGE) images, and the computation of MIS transmurality and extent.Methods: DB-LGE short-axis images of consecutive patients with myocardial infarction were acquired at 1.5T in two centres between Jan 1, 2019, and June 1, 2021. Two convolutional neural network (CNN) mod-els based on the U-Net architecture were trained to sequentially segment the LV and MIS, by processing an incoming series of DB-LGE images. A 5-fold cross-validation was performed to assess the performance of the models. Model outputs were compared respectively with manual (LV endo-and epicardial border) and semi-automated (MIS, 4-Standard Deviation technique) ground truth to assess the accuracy of the segmentation. An automated post-processing and reporting tool was developed, computing MIS extent (expressed as relative infarcted mass) and transmurality.Results: The dataset included 1355 DB-LGE short-axis images from 144 patients (MIS in 942 images). High performance (> 0.85) as measured by the Intersection over Union metric was obtained for both the LV and MIS segmentations on the training sets. The performance for both LV and MIS segmentations was 0.83 on the test sets.Compared to the 4-Standard Deviation segmentation technique, our system was five times quicker ( <1 min versus 7 +/- 3 min), and required minimal user interaction. Conclusions: Our solution successfully addresses different issues related to automatic MIS segmentation, including accuracy, time-effectiveness, and the automatic generation of a clinical report.(c) 2022 Elsevier B.V. All rights reserved

An accurate and time-efficient deep learning-based system for automated segmentation and reporting of cardiac magnetic resonance-detected ischemic scar

BACKGROUND AND OBJECTIVES: Myocardial infarction scar (MIS) assessment by cardiac magnetic resonance provides prognostic information and guides patients' clinical management. However, MIS segmentation is time-consuming and not performed routinely. This study presents a deep-learning-based computational workflow for the segmentation of left ventricular (LV) MIS, for the first time performed on state-of-the-art dark-blood late gadolinium enhancement (DB-LGE) images, and the computation of MIS transmurality and extent. METHODS: DB-LGE short-axis images of consecutive patients with myocardial infarction were acquired at 1.5T in two centres between Jan 1, 2019, and June 1, 2021. Two convolutional neural network (CNN) models based on the U-Net architecture were trained to sequentially segment the LV and MIS, by processing an incoming series of DB-LGE images. A 5-fold cross-validation was performed to assess the performance of the models. Model outputs were compared respectively with manual (LV endo- and epicardial border) and semi-automated (MIS, 4-Standard Deviation technique) ground truth to assess the accuracy of the segmentation. An automated post-processing and reporting tool was developed, computing MIS extent (expressed as relative infarcted mass) and transmurality. RESULTS: The dataset included 1355 DB-LGE short-axis images from 144 patients (MIS in 942 images). High performance (> 0.85) as measured by the Intersection over Union metric was obtained for both the LV and MIS segmentations on the training sets. The performance for both LV and MIS segmentations was 0.83 on the test sets. Compared to the 4-Standard Deviation segmentation technique, our system was five times quicker (<1 min versus 7 ± 3 min), and required minimal user interaction. CONCLUSIONS: Our solution successfully addresses different issues related to automatic MIS segmentation, including accuracy, time-effectiveness, and the automatic generation of a clinical report

Association of outcome with left ventricular volumes and ejection fraction measured with two- and three-dimensional echocardiography in patients referred for routine, clinically indicated studies

ObjectivesWe sought to analyze if left ventricular (LV) volumes and ejection fraction (EF) measured by three-dimensional echocardiography (3DE) have incremental prognostic value over measurements obtained from two-dimensional echocardiography (2DE) in patients referred to a high-volume echocardiography laboratory for routine, clinically-indicated studies.MethodsWe measured LV volumes and EF using both 2DE and 3DE in 725 consecutive patients (67% men; 59 ± 18 years) with various clinical indications referred for a routine clinical study.ResultsLV volumes were significantly larger, and EF was lower when measured by 3DE than 2DE. During follow-up (3.6 ± 1.2 years), 111 (15.3%) all-cause deaths and 248 (34.2%) cardiac hospitalizations occurred. Larger LV volumes and lower EF were associated with worse outcome independent of age, creatinine, hemoglobin, atrial fibrillation, and ischemic heart diseases). In stepwise Cox regression analyses, the associations of both death and cardiac hospitalization with clinical data (CD: age, creatinine, hemoglobin, atrial fibrillation, and ischemic heart disease) whose Harrel’s C-index (HC) was 0.775, were augmented more by the LV volumes and EF obtained by 3DE than by 2DE parameters. The association of CD with death was not affected by LV end-diastolic volume (EDV) either measured by 2DE or 3DE. Conversely, it was incremented by 3DE LVEF (HC = 0.84, p &amp;lt; 0.001) more than 2DE LVEF (HC = 0.814, p &amp;lt; 0.001). The association of CD with the composite endpoint (HC = 0.64, p = 0.002) was augmented more by 3DE LV EDV (HC = 0.786, p &amp;lt; 0.001), end-systolic volume (HC = 0.801, p &amp;lt; 0.001), and EF (HC = 0.84, p &amp;lt; 0.001) than by the correspondent 2DE parameters (HC = 0.786, HC = 0.796, and 0.84, all p &amp;lt; 0.001) In addition, partition values for mild, moderate and severe reduction of the LVEF measured by 3DE showed a higher discriminative power than those measured by 2DE for cardiac death (Log-Rank: χ2 = 98.3 vs. χ2 = 77.1; p &amp;lt; 0.001). Finally, LV dilation defined according to the 3DE threshold values showed higher discriminatory power and prognostic value for death than when using 2DE reference values (3DE LVEDV: χ2 = 15.9, p &amp;lt; 0.001 vs. χ2 = 10.8, p = 0.001; 3DE LVESV: χ2 = 24.4, p &amp;lt; 0.001 vs. χ2 = 17.4, p = 0.001).ConclusionIn patients who underwent routine, clinically-indicated echocardiography, 3DE LVEF and ESV showed stronger association with outcome than the corresponding 2DE parameters.</jats:sec

Significant Disagreement Between Conventional Parameters and 3D Echocardiography-Derived Ejection Fraction in the Detection of Right Ventricular Systolic Dysfunction and Its Association With Outcomes

Aims Conventional echocardiographic parameters such as tricuspid annular plane systolic excursion (TAPSE), fractional area change (FAC), and free-wall longitudinal strain (FWLS) offer limited insights into the complexity of right ventricular (RV) systolic function, while 3D echocardiography-derived RV ejection fraction (RVEF) enables a comprehensive assessment. We investigated the discordance between TAPSE, FAC, FWLS, and RVEF in RV systolic function grading and associated outcomes. Methods We analyzed two- and three-dimensional echocardiography data from 2 centers including 750 patients followed up for all-cause mortality. Right ventricular dysfunction was defined as RVEF −20%) considered. Results Among patients with normal RVEF, significant proportions exhibited impaired TAPSE (21%), FAC (33%), or FWLS (8%). Conversely, numerous patients with reduced RVEF had normal TAPSE (46%), FAC (26%), or FWLS (41%). Using receiver-operating characteristic analysis, FWLS exhibited the highest area under the curve of discrimination for RV dysfunction (RVEF <45%) with 59% sensitivity and 92% specificity. Over a median 3.7-year follow-up, 15% of patients died. Univariable Cox regression identified TAPSE, FAC, FWLS, and RVEF as significant mortality predictors. Combining impaired conventional parameters showed that outcomes are the worst if at least 2 parameters are impaired and gradually better if only one or none of them are impaired (log-rank P < .005). Conclusion Guideline-recommended cutoff values of conventional echocardiographic parameters of RV systolic function are only modestly associated with RVEF-based assessment. Impaired values of FWLS showed the closest association with the RVEF cutoff. Our results emphasize a multiparametric approach in the assessment of RV function, especially if 3D echocardiography is not available

Impact of severe secondary tricuspid regurgitation on rest and exercise hemodynamics of patients with heart failure and a preserved left ventricular ejection fraction

BackgroundBoth secondary tricuspid regurgitation (STR) and heart failure with preserved ejection fraction (HFpEF) are relevant public health problems in the elderly population, presenting with potential overlaps and sharing similar risk factors. However, the impact of severe STR on hemodynamics and cardiorespiratory adaptation to exercise in HFpEF remains to be clarified.AimTo explore the impact of STR on exercise hemodynamics and cardiorespiratory adaptation in HFpEF.MethodsWe analyzed invasive hemodynamics and gas-exchange data obtained at rest and during exercise from HFpEF patients with severe STR (HFpEF-STR), compared with 1:1 age-, sex-, and body mass index (BMI)- matched HFpEF patients with mild or no STR (HFpEF-controls).ResultsTwelve HFpEF with atrial-STR (mean age 72 years, 92% females, BMI 28 Kg/m2) and 12 HFpEF-controls patients were analyzed. HFpEF-STR had higher (p &amp;lt; 0.01) right atrial pressure than HFpEF-controls both at rest (10 ± 1 vs. 5 ± 1 mmHg) and during exercise (23 ± 2 vs. 14 ± 2 mmHg). Despite higher pulmonary artery wedge pressure (PAWP) at rest in HFpEF-STR than in HFpEF-controls (17 ± 2 vs. 11 ± 2, p = 0.04), PAWP at peak exercise was no more different (28 ± 2 vs. 29 ± 2). Left ventricular transmural pressure and cardiac output (CO) increased less in HFpEF-STR than in HFpEF-controls (interaction p-value &amp;lt; 0.05). This latter was due to lower stroke volume (SV) values both at rest (48 ± 9 vs. 77 ± 9 mL, p &amp;lt; 0.05) and at peak exercise (54 ± 10 vs. 93 ± 10 mL, p &amp;lt; 0.05). Despite these differences, the two groups of patients laid on the same oxygen consumption isophlets because of the increased peripheral oxygen extraction in HFpEF-STR (p &amp;lt; 0.01). We found an inverse relationship between pulmonary vascular resistance and SV, both at rest and at peak exercise (R2 = 0.12 and 0.19, respectively).ConclusionsSevere STR complicating HFpEF impairs SV and CO reserve, leading to pulmonary vascular de-recruitment and relative left heart underfilling, undermining the typical HFpEF pathophysiology.</jats:sec

Data_Sheet_1_Impact of severe secondary tricuspid regurgitation on rest and exercise hemodynamics of patients with heart failure and a preserved left ventricular ejection fraction.docx

BackgroundBoth secondary tricuspid regurgitation (STR) and heart failure with preserved ejection fraction (HFpEF) are relevant public health problems in the elderly population, presenting with potential overlaps and sharing similar risk factors. However, the impact of severe STR on hemodynamics and cardiorespiratory adaptation to exercise in HFpEF remains to be clarified.AimTo explore the impact of STR on exercise hemodynamics and cardiorespiratory adaptation in HFpEF.MethodsWe analyzed invasive hemodynamics and gas-exchange data obtained at rest and during exercise from HFpEF patients with severe STR (HFpEF-STR), compared with 1:1 age-, sex-, and body mass index (BMI)- matched HFpEF patients with mild or no STR (HFpEF-controls).ResultsTwelve HFpEF with atrial-STR (mean age 72 years, 92% females, BMI 28 Kg/m2) and 12 HFpEF-controls patients were analyzed. HFpEF-STR had higher (p 2 = 0.12 and 0.19, respectively).ConclusionsSevere STR complicating HFpEF impairs SV and CO reserve, leading to pulmonary vascular de-recruitment and relative left heart underfilling, undermining the typical HFpEF pathophysiology.</p

Systematic pelvic and aortic lymphadenectomy in advanced ovarian cancer patients at the time of interval debulking surgery: a double-institution case-control study

The prognostic role of systematic lymphadenectomy remains unclear in advanced ovarian cancer (AOC). Only few retrospective case series have investigated the percentage of lymph node metastases after neoadjuvant chemotherapy. This multi-institutional case-control study analyzed the prognostic role of systematic lymphadenectomy in AOC patients at the time of interval debulking surgery (IDS)