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Objectives Time-resolved, 2D-phase-contrast MRI (2D-CINE-PC-MRI) enables in vivo blood flow analysis. However, accurate vessel contour delineation (VCD) is required to achieve reliable results. We sought to evaluate manual analysis (MA) compared to the performance of a deep learning (DL) application for fully-automated VCD and flow quantification and corrected semi-automated analysis (corSAA). Methods We included 97 consecutive patients (age = 52.9 ± 16 years, 41 female) with 2D-CINE-PC-MRI imaging on 1.5T MRI systems at sinotubular junction (STJ), and 28/97 also received 2D-CINE-PC at main pulmonary artery (PA). A cardiovascular radiologist performed MA (reference) and corSAA (built-in tool) in commercial software for all cardiac time frames (median: 20, total contours per analysis: 2358 STJ, 680 PA). DL-analysis automatically performed VCD, followed by net flow (NF) and peak velocity (PV) quantification. Contours were compared using Dice similarity coefficients (DSC). Discrepant cases (> ± 10 mL or > ± 10 cm/s) were reviewed in detail. Results DL was successfully applied to 97% (121/125) of the 2D-CINE-PC-MRI series (STJ: 95/97, 98%, PA: 26/28, 93%). Compared to MA, mean DSC were 0.91 ± 0.02 (DL), 0.94 ± 0.02 (corSAA) at STJ, and 0.85 ± 0.08 (DL), 0.93 ± 0.02 (corSAA) at PA; this indicated good to excellent DL-performance. Flow quantification revealed similar NF at STJ (p = 0.48) and PA (p > 0.05) between methods while PV assessment was significantly different (STJ: p < 0.001, PA: p = 0.04). A detailed review showed noisy voxels in MA and corSAA impacted PV results. Overall, DL analysis compared to human assessments was accurate in 113/121 (93.4%) cases. Conclusions Fully-automated DL-analysis of 2D-CINE-PC-MRI provided flow quantification at STJ and PA at expert level in > 93% of cases with results being available instantaneously. Key Points • Deep learning performed flow quantification on clinical 2D-CINE-PC series at the sinotubular junction and pulmonary artery at the expert level in > 93% of cases. • Location detection and contouring of the vessel boundaries were performed fully-automatic with results being available instantaneously compared to human assessments which approximately takes three minutes per location. • The evaluated tool indicates usability in daily practice.

4D Flow MRI is a quantitative imaging technique to evaluate blood flow patterns; however, it is unclear how compressed sensing (CS) acceleration would impact aortic hemodynamic quantification in type B aortic dissection (TBAD).To investigate CS-accelerated 4D Flow MRI performance compared to GRAPP-accelerated 4D Flow MRI (GRAPPA) to evaluate aortic hemodynamics in TBAD.Prospective.Twelve TBAD patients, two volunteers.1.5T, 3D time-resolved cine phase-contrast gradient echo sequence.GRAPPA (acceleration factor [R] = 2) and two CS-accelerated (R = 7.7 [CS7.7] and 10.2 [CS10.2]) 4D Flow MRI scans were acquired twice for interscan reproducibility assessment. Voxelwise kinetic energy (KE), peak velocity (PV), forward flow (FF), reverse flow (RF), and stasis were calculated. Plane-based mid-lumen flows were quantified. Imaging times were recorded.Repeated measures analysis of variance, Pearson correlation coefficients (r), intraclass correlation coefficients (ICC). P 0.05 indicated statistical significance.The KE and FF in true lumen (TL) and PV in false lumen (FL) did not show difference among three acquisition types (P = 0.818, 0.065, 0.284 respectively). The PV and stasis in TL were higher, KE, FF, and RF in FL were lower, and stasis was higher in GRAPPA compared to CS7.7 and CS10.2. The RF was lower in GRAPPA compared to CS10.2. The correlation coefficients were strong in TL (r = [0.781-0.986]), and low to strong in FL (r = [0.347-0.948]). The ICC levels demonstrated moderate to excellent interscan reproducibility (0.732-0.989). The FF and net flow in mid-descending aorta TL were significantly different between CS7.7 and CS10.2.CS-accelerated 4D Flow MRI has potential for clinical utilization with shorter scan times in TBAD. Our results suggest similar hemodynamic trends between acceleration types, but CS-acceleration impacts KE, FF, RF, and stasis more in FL.1 Technical Efficacy: Stage 2.

PURPOSE: To compare maximum left atrial (LA) volume (LAV) from the routinely used biplane area-length (BAL) method with three-dimensional (3D)–based volumetry from late gadolinium-enhanced MRI (3D LGE MRI) and contrast-enhanced MR angiography (3D CE-MRA) in patients with atrial fibrillation (AF). MATERIALS AND METHODS: Sixty-four patients with AF (mean age, 63 years ± 9 [SD]; 40 male patients) were retrospectively included from a prospective cohort acquired between October 2018 and February 2021. All patients underwent a research MRI examination that included standard two- and four-chamber cine acquisitions, 3D CE-MRA, and 3D LGE MRI performed prior to the atrial kick. Contour delineation on cine imaging and LA 3D segmentations were performed by a radiologist. Maximum LAV (BALmax) was extracted from the BAL volume-time curve and compared with LAV from 3D CE-MRA and 3D LGE MRI. The Kruskal-Wallis test was performed, followed by the Dunn post hoc test and Bland-Altman analyses. Interobserver variability was assessed in 10 patients. RESULTS: BALmax underestimated LAV compared with 3D CE-MRA (bias: -23.5 mL ± 46.2, P < .001) and 3D LGE MRI (bias: -31.3 mL ± 58.3, P < .001), whereas 3D LGE MRI volumes showed no evidence of a difference from 3D CE-MRA (bias: 7.8 mL ± 45.7, P = .38). Interobserver variability yielded excellent agreement for each method (intraclass correlation coefficient, 0.96–0.98). CONCLUSION: BALmax underestimated LAV in patients with AF compared with 3D LGE MRI and 3D CE-MRA, suggesting that the geometric assumption of an ellipsoidal LA shape in BAL does not reflect LA geometry in patients with AF. Keywords: Left Atrial Volume, Biplane Area-Length, Late Gadolinium-enhanced 3D MRI, Contrast-enhanced 3D MR Angiography, Atrial Fibrillation Supplemental material is available for this article. © RSNA, 2023

The purpose of this study was to determine an optimal saturation-recovery time (TS) for minimizing the underestimation of arterial input function (AIF) in quantitative cardiac perfusion MRI without multiple gadolinium injections per subject.We scanned 18 subjects (mean age = 59 ± 14 years, 9/9 males/females) to acquire resting perfusion data and 1 additional subject (age = 38 years, male) to obtain stress-rest perfusion data using a 5-fold accelerated pulse sequence with radial k-space sampling and applied k-space weighted image contrast (KWIC) filters on the same k-space data to retrospectively reconstruct five AIF images with effective TS ranging from 10 to 21.2 ms (2.8 ms steps). Undersampled images were reconstructed using a compressed sensing framework with temporal-total-variation and temporal-principal-component as 2 orthogonal sparsifying transforms. The image processing steps included, same motion correction across five different AIF images, signal normalization by the proton-density-weighted-image, signal-to-TAmong five TS values, the shortest TS (10 ms) produced significantly (P 0.05) higher peak AIF and lower resting MBF (13.73 mM, 0.73 mL gThis study demonstrates that TS of 10 ms reduces the underestimation of AIF and, hence, the overestimation of MBF compared with longer TS values (12.8-21.2 ms).

The aim of this study is to elucidate the prevalence and factors associated with follow-up chest computed tomography (CT) imaging in patients undergoing stress-perfusion cardiac magnetic resonance imaging (sCMR) and coronary CT angiography (cCTA).Cardiac imaging encounters between January 1, 2015 and May 16, 2020 were selected for analysis. Follow-up was tracked within 1-year of initial cardiac imaging, up to May 16, 2021. Patient demographics, comorbidities, and cardiopulmonary outcomes were also analyzed.Between 2015 and 2020, there were 4024 cCTA and 837 sCMR imaging procedures on unique patients with 1.1% and 0.5% of patients having follow-up CT chest studies within 1 year, respectively. When controlling for patient demographic factors, body mass index, insurance status, smoking history, and comorbid diagnostic codes, there was statistically significant increased odds (adjusted odds ratio [95% confidence interval]: 2.864 [1.129-7.265]) of undergoing follow-up within the cCTA cohort. Pulmonary nodules represented the most common incidental finding, with cCTA associated with higher rates of pulmonary nodules detected on imaging (adjusted odds ratio [95% confidence interval]: 5.947 [4.136-8.552]). sCMR was associated with higher rates of MI, percutaneous coronary intervention, and lung malignancy within 1 year, with no difference in all-cause mortality.Patients undergoing either cCTA and sCMR demonstrated a low prevalence of follow-up CT chest imaging; however, follow-up was 2 times greater after cCTA due to greater pulmonary nodule detection. Potential for follow-up should be considered when evaluating the comparative effectiveness of these modalities, including the impact of follow-up imaging on cost and patient outcomes. Strategies to improve lung nodule detection and characterization at the time of sCMR may provide added value in these patients.

Background Acute aortic syndromes comprise a spectrum of diseases including aortic dissection, intramural hematoma, and penetrating atherosclerotic ulcers. Early diagnosis, rapid intervention, and multidisciplinary team care are vital to efficiently manage time-sensitive aortic emergencies, mobilize appropriate resources, and optimize clinical outcomes. Objective This comprehensive review outlines the multidisciplinary team approach from initial presentation to definitive interventional treatment and post-operative care. Discussion Acute aortic syndromes can be life-threatening and require prompt diagnosis and aggressive initiation of blood pressure and pain control to prevent subsequent complications. Early time to diagnosis and intervention are associated with improved outcomes. Conclusions A multidisciplinary team can help promptly diagnose and manage aortic syndromes.

The aim of this study was to evaluate the role of wall shear stress (WSS) as a predictor of ascending aorta (AAo) growth at 5 years or greater follow-up.Aortic 4-dimensional flow cardiac magnetic resonance (CMR) can quantify regions exposed to high WSS, a known stimulus for arterial wall dysfunction. However, its association with longitudinal changes in aortic dilation in patients with bicuspid aortic valve (BAV) is unknown.This retrospective study identified 72 patients with BAV (age 45 ± 12 years) who underwent CMR for surveillance of aortic dilation at baseline and ≥5 years of follow-up. Four-dimensional flow CMR analysis included the calculation of WSS heat maps to compare regional WSS in individual patients with population averages of healthy age- and sex-matched subjects (database of 136 controls). The relative areas of the AAo and aorta (in %) exposed to elevated WSS (outside the 95% CI of healthy population averages) were quantified.At a median follow-up duration of 6.0 years, the mean AAo growth rate was 0.24 ± 0.20 mm/y. The fraction of the AAo exposed to elevated WSS at baseline was increased for patients with higher growth rates (0.24 mm/y, n = 32) compared with those with growth rates 0.24 mm/y (19.9% [IQR: 10.2%-25.5%] vs 5.7% [IQR: 1.5%-21.3%]; P = 0.008). Larger areas of elevated WSS in the AAo and entire aorta were associated with higher rates of AAo dilation0.24 mm/y (odds ratio: 1.51; 95% CI: 1.05-2.17; P = 0.026 and odds ratio: 1.70; 95% CI: 1.01-3.15; P = 0.046, respectively).The area of elevated AAo WSS as assessed by 4-dimensional flow CMR identified BAV patients with higher rates of aortic dilation and thus might determine which patients require closer follow-up.

Aneurysms of the left atrial appendage (LAA) are rare entities that often require surgical intervention. We demonstrate multimodality imaging features of a giant LAA aneurysm, with a focus on 3-dimensional blood flow dynamics by using 4-dimensional-flow cardiac magnetic resonance. (Level of Difficulty: Advanced.), Graphical abstract

BACKGROUND Cardiac magnetic resonance imaging (MRI) is becoming an alternative to right heart catheterization (RHC) for evaluating pulmonary hypertension (PH). A need exists to further evaluate cardiac MRI's ability to characterize PH. PURPOSE To evaluate the potential for four-dimensional (4D) flow MRI-derived pulmonary artery velocities to characterize PH. STUDY TYPE Prospective case-control. POPULATION Fifty-four PH patients (56% female); 25 controls (36% female). FIELD STRENGTH/SEQUENCE 1.5 T; gradient recalled echo 4D flow and balanced steady-state free precession cardiac cine. ASSESSMENT RHC was used to derive patients' pulmonary vascular resistance (PVR). 4D flow measured blood velocities at the main, left, and right pulmonary arteries (MPA, LPA, and RPA); cine measured ejection fraction, end diastolic, and end systolic volumes (EF, EDV, and ESV). EDV and ESV were normalized (indexed) to body surface area (ESVI and EDVI). Parameters were evaluated between, and within, PH subgroups: pulmonary arterial hypertension (PAH); PH due to left heart disease (PH-LHD)/chronic lung disease (PH-CLD)/or chronic thrombo-emboli (CTE-PH). STATISTICAL TESTS Analysis of variance and Kruskal-Wallis tests compared parameters between subgroups. Pearson's r assessed velocity, PVR, and volume correlations. Significance definition: P

The hemispherical aortic annuloplasty reconstructive technology (HAART) is an internal geometric annuloplasty ring designed to restore a natural elliptical shape to the aortic annulus as part of aortic valve repair. We present 4D flow hemodynamic analysis before and after implementation of the HAART ring in patients undergoing ascending aortic replacement. HAART patients displayed similar or improved flow profiles when compared to a patient undergoing ascending aortic replacement alone.

Background There are characteristic findings of coronavirus disease 2019 (COVID-19) on chest images. An artificial intelligence (AI) algorithm to detect COVID-19 on chest radiographs might be useful for triage or infection control within a hospital setting, but prior reports have been limited by small data sets, poor data quality, or both. Purpose To present DeepCOVID-XR, a deep learning AI algorithm to detect COVID-19 on chest radiographs, that was trained and tested on a large clinical data set. Materials and Methods DeepCOVID-XR is an ensemble of convolutional neural networks developed to detect COVID-19 on frontal chest radiographs, with reverse-transcription polymerase chain reaction test results as the reference standard. The algorithm was trained and validated on 14 788 images (4253 positive for COVID-19) from sites across the Northwestern Memorial Health Care System from February 2020 to April 2020 and was then tested on 2214 images (1192 positive for COVID-19) from a single hold-out institution. Performance of the algorithm was compared with interpretations from five experienced thoracic radiologists on 300 random test images using the McNemar test for sensitivity and specificity and the DeLong test for the area under the receiver operating characteristic curve (AUC). Results A total of 5853 patients (mean age, 58 years ± 19 [standard deviation]; 3101 women) were evaluated across data sets. For the entire test set, accuracy of DeepCOVID-XR was 83%, with an AUC of 0.90. For 300 random test images (134 positive for COVID-19), accuracy of DeepCOVID-XR was 82%, compared with that of individual radiologists (range, 76%–81%) and the consensus of all five radiologists (81%). DeepCOVID-XR had a significantly higher sensitivity (71%) than one radiologist (60%, P < .001) and significantly higher specificity (92%) than two radiologists (75%, P < .001; 84%, P = .009). AUC of DeepCOVID-XR was 0.88 compared with the consensus AUC of 0.85 (P = .13 for comparison). With consensus interpretation as the reference standard, the AUC of DeepCOVID-XR was 0.95 (95% CI: 0.92, 0.98). Conclusion DeepCOVID-XR, an artificial intelligence algorithm, detected coronavirus disease 2019 on chest radiographs with a performance similar to that of experienced thoracic radiologists in consensus. © RSNA, 2020 Supplemental material is available for this article. See also the editorial by van Ginneken in this issue.

PURPOSE To develop and evaluate a flexible, Bloch-equation based framework for retrospective T2∗ correction to the arterial input function (AIF) obtained with quantitative cardiac perfusion pulse sequences. METHODS Our framework initially calculates the gadolinium concentration [Gd] based on T1 measurements alone. Next, T2∗ is estimated from this initial calculation of [Gd] while assuming fast water exchange and using the literature native T2 and static magnetic field variation (ΔB0 ) values. Finally, the [Gd] is recalculated after performing T2∗ correction to the Bloch equation signal model. Using this approach, we performed T2∗ correction to historical phantom and in vivo, dual-imaging perfusion data sets from 3 different patient groups obtained using different pulse sequences and imaging parameters. Images were processed to quantify both the AIF and resting myocardial blood flow (MBF). We also performed a sensitivity analysis of our T2∗ correction to ±20% variations in native T2 and ΔB0 . RESULTS Compared with the ground truth [Gd] of phantom, the normalized root-means-square-error (NRMSE) in measured [Gd] was 5.1%, 1.3%, and 0.6% for uncorrected, our corrected, and Kellman's corrected, respectively. For in vivo data, both the peak AIF (7.0 ± 3.0 mM vs. 8.6 ± 7.1 mM, 7.2 ± 0.9 mM vs. 8.6 ± 1.7 mM, 7.7 ± 1.8 mM vs. 10.3 ± 5.1 mM, P < .001) and resting MBF (1.3 ± 0.1 mL/g/min vs. 1.1 ± 0.1 mL/g/min, 1.3 ± 0.1 mL/g/min vs. 1.1 ± 0.1 mL/g/min, 1.2 ± 0.1 mL/g/min vs. 0.9 ± 0.1 mL/g/min, P < .001) values were significantly different between uncorrected and corrected for all 3 patient groups. Both the peak AIF and resting MBF values varied by

To noninvasively assess left atrial (LA) kinetic energy (KE) in hypertrophic cardiomyopathy (HCM) patients using 4D flow MRI and evaluate coupling associations with mitral regurgitation (MR) and left ventricular outflow tract (LVOT) obstruction. Twenty-nine retrospectively identified patients with HCM underwent 4D flow MRI. MRI-estimated peak LVOT pressure gradient (∆PMRI) was used to classify patients into non-obstructive and obstructive HCM. Time-resolved volumetric LA kinetic energy (KELA) was computed throughout systole. Average systolic (KELA-avg) and peak systolic (KELA-peak) KELA were compared between non-obstructive and obstructive HCM groups, and associations to MR severity and LVOT ∆PMRI were tested.The study included 15 patients with non-obstructive HCM (58.6 [45.9, 65.2] years, 7 females) and 14 patients with obstructive HCM (51.9 [47.6, 62.6] years, 6 females). Obstructive HCM patients demonstrated significantly elevated instantaneous KELA over all systolic time-points compared to non-obstructive HCM (P

Objective The 2019 Coronavirus (COVID-19) results in a wide range of clinical severity and there remains a need for prognostic tools which identify patients at risk of rapid deterioration and who require critical care. Chest radiography (CXR) is routinely obtained at admission of COVID-19 patients. However, little is known regarding correlates between CXR severity and time to intubation. We hypothesize that the degree of opacification on CXR at time of admission independently predicts need and time to intubation. Methods In this retrospective cohort study, we reviewed COVID-19 patients who were admitted to an urban medical center during March 2020 that had a CXR performed on the day of admission. CXRs were divided into 12 lung zones and were assessed by two blinded thoracic radiologists. A COVID-19 opacification rating score (CORS) was generated by assigning one point for each lung zone in which an opacity was observed. Underlying comorbidities were abstracted and assessed for association. Results One hundred forty patients were included in this study and 47 (34%) patients required intubation during the admission. Patients with CORS ≥ 6 demonstrated significantly higher rates of early intubation within 48 h of admission and during the hospital stay (ORs 24 h, 19.8, p < 0.001; 48 h, 28.1, p < 0.001; intubation during hospital stay, 6.1, p < 0.0001). There was no significant correlation between CORS ≥ 6 and age, sex, BMI, or any underlying cardiac or pulmonary comorbidities. Conclusions CORS ≥ 6 at the time of admission predicts need for intubation, with significant increases in intubation at 24 and 48 h, independent of comorbidities. Key Points • Chest radiography at the time of admission independently predicts time to intubation within 48 h and during the hospital stay in COVID-19 patients. • More opacities on chest radiography are associated with several fold increases in early mechanical ventilation among COVID-19 patients. • Chest radiography is useful in identifying COVID-19 patients whom may rapidly deteriorate and help inform clinical management as well as hospital bed and ventilation allocation. Electronic supplementary material The online version of this article (10.1007/s00330-020-07354-y) contains supplementary material, which is available to authorized users.

Pulmonary vascular assessment commonly relies on computed tomography angiography (CTA), but continued advances in magnetic resonance angiography have allowed pulmonary magnetic resonance angiography (pMRA) to become a reasonable alternative to CTA without exposing patients to ionizing radiation. pMRA allows the evaluation of pulmonary vascular anatomy, hemodynamic physiology, lung parenchymal perfusion, and (optionally) right and left ventricular function with a single examination. This article discusses pMRA techniques and artifacts; performance in commonly encountered pulmonary vascular diseases, specifically pulmonary embolism and pulmonary hypertension; and recent advances in both contrast-enhanced and noncontrast pMRA.

Hypertrophic cardiomyopathy (HCM) is a genetic cardiomyopathy with a wide spectrum of clinical manifestations. Patients can be asymptomatic or suffer major adverse events including sudden cardiac death, ventricular arrhythmias, and heart failure. Identification of individuals with HCM who are at risk for these complications remains challenging. While echocardiography remains the mainstay of diagnostic evaluation, cardiac magnetic resonance imaging (CMR) is an important adjunctive diagnostic modality with emerging applications for risk-stratification of adverse events in the HCM population. Although not included in current guidelines for HCM management, there is increasing evidence to support the use of CMR for routine prognostic assessment of HCM patients. In this review we discuss the use of CMR techniques, including late gadolinium enhancement, T1 mapping, and quantification of extracellular volume fraction, for the risk stratification of three major adverse events in HCM: sudden cardiac death, ventricular arrhythmias, and congestive heart failure.

Recent studies with lung MRI (MRI) have shown high sensitivity (Sn) and specificity (Sp) for lung nodule detection and characterization relative to low-dose CT (LDCT). Using this background data, we sought to compare the potential screening performance of MRI vs. LDCT using a Markov model of lung cancer screening.We created a Markov cohort model of lung cancer screening which incorporated lung cancer incidence, progression, and mortality based on gender, age, and smoking burden. Sensitivity (Sn) and Sp for LDCT were taken from the MISCAN Lung Microsimulation and Sn/Sp for MRI was estimated from a published substudy of the German Lung Cancer Screening and Intervention Trial. Screening, work-up, and treatment costs were estimated from published data. Screening with MRI and LDCT was simulated for a cohort of male and female smokers (2 packs per day; 36 pack/years of smoking history) starting at age 60. We calculated the screening performance and cost-effectiveness of MRI screening and performed a sensitivity analysis on MRI Sn/Sp and cost.There was no difference in life expectancy between MRI and LDCT screening (males 13.28 vs. 13.29 life-years; females 14.22 vs. 14.22 life-years). MRI had a favorable cost-effectiveness ratio of $258,169 in men and $403,888 in women driven by fewer false-positive screens. On sensitivity analysis, MRI remained cost effective at screening costs$396 dollars and Sp81%.In this Markov model of lung cancer screening, MRI has a near-equivalent life expectancy benefit and has superior cost-effectiveness relative to LDCT.• In this Markov model of lung cancer screening, there is no difference in mortality between yearly screening with MRI and low-dose CT. • Compared to low-dose CT, screening with MRI led to a reduction in false-positive studies from 26 to 2.8% in men and 26 to 2.6% in women. • Due to similar life-expectancy and reduced false-positive rate, we found a favorable cost-effectiveness ratio of $258,169 in men and $403,888 in women of MRI relative to low-dose CT.

Gadobutrol (GB) and gadoterate meglumine (GM) are contrast agents used for contrast-enhanced magnetic resonance angiography (CEMRA). Supraaortic vasculature (SAV) CEMRAs are used to evaluate stroke risk and neurologic symptoms. There is a need to compare the SAV CEMRA image quality obtained with GB and GM.To intra-individually compare MRA images obtained with equimolar GB and GM at 1.5 T in the SAV.Prospective, crossover.Twenty-eight subjects (54 ± 13 years; 17 female).1.5 T; three-dimensional (3D) gradient recalled echo.Quantitative image quality was measured by normalized signal intensity (SISINo significant difference in SIAt 1.5 T and equimolar demonstration, GB (0.1 mL/kg, i.e., 0.1 mmol/kg) showed higher CRs in the SAV compared to GM (0.2 mL/kg, i.e., 0.1 mmol/kg) at most vessels. Subjective image quality was not significantly different between the two agents for most vessels.2 TECHNICAL EFFICACY: Stage 2.

Background Despite decades of accruing evidence supporting the clinical utility of cardiovascular magnetic resonance (CMR), adoption of CMR in routine cardiovascular practice remains limited in many regions of the world. Persistent use of long scan times of 60 min or more contributes to limited adoption, though techniques available on most scanners afford routine CMR examination within 30 min. Incorporating such techniques into standardize protocols can answer common clinical questions in daily practice, including those related to heart failure, cardiomyopathy, ventricular arrhythmia, ischemic heart disease, and non-ischemic myocardial injury. Body In this white paper, we describe CMR protocols of 30 min or shorter duration with routine techniques with or without stress perfusion, plus specific approaches in patient and scanner room preparation for efficiency. Minimum requirements for the scanner gradient system, coil hardware and pulse sequences are detailed. Recent advances such as quantitative myocardial mapping and other add-on acquisitions can be incorporated into the proposed protocols without significant extension of scan duration for most patients. Conclusion Common questions in clinical cardiovascular practice can be answered in routine CMR protocols under 30 min; their incorporation warrants consideration to facilitate increased access to CMR worldwide.