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Lakhani, Dhairya

0000-0001-7577-1887

Mayo Clinic

Department of Neurology, Rockefeller Neuroscience Institute, West Virginia University, Morgantown, WV, USA.

Citations 24

Clinical application of ultra-high resolution compressed sensing time-of-flight MR angiography at 7T to detect small vessel pathology
Lakhani, Dhairya A. , Zhou, Xiangzhi , Tao, Shengzhen , Westerhold, Erin , Eidelman, Benjamin H., Middlebrooks, Erik H. , Westerhold, Erin M, Singh Sandhu, Sukhwinder Johnny, Middlebrooks, Erik H , Lakhani, Dhairya , Sandhu, Sukhwinder J.S.

The Neuroradiology Journal | September 29, 2022 | Volume: 36 | Issue: 3 | Pages: 335-340

10.1177/19714009221129576 Get It

3D time-of-flight (TOF) MR angiography (MRA) benefits from ultra-high-field MRI (≥7 T) due to improved contrast and increased signal-to-noise ratio. However, high-resolution TOF MRA at 7T usually requires longer acquisition times. In addition, relatively higher specific absorption rate (SAR) at 7T limits the choice of optimal pulse sequence parameters, especially if venous saturation is employed. Here, we illustrate the clinical application of ultra-high resolution cerebral 7T TOF MRA using compressed sensing in cases of artery of Percheron and lacunar infarcts, which showed superior resolution and exquisite details pertinent to the clinical diagnosis. The technical challenges associated with high-resolution 7T imaging were alleviated by optimization of sequence parameters and utilization of compressed sensing acceleration.
7-T Neuromelanin and R2* MRI in Parkinson Disease
Lakhani, Dhairya A. , Middlebrooks, Erik H. , Middlebrooks, Erik H , Lakhani, Dhairya

Radiology | August 2, 2022 | Volume: 305 | Issue: 2 | Pages: 296-296

10.1148/radiol.220230 Get It

Can Longitudinal Analysis of Computer Tomography-Based Score Indicative of Lung Cancer Aggression (SILA) Help in the Early Characterization of Lung Adenocarcinoma?
Lakhani, Dhairya A. , Roller, Lance, Chen, H. , Karwoski, R., Rajagopalan, S., Peikert, Tobias, Massion, Pierre P. , Maldonado, Fabien , Lakhani, Dhairya , Balar, Aneri , Antic, S., Kammer, Michael N. , Rajagopalan, S.

D99. ADVANCING RISK ASSESSEMENT FOR PULMONARY NODULES | July 7, 2020 | Volume: No volume available | Issue: No issue available | Pages: A7692-A7692

10.1164/ajrccm-conference.2020.201.1_meetingabstracts.a7692 Get It

Short‐term outcomes of atrial flutter ablation
Tripathi, Byomesh , Arora, Shilpkumar , Mishra, Abhishek , Kundoor, Vishwa, Lahewala, Sopan , Kumar, Varun , Shah, Mahek , Lakhani, Dhairya A. , Shah, Harshil , Patel, Nilay , Patel, Nileshkumar , Dave, Mihir, Deshmukh, Abhishek , Sattur, Sudhakar, Gopalan, Radha , Lakhani, Dhairya

Journal of Cardiovascular Electrophysiology | August 11, 2017 | Volume: 28 | Issue: 11 | Pages: 1275-1284

10.1111/jce.13311 Get It

AbstractBackgroundUnderstanding the factors associated with early readmissions following atrial flutter (AFL) ablation is critical to reduce the cost and improving the quality of life in AFL patients.MethodThe study cohort was derived from the national readmission database 2013–2014. International Classification of Diseases, 9th Revision (ICD‐9‐CM) diagnosis code 427.32 and procedure code 37.34 were used to identify AFL and catheter ablation, respectively. The primary and secondary outcomes were 90‐day readmission and complications including in‐hospital mortality. Cox proportional regression and hierarchical logistic regression were used to generate the predictors of primary and secondary outcomes respectively. Readmission causes were identified by ICD‐9‐CM code in primary diagnosis field of readmissions.ResultReadmission rate of 18.19% (n = 1,010 with 1,396 readmissions) was noted among AFL patients (n = 5552). Common etiologies for readmission were heart failure (12.23%), atrial fibrillation (11.13%), atrial flutter (8.93%), respiratory complications (9.42%), infections (7.4%), bleeding (7.39%, including GI bleed–4.09% and intracranial bleed–0.79%) and stroke/TIA (1.89%). Multivariate predictors of 90‐day readmission (hazard ratio, 95% confidence interval, P value) were preexisting heart failure (1.30, 1.13–1.49, P < 0.001), chronic pulmonary disease (1.37, 1.18–1.58, P < 0.001), anemia (1.23, 1.02–1.49, P = 0.035), malignancy (1.87, 1.40–2.49, P < 0.001), weekend admission compared to weekday admission (1.23, 1.02–1.47, P = 0.029), and length of stay (LOS) ≥5 days (1.39, 1.16–1.65, P < 0.001). Note that 50% of readmissions happened within 30 days of discharge.ConclusionCardiac etiologies remain the most common reason for the readmission after AFL ablation. Identifying high risk patients, careful discharge planning, and close follow‐up postdischarge can potentially reduce readmission rates in AFL ablation patients.