How to Add Oil - ARRS InPractice

Jessica T. Wen MD, PhD

PGY-3 IR/DR Resident

Stanford University

In Mandarin Chinese, a phrase that is often said to encourage and support loved ones is 加油 (pronounced jiāyóu). In English, it directly translates to “add oil” or “add fuel.”

My parents immigrated to the United States from Taiwan in the 1970s and 1980s. My siblings and I were born in Monterey Park, CA, a well-known suburban haven for East Asian Americans. My parents, however, quickly moved us to a predominantly White neighborhood in Orange County, hoping that we would assimilate for a better life.

After studying bioengineering in college, I pursued my PhD working on agricultural diagnostics. Early in graduate school, my dad was diagnosed with prior hepatitis B infection and liver cirrhosis. This is when I learned that Asian American men are 60% more likely to die of hepatobiliary cancer, compared to non-Hispanic White men [1]. At the time, I felt ashamed that as a college graduate pursuing an advanced degree, I had been completely ignorant of this health disparity that was pervasive in my own Asian American community. Why did we learn so much about HIV and hepatitis C in school, and so little about hepatitis B? After extended discussions with career mentors and family, I ultimately decided to career-change into medicine; I would apply for and plan to attend medical school after completing my PhD.

As a non-traditional applicant, I was fortunate to be accepted into the Medical Innovators Development Program [2] at Vanderbilt University School of Medicine—my dream program, where I could simultaneously learn medicine and keep alive my interest in engineering. As a West Coast native, however, I was not prepared for the culture shock that was waiting for me in the South. Upon transplantation, I was quickly surrounded by microaggressions, which were both confusing and yet oddly familiar. “But where are you really from?” was a common question for me, after offering that I am from Southern California, the place where I was born and spent my childhood. Comments about my surprisingly proficient English and catcalls on the street, using deranged pronunciations of East Asian languages from Japanese to Korean, made it clear that strictly based on my appearance, I was not perceived as “American” to my local community. This experience triggered repressed memories of bullying from grade school, when my peers would compare the shape of my eyes to floss and ask me to translate “ching chong ching chong” for them. To which I would respond, confused, that those were not Chinese words, and the words meant nothing.

During medical school, this sparked a new reflection and interest in my experience as an Asian American growing up and living in America. Through the Asian Pacific American Medical Student Association, I participated in an anti-racism workshop in which I learned about the racial triangulation theory (Fig. 1), published by Claire Jean Kim in 1999 [3].

Fig. 1—’Racial Triangulation’ adapted from Kim, Politics & Society, 1999.

Kim explains the context of anti-Asian racism, which is based on anti-Blackness. Asian stereotypes such as “oriental” (read: exotic, foreign, anti-Western) and “model minority” (read: quiet, submissive, good-at-math), have been used to drive a wedge between the Asian and Black populations; driving home the message that if Asians would follow the anti-Black social racial hierarchy, they would be passively tolerated—albeit never accepted—in American society. Racial triangulation has since been further extrapolated to additionally include the Hispanic/Latinx experience. From this foundation, I understood that the best way to combat racism is for all populations of color to stand together, with respect and support for one another.

Today, I reside again in California. As a diagnostic/interventional radiology trainee, I have started a medical research initiative called Research with Inclusion, Social justice, and Equity or RISE [4]. Our mission is to increase the representation of populations of color in medical research cohorts by supporting data transparency and empowering clinicians and clinical researchers to report the racial/ethnic breakdown of their study cohorts in their demographics table. A question I am often asked is, “how do you find the motivation and energy for it all?” Amid the rampant burnout that plagues our training culture [5], how do I “add oil” to keep going? My answer is that I reflect on my story, and I remind myself that my story is not unique. I get out of bed in the morning to work toward a hope that one day my story will become a fragment of a past culture in American medicine. And while it’s not a perfect method of fighting burnout, it’s certainly gotten me this far.

What is your story? How do you add oil?

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AJR Journal Club articles offer Study Guide questions specifically written by independent authors to improve your ability to critically analyze the primary scientific literature for more thorough participation in evidence-based medicine.

April’s article evaluates features on gadoxetate disodium–enhanced MRI of HCA subtypes on the basis of the 2017 classification and to propose a diagnostic algorithm for determining subtype using these features.

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Thyroid Nodules on Ultrasound in Children and Young Adults: Comparison of Diagnostic Performance of Radiologists’ Impressions, ACR TI-RADS, and a Deep Learning Algorithm

TUE, APR 26, 2023 | 12 noon–1pm, Eastern

Moderator: AJR Section Editor Jonathan R. Dillman, MD, MSc
Speakers: Laura Page, MD; Donald Frush, MD; Jichen (Andy) Yang

The incidence of thyroid nodules is increasing in children and young adults. For this population, the ultrasound reader’s overall impression often guides the decision of whether or not to perform a fine-needle aspiration, but there is a lack of clarity for how the interpreting physician’s impression may compare to other tools for thyroid nodule evaluation. This webinar will use a recent study, published in the March 2023 issue of AJR, to compare the diagnostic performance of radiologists’ overall impressions, guidance through ACR TI-RADS, and a previously developed deep learning algorithm in differentiating benign and malignant thyroid nodules from children and young adults.

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