_{Published November 4, 2022}

The mission of ARRS’ Global Partner Society (GPS) program is to build long-standing relationships with key leaders and organizations in the worldwide imaging community—increasing awareness of our society’s services in specific nations, while raising the stature of Global Partner Societies among ARRS members. Every year, the ARRS Annual Meeting Global Exchange incorporates one partner society into the educational and social fabric of our meeting. ARRS members then reciprocate at the partner society’s meeting that same year.

The GPS partner to be featured at the 2023 ARRS Annual Meeting on the stunning island of Oahu in Honolulu, HI, will be our longtime colleagues from the Korean Society of Radiology (KSR). Established in 1945, KSR remains the official society representing all physicians of Korea working in the field of radiology. With a membership of more than 3,000 practicing imaging professionals—including 500 in-training members—KSR also publishes two scholarly journals: the Korean Journal of Radiology and Journal of the Korean Society of Radiology.

The 2023 ARRS Global Exchange Featuring KSR, “Changing Paradigms in Tumor Response Assessment,” will be the latest in a very long succession of successful educational partnerships between the Americans and Koreans. These two vaunted societies joined forces to present a GPS symposium on breast imaging back in 2017. For that fourth KSR/ARRS online collaboration, respective faculty curated 15 lectures across five breast imaging topics that were delivered during the 72nd Korean Congress of Radiology and the 2016 ARRS Annual Meeting in Los Angeles, CA [1].   

On Sunday, April 16, live, virtually, and on-demand from Hawaii, the ARRS Annual Global Exchange Program will deliver a panel of experts from both the United States and Korea discussing a variety of topics and approaches regarding the quickly evolving role of radiologists in tumor response assessment. All participants, regardless of registration type, will gain functional familiarity with treatment response criteria across a wide swath of tumors, treatments, and techniques, learning from esteemed ARRS faculty from Brigham & Women’s Hospital, Memorial Sloan Kettering Cancer Center, and Rhode Island Hospital. I know I speak for the entire ARRS leadership and membership when I note how much we are all looking forward to hosting KSR’s leading experts from Seoul National University Hospital, Yonsei University Health System, Soonchunhyang University College of Medicine, and the Catholic University of Korea. Our Korean friends will help us understand locoregional treatment response evaluation for hepatocellular carcinoma (HCC).

Immune Checkpoints: No Inhibitions?

Be it in America, across the Pacific, or anywhere else in the world for that matter, a chief radiological concern moving forward is recognizing the spectrum of responses and progressive diseases typically encountered in patients treated with immunotherapies, especially immune checkpoint inhibitors (ICI). Right now, indications for ICI therapy already include more than 16 different cancers. As this number will only continue to increase in the coming years, academic and private practice imagers (in addition to radiology residents and fellows) need to know the hang-ups of ICIs.

Recently, on the AJR Podcast episode “Chest CT Findings of Immune Checkpoint Inhibitor Therapy-Related Adverse Events,” Kerem Ozturk, MD, discussed why awareness of early chest CT findings is required for early detection and accurate diagnosis of ICI therapy-related adverse events [2]. Said events are myriad, including pneumonitis, new consolidation, worsening thoracic tumor burden, pleural/pericardial effusion, and pulmonary emboli in the emergency department.

We need to know about combinations, too. Promising results have been published in KSR’s own Korean Journal of Radiology regarding ICI combination therapy and ICI combined with radiotherapy. Specifically, as Kim et al. pointed out in their systematic review and meta-analysis, ICI combination therapy or ICI combined with radiotherapy can work wonders, showing better localized efficacy than ICI monotherapy for treating melanoma brain metastasis [3]. Inevitably, the ever-increasing adoption of ICIs will lead to more and more practical applications.

HCC: Mimics and Machine Learning

Due to its distinct imaging, HCC can be diagnosed noninvasively, typically via multiphasic CT and MRI. As Yoon et al. reminded us in their survey and pictorial review for the Journal of the Korean Society of Radiology, while imaging features like arterial phase hyperenhancement and washout on portal or delayed phase images is classic for HCC, the ability to distinguish HCC-mimicking lesions (e.g., arterioportal shunts, combined HCC-cholangiocarcinoma, intrahepatic cholangiocarcinoma, hemangioma, etc.) on initial imaging examinations is critical for management and treatment alike [4].

Radiologists of tomorrow will need to recognize more than just mimics. We must become familiar with multiple machine learning models, as applied to presently underutilized imaging features that could help construct more reliable criteria for organ allocation and liver transplant eligibility. Apropos, recent findings suggest that machine learning-based models can predict recurrence before therapy allocation in patients with early-stage HCC initially eligible for liver transplant.  

As described in AJR OnTrend, 120 patients diagnosed with early-stage HCC, who were initially eligible for liver transplant and underwent treatment by transplant, resection, or thermal ablation, underwent pretreatment MRI and post-treatment imaging surveillance. Imaging features were extracted from postcontrast phases of pretreatment MRI examinations using a pretrained convolutional neural network. Pretreatment clinical characteristics (including labs) and extracted imaging features were integrated for recurrence prediction to develop three ML models: clinical, imaging, combined. Ultimately, all three models predicted posttreatment recurrence for early-stage HCC from pretreatment clinical, MRI, and both data combined [5]. 

Paradigm and Response Changes

Fortunately, the many recent advances in oncologic patient care are allowing physicians to move beyond nonselective cytotoxic therapies. Increasingly, our specialty will come to rely upon more targeted and personalized treatments for cancer: immunotherapies, stereotactic radiation, image-guided interventions, and theranostics. Alongside these novel approaches to cancer treatment, all houses of radiology will need to prop the door open for our specialty to evolve beyond tumor size measurement—recognizing the cumulative variability in the appearance of treatment responses and associated treatment toxicities by CT, MRI, PET, and a host of hybrid imaging. Given the proliferation of still evolving precision treatment pathways, abdominal, gastrointestinal, and genitourinary subspecialists must stay vigilant and informed. “Changing Paradigms in Tumor Response Assessment” aims to provide precisely that—a contemporary, rigorous update regarding the changing appearances of tumor response on multiple modalities and across a wide spectrum of tumors. I cordially invite you to join Jin-Young Choi, Joon-Il Choi, Natally Horvat, Katherine Krajewski, Jeong Min Lee, Sanghyeok Lim, Don Yoo, and me for the 2023 ARRS Global Exchange Featuring Korean Society of Radiology (대한방사선학회).

References

1. 2017 KSR-ARRS Global Partnership Breast Imaging Web Symposium. ARRS website. ARRS.org/ARRSLIVE/KSR_BR17/Home/ARRSLIVE/GlobalPartners/Symposia/KSR/BR17/Home.aspx. Accessed September 27, 2022
2. Ozturk K. Findings on Chest CT Performed in the Emergency Department in Patients Receiving Immune Checkpoint Inhibitor Therapy: Single-Institution 8-Year Experience in 136 Patients. AJR Podcast website. AJRPodcast.libsyn.com/chest-ct-findings-of-immune-checkpoint-inhibitor-therapy-related-adverse-events. Published January 14, 2021. Accessed September 27, 2022
3. Kim PH et al. Immune checkpoint inhibitor with or without radiotherapy in melanoma patients with brain metastases: a systematic review and meta-Analysis. J Korean Soc Radiol 2022; 83:808–829
4. Yoon J et al. Atypical manifestation of primary hepatocellular carcinoma and hepatic malignancy mimicking lesions. Korean J Radiol 2021; 22:584–595
5. Young LK. Machine Learning Models Predict Hepatocellular Carcinoma Treatment Response. ARRS website. ARRS.org/ARRSLIVE/Pressroom/PressReleases/Machine_Learning_Hepatocellular_Carcinoma_Treatment.aspx. Published August 17, 2022. Accessed September 27, 2022