Cancer Moonshot

The Biden administration “reignited” the US’ Cancer Moonshot initiative, setting a goal to halve the country’s age-adjusted cancer death rate within the next 25 years. Here’s how they plan to achieve this “Moonshot” of a goal, and what that means for imaging.

Cancer Moonshot History – Biden spearheaded the Obama administration’s Cancer Moonshot initiative, inspired by losing his son to brain cancer. The 7-year initiative used $1.8B in federal funding to improve cancer therapeutics, prevention, and detection through scientific discovery, collaboration, and data sharing.

The Reignited Moonshot – The revamped initiative inherits these same goals and approaches, while adding new focus areas and operational structures:

  • Overcoming the COVID pandemic’s cancer screening backlog
  • Addressing inequity in cancer incidence, detection, and care
  • Developing new treatments for rare and childhood cancers
  • Fast-tracking the development of multi-cancer tests
  • Improving the experience of cancer survivors and caregivers
  • Leveraging data to “turn our cancer care system into a learning system”
  • Creating a cancer research funding program modeled after DARPA
  • Appointing federal Cancer Moonshot leaders to coordinate this work

Imaging Alignment – Any government attempt to overcome cancer screening backlogs and to make early detection mainstream would surely result in more imaging, while the Moonshot initiative’s focus on “learning from data” could hold imaging AI upsides. That said, the announcement placed a much brighter spotlight on non-imaging areas (blood tests, vaccines, treatments), and few people on the clinical side of radiology believe more imaging is necessarily better for patients.

Moonshot Critics – The Cancer Moonshot initiative has its fair share of critics, who argued that cutting cancer deaths by 50% would require “curing” cancer (not just catching and treating it), expanding screening has downsides (radiation, unnecessary treatments), and that initiatives like this are largely done for appearances.

The Takeaway
The White House just made the fight against cancer a top administrative priority, meaning that a lot more government attention and resources are on the way, and notable changes in cancer imaging policies and volumes might follow.

The AMA’s Quantitative Codes

The American Medical Association issued new CPT III codes for CT and MRCP quantification (see page 4), representing key milestones for quantitative and incidental/population health imaging.

CT Quantification Codes – The AMA’s 2022 CPT III update includes two new codes for quantitative CT tissue characterization, interpretation, and reporting. These codes could be a big deal for AI firms and radiology departments hoping to launch CT-based population health solutions (and eventually bill for them), such as Nanox AI’s HealthCCSng CAC scoring product and UCSF’s automated CAC scoring system. They also come just six months after the AMA added a similar CPT III code for using AI to automatically detect vertebral fractures in existing CT scans (covering Nanox AI’s VCF solution).

MRCP Quantification Codes – The AMA also added CPT III codes for quantitative magnetic resonance cholangiopancreatography (QMRCP) interpretation and reporting. These codes are a solid step for MRCP quantification products like Perspectum’s MRCP+ and could help drive adoption for this far less-subjective MRCP interpretation method. In the process, it might even change ERCP’s role to a purely therapeutic procedure.

About CPT III Codes – Since there’s often confusion about CPT III codes, it’s worth noting that they are intended to help collect clinical data for emerging technologies / procedures to support future coverage and regulatory decisions. CPT III codes don’t have assigned RVUs, so actual reimbursements would be up to payors.

The Takeaway

It’s pretty clear that the AMA is starting to see value in image quantification, AI, and incidental detection. In the last six months the AMA has issued four quantitative imaging CPT III codes, all of which directly support key imaging AI use cases (CT tissue characterization, CT vertebral fracture detection, ultrasound tissue characterization, MRI post-processing) and two that support key population health and incidental detection applications (CT tissue characterization, CT vertebral fracture detection). 

The Diagnostic Gap

The Lancet Commission on Diagnostics just put a spotlight on the developing world’s alarmingly low access to diagnostics and how this situation can be addressed. 

The LMIC Gap – An unbelievable 47% of the global population has little to no access to diagnostics, with the vast majority of this diagnostic gap concentrated in low and middle-income countries (LMICs). This problem is greatest through LMICs’ primary care facilities (19% of people can access PCs w/ diagnostics), but also exists in hospitals (60%-70% of people can access hospitals w/ diagnostics).

The Impact – About 50% of people living with any of six key conditions in LMICs are undiagnosed (hypertension, type 2 diabetes, HIV, tuberculosis, syphilis & hepatitis B virus infection in pregnant women), making diagnostic access the world’s single greatest barrier to care. If undiagnosed rates for these six conditions were reduced to 10% in LMICs, it would avoid 1.1m premature deaths annually.

The Imaging Gap – There is a significant lack of imaging access in LMICs. Imaging access is lowest in primary care where only 5% of basic facilities and 12% of advanced facilities have ultrasound (never mind more advanced imaging). Meanwhile only 36% to 87% of hospitals in LMICs have working X-ray systems and just 2% to 29% of hospitals have a CT scanner (depending on the country).

The Problem – The authors largely blamed the developing world’s diagnostic gap on a lack of visibility and prioritization, although there’s a long list of other factors (corruption, costs, infrastructure, workforce).

The Solutions – The Lancet Commission believes that recent technology and informatics innovations could accelerate government efforts to improve diagnostic access. Until then, they recommend that LMICs develop national diagnostics strategies, ensure that standard diagnostic tests are available at various healthcare tiers (e.g. ultrasound at all primary care facilities), and prioritize improving diagnostic access through primary care facilities.

One Takeaway – Half the world doesn’t have access to diagnostics. This is mainly an economic problem, but imaging could play an outsized role in the solution considering that many of the latest imaging innovations are well suited for low-resource areas (e.g. handheld POCUS, AI diagnostics/guidance, portable MRI, teleradiology, etc.).

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-- The Imaging Wire team