由中国抗癌协会主办，天津医科大学肿瘤医院、天津市抗癌协会、中国整合医学发展战略研究院承办的“2023中国整合肿瘤学大会（2023 CCHIO）”将于2023年11月16—19日在天津举办。世界卫生组织国际癌症研究机构（WHO IACR）负责人Partha Basu教授将在会上就癌症筛查的AI发展和未来予以介绍。《肿瘤瞭望》就此开展特别采访，邀请Partha Basu教授分享全球癌症筛查面临的挑战、AI的发展以及中国的贡献。
编者按：由中国抗癌协会主办，天津医科大学肿瘤医院、天津市抗癌协会、中国整合医学发展战略研究院承办的“2023中国整合肿瘤学大会（2023 CCHIO）”将于2023年11月16—19日在天津举办。世界卫生组织国际癌症研究机构（WHO IACR）负责人Partha Basu教授将在会上就癌症筛查的AI发展和未来予以介绍。《肿瘤瞭望》就此开展特别采访，邀请Partha Basu教授分享全球癌症筛查面临的挑战、AI的发展以及中国的贡献。
Editor’s Note:Organized by the China Anti-Cancer Association and hosted by Tianjin Medical University Cancer Institute&Hospital，Tianjin Anti-Cancer Association，and the China Research Institute of Development Strategies of Holistic Integrative Medicine，the"2023 Chinese Congress of Holistic Integrative Oncology(2023 CCHIO)"will be held in Tianjin from November 16th to 19th，2023.Dr Partha Basu，the head of the Cancer Early Detection&Prevention Branch at the International Agency for Research on Cancer(IARC)of the World Health Organization(WHO)，will give the presentation of“Artificial intelligence and future of cancer screeningt”at the CCHIO conference.Oncology Frontier conducted a special interview to invite Dr Partha Basu to share the challenges of global cancer screening，the development of AI，and China’s contributions.
Oncology Frontier:What challenges do you think the current global cancer screening is facing?
Dr.Partha Basu:The WHO conducted a modeling study to determine the milestones required to be achieved to eliminate cervical cancer.Through our observations，we determined that achieving the elimination target by the end of this millennium necessitates ensuring high screening coverage--at least twice in a lifetime screening for 70%of the age-eligible women along with vaccination of girls below 15 years of age.Additionally，it is crucial to guarantee the appropriate quality of the screening test.Currently，it can be stated with near certainty that the human papillomavirus(HPV)test is an exceptional test with high accuracy.We must also ensure that women who are diagnosed with pre-cancerous and cancerous lesions receive treatment.However，there are challenges in many aspects of the screening continuum.
Foremost are the barriers that a women encounters to access screening services.Women face numerous barriers due to social reasons，economic reasons，and their limited awareness of cervical cancer prevention.Therefore，there are barriers at the level of women.
There are even more significant barriers，which we refer to as structural barriers or health system barriers.In many countries，particularly low-and middle-income countries，we have yet to establish a system that can guarantee high coverage for women，ensure the provision of high-accuracy testing，and ensure appropriate management of positive screening results.HPV tests are still quite expensive and unavailable in many limited resourced settings.
By adopting a screen-and-treat approach，we can effectively treat many women through thermal ablation，resulting in a high compliance rate for treatment.However，approximately 30%to 40%of women require excisional treatment，also known as LEEP.This poses a significant challenge since these women need to be referred to specialized centers.In many areas，such facilities are not well-organized，leading to a high attrition rate in women seeking treatment.Therefore，achieving a high coverage of women and particularly offering them HPV detection tests involves several levels of barriers.As I mentioned earlier，we must address these barriers to ensure successful outcomes.
Oncology Frontier:What is the application value of artificial intelligence in global cancer screening?
Dr.Partha Basu:Artificial intelligence(AI)holds a great potential in ensuring high-quality cancer screening.In many countries，AI-based cancer screening is being evaluated and mainly focuses on breast cancer，cervical cancer，colorectal cancer，and lung cancer.AI examines the pattern or repetitive data linked to‘ground truth’，the final diagnosis，and tries to interpret it to produce a diagnosis as a result.This principle has been applied in cancer screening in different aspects.
Firstly，in cervical cytology，there are already validated AI-based applications，which are approved in some countries for interpreting cervical cytology.These applications have been found to perform well in cytology reading.However，when discussing cytology，it is important to recognize that the challenge is not just in reading the cytology，especially for low-and middle-income countries.Ensuring good quality sample collection and having available well-trained laboratory technicians who can produce high-quality slides is crucial.If the slide quality is poor，even the best AI technology will not work effectively.This is an example where AI has been developed and is functioning，but there are several gaps in practical applications.
Secondly，AI can examine the patterns visible in mammography films to identify malignant lesions，differentiate between benign and malignant lesions，or identify truly normal mammograms.Extensive studies have been conducted and highly effective algorithms have been developed after being trained on thousands of mammography images.In many European countries each negative mammogram should be reviewed by a second reader.We can use an AI-based algorithm to read negative mammograms instead of a second reader.This approach is supported by strong evidence and has already been recommended in European guidelines.You can see that AI is gradually being incorporated into cancer screening.Similarly，for colorectal cancer screening，AI has been found to be highly effective in detecting lesions during colonoscopy.
Thirdly，AI can be employed to assist in the diagnosis of cervical precancers and cancers through evaluation of images collected after application of acetic acid(VIA).In cervical cancer screening，our primary focus is on ensuring the screening and management of women in low-and middle-income countries，where several different opportunities arise.One such opportunity is visual inspection with VIA，which has shown great promise.At least it is much better than doing cytology in a low-and middle-income country setting.However，the main challenge of VIA is that it is subjective and requires extensive training of the providers to perform high-quality VIA assessments.Using the same principles AI algorithms can be trained to interpret cervical images.Extensive work is ongoing，including an International Agency for Research on Cancer study that is exploring AI-based systems to recognize patterns visible in cervical images after the application of acetic acid or Lugol’s solution.In a screening setting，women are examined by nurses who apply acetic acid to the cervix，capture the image，and then an AI-based algorithm provides the diagnosis.
Furthermore，we believe that AI holds greater potential in the triage of HPV-positive women.As you are aware，the landscape of HPV testing is gradually shifting.There are several technologies now available worldwide.Affordability will improve over time.HPV self-sampling has created a significant opportunity to improve compliance among women，particularly in limited-resource settings.Women can now opt for HPV testing and provide self-collected samples，but positive cases require examination through triage to identify those with lesions and those without lesions.Additionally，decisions need to be made on whether they should undergo ablation or excisional treatment.This is where AI truly shines.
Therefore，an AI-based analysis of cervical images or the appearance after VIA is a very possible approach for triaging HPV positive women，which is a very promising aspect，but we still need to have appropriately trained algorithms.We need to validate the algorithm in a field setting，and that is exactly what a large IARC trial is doing in Zimbabwe.So we have developed an algorithm and trained the algorithm over the last two years using thousands of images collected from Thailand，India，and other countries.This algorithm will be field-tested in Zimbabwe.So this is，we think，a very promising project.We have come to the realization that for AI development to achieve good quality results，good quality images are necessary.Therefore，the original concept of simply using a mobile phone to capture an image of the cervix for AI analysis may not be entirely practical.As such，we are also developing an image-capturing device that will ensure high-quality image capture，which can then be used by the AI for diagnosis.
AI is a highly promising field，but there are still many unanswered questions.For instance，the trust of women and those being screened in the AI system remains an unresolved issue.Similarly，the trust of healthcare professionals in AI has yet to be addressed.There are also several ethical and legal concerns，such as who would be responsible if an AI-based algorithm makes a mistake.These are matters that we still need to resolve.
Oncology Frontier:Do you have any expectation or call for cooperation between CACA and academic groups around the world to jointly promote the improvement of cancer screening levels?
Dr.Partha Basu:Our colleagues in China have made immense contributions to our understanding of the accuracy of various testing and triaging technologies，including treatment methods，particularly for cervical precancers in community settings.The screening programs that exist in China in rural and urban areas，are large-scale programs，and several studies have been nested within these programs to generate extremely valuable evidence not only for breast and cervical cancer screenings，but also for some of the uncommon screening sites such as gastric and esophageal cancers，as well as liver cancer.Therefore，I believe that the collaborative atmosphere fostered by CACA will assist the global community in terms of exchanging ideas，sharing information，and guiding global policies.Numerous studies conducted by our colleagues in China have significantly informed the WHO guidelines for cervical cancer screening and management published in 2021 and 2022.Additionally，in the realm of AI，China has published numerous studies examining AI-based systems in different aspects of cancer screening continuum.
It is essential to collaborate with the global community，as we recognize that AI has a population-specific element.This implies that an AI developed using data and images from the Chinese population may not perform equally well when applied to populations in Africa，and vice versa.Therefore，greater collaboration is necessary when it comes to the development of AI across diverse global communities.This ensures trustworthy systems that can perform equally well in Chinese，Asian，African，or Latin American populations.It is crucial to eliminate any bias in AI development to promote inclusivity and enhance the accuracy of these systems.
Another significant contribution of China to global efforts in improving cancer screening is by introducing more affordable testing options，which have been thoroughly validated in China.Many of these tests are already being utilized in China and beyond.Due to the vast scale of production，the costs of consumables and technologies developed in China are more affordable compared to similar technologies developed elsewhere in the world.Hence，I firmly believe that CACA’s initiative to foster a more collaborative research environment，particularly in cancer early detection and prevention，is highly commendable.