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Helping hands – Robotic surgery in modern oncology

by ecancer reporter Will Davies

It is, as many of our interviewees have told us, a very exciting time to be working with cancer.

Pathologic detection and cellular subtyping is a wellspring of ever more biomarkers for disease status and treatment.

Radiotherapy courses are becoming increasingly tailored with personalised schedules and intensities.

Chemotherapeutics now sit in combination with treatment modalities that did not exist a decade ago.

From detection of disease through to palliative care, there is no stage of treatment that has not been revolutionised.

In this age of modern marvels, it seems almost archaic that surgical intervention remains among the most effective means of disease control for solid tumours.

Of course, surgery is as much a field of advance as any other healthcare aspect.

The leap from open surgery to laparoscopic surgery, was a game changer in its own right.

Laparoscopic, or keyhole, surgery, has taken a stratospheric course from animal experiments at the turn of the last century.

While laparoscopic cholecystectomy was first performed in 1987 1, it is now the first choice for the ~600,000 cholecystectomies per year that take place in America alone.

Advancing on laparoscopic techniques pioneered above, robotic surgery has become increasingly entrenched in hospitals and the healthcare market.

With modern retrospect, it seems almost inevitable that more fully robotised surgery would follow, with improved imaging and more responsive interfaces enabling surgeons to act on a much smaller scale.

Popularity of robotic surgical units has boomed following the 2001 success of Lindbergh, in which a gall bladder in a woman in Strasbourg was removed by a surgical team in New York2 .

Many of the drawbacks surgeons experienced with keyhole instruments (reduced sense of touch, lack of 3D visualisation) remain, serving as an essential training ground for developing feedback systems into robotic units, and though other senses may be diminished with distance, the finest human manual dexterity (~200um) seems clumsy compared to the exact incisions possible with a robotic interface (~10um)3.

Talk about precision medicine.

Through the keyhole

In treating abdominal and thoracic tumours, surgeons have the benefit of the longest history of laparoscopic techniques to build on.

With surgical resection the first choice for treating early stage lung cancer, robot assistance in lobectomies is proving safe, even advantageous in difficult cases4.

Breast cancer patients, having a tremendous boost in survivorship over the last 50 years5, are today embracing risk-reducing mastectomy (RRM) upon detection of aggressive BRCA biomarker mutations.

This is, in no small way, built on successive advances in cosmetic and reconstructive surgeries6, and the satisfaction and quality of life of women undergoing preventative surgery remains high7.

While the cosmetic, social and psychological prospects of mastectomies can lean heavily on this history8, the potential of minimally invasive surgery twinned with oncoplastic techniques may offer a fully finessed surgical path.

The latest trials in robotic reduced-port surgery for gastric cancers show similar promise 9, and may benefit from a matched boost in surgical expertise with the increasing trend of bariatric surgeries10 and the historic precedent of robotic assisted surgery in cholecystectomy3.

For neck, thyroid and upper gastric cancers, indications of safety and feasibility are now coming from Japan11,12 , and the US13 .

The Lancet recently debuted the very first results comparing the quality of life of patients with localised prostate cancer who had received robotic surgery, finding equivalent urinary and sexual function after 3 months to those who had received open surgery14,  though success with robotic approaches and laparoscopic surgery in treating rectal cancer is mixed15, 16, 17 .

In a review of robotic advances for treating ovarian cancer, Minig et al18 note that, while robotic-assisted and conventional laparoscopy for early ovarian cancer have similar outcomes, the shorter learning curve for robotic assistance may make surgical stagings of this kind open to a wider number of patients.

There also seems to be equivalence of outcomes for endometrial cancer patients19,20 , and in treating colorectal cancer21.

A recent meta-analysis of robotic vs laparascopic partial nephrectomy reported that a robotic partial nephrectomy is favourable over laparoscopic22, in a move going beyond the equivalence described in other indications above.

Commentators were quick to highlight23 what may end up being the deciding issue for choosing surgical modalities in the future -  the brute math that monetary cost is higher with robots, and outcomes are statistically the same24 .

This higher cost, equal outcome ratio is even high in other indications25,21 though there are, of course, counterpoints to be made where the overall cost is lower than open surgery26.

The cost per surgery can be further weighed against investment in staff training reportedly shortening learning curves, meaning more surgeons performing more surgeries over time27.

This training is its own point of contention, with diverging expectations of training time and medium 39, and when, how, and under whose purview to integrate guidelines and new technologies28.

All of this hasn’t slowed adoption and widening of indications29, which may bear out arguments for investing time and training into a robotic unit, though the forces driving this adoption may not be entirely clinical either.

Thanks, in no small part, to a marketing effort targeting both hospitals and patients30, a hospital without a robotic unit is assumed to simply not be as good as one with it31. Even if what a robotic surgical unit is for, capable of, or perceived as by the public, does not match up with empirical evidence32.

How much of that is marketing hyperbole and how best to ground expectations is yet to be seen, but through influencing patient impressions, preference, and eventually ‘demand’ for robotic units33, the robotic claw is now being operated by ‘the invisible hand’.

In this way, robotic surgical units might be a peak example of the uneven distribution of wealth buying an uneven distribution of health34.

Just as the ‘Moonshot’ of personalised therapy has been anchored by calls for a groundshot of making the most of existing therapies, for the most of patients, consolidation and global distribution of best-available manual surgical practices may offer more benefits to the dollar than a daVinci unit, plus staff.

Facing the future

Last year saw the first International Workshop on Robotic Surgery in Thoracic Oncology4, in which advances and trials of robotic interventions were shared for the first time in the disease indication. 

Some advances proposed for operating theatres sound as if they have been freshly plucked from science fiction, including an honest-to-Roddenberry laser scalpel and an implantable chemo-sensing, drug-delivering plantoid, which grows in an arboreal manner through tissues towards its goal.

Increased targeting and resolution for surgery with new scanning technology is one avenue of development that been seen developing day by day, with some touting virtual reality as the next frontier in surgeon training and telemedicine.

Some anecdotal evidence supports this35, with familiarity and confidence upped.

Twinned with telesurgery, a surgeon may soon have a very intimate knowledge of patients they’ve never met.

Finally, the holy grail of technological progress, artificial intelligence (or at least, its boxed-in baby brother ‘machine learning’) is already exerting its algorithmic influence over, patient care36, drug design37, successfully predicting novel phenotypes in models38.

Does that mean medical professionals can sit back and let their robots do the talking?


Seeing as the future is famously uneven in its distribution, assisting or automating one aspect of healthcare by no means invalidates the experience of doctors working around the globe.

But just as the space race in the 60s brought the world Velcro, foam fire extinguishers, freeze dried fruit and digital thermometers, advances in micro-dexterous robotic interfaces could impact the world in ways we cannot now predict.

Whether it works out saving money or not, these units and their surgeons are saving lives now.

And that seems like a good start to me.


  1. Wyld, Lynda, Riccardo A. Audisio, and Graeme J. Poston. "The evolution of cancer surgery and future perspectives." Nature Reviews Clinical Oncology 12.2 (2015): 115-124.
  2. Diana, M. and Marescaux, J. (2015), Robotic surgery. Br J Surg, 102: e15–e28. doi: 10.1002/bjs.9711
  3. Satava, Richard M. "Surgical robotics: the early chronicles: a personal historical perspective." Surgical Laparoscopy Endoscopy & Percutaneous Techniques 12.1 (2002): 6-16.
  4. Veronesi, Giulia, et al. "report on First international Workshop on robotic surgery in thoracic Oncology." Frontiers in Oncology 6 (2016).
  5. Cancer Research UK. Cancer statistics; key facts: all cancers combined [online], (2014
  6. Hooker, G. W. et al. Long-term satisfaction and quality of life following risk reducing surgery in BRCA1/2 mutation carriers. Hered. Cancer Clin. Pract. 12, 9 (2014).
  7. Rozen, W. M., Rajkomar, A. K., Anavekar, N. S. & Ashton, M. W. Post-mastectomy breast reconstruction: a history in evolution. Clin. Breast Cancer 9, 145–154 (2009).
  8. Macmillan, R. Douglas, and Stephen J. McCulley. "Oncoplastic Breast Surgery: What, When and for Whom?." Current Breast Cancer Reports 8.2 (2016): 112-117
  9. Lee, Seungho, et al. "Safety and feasibility of reduced-port robotic distal gastrectomy for gastric cancer: a phase I/II clinical trial." Surgical Endoscopy (2017): 1-8
  10. Memarian, Ensieh, et al. "Sociodemographic differences and time trends of bariatric surgery in Sweden 1990–2010." Obesity surgery 24.12 (2014): 2109-2116
  11. Fujiwara, Kazunori, et al. "Preliminary study of transoral robotic surgery for pharyngeal cancer in Japan." Journal of robotic surgery 10.1 (2016): 11-17.
  12.  Suda, Koichi, et al. "Robotic Surgery for Upper GI Cancer: Current Status and Future Perspectives." Digestive Endoscopy (2016).
  13. DeLong, Jonathan C., et al. "The benefits and limitations of robotic assisted transhiatal esophagectomy for esophageal cancer." The Journal of Visualized Surgery 2.9 (2016).
  14. Yaxley, John W., et al. "Robot-assisted laparoscopic prostatectomy versus open radical retropubic prostatectomy: early outcomes from a randomised controlled phase 3 study." The Lancet 388.10049 (2016): 1057-1066.
  15. Baukloh, J. K., et al. "Evaluation of the robotic approach concerning pitfalls in rectal surgery." European Journal of Surgical Oncology (EJSO) (2017).
  16. Arezzo, Alberto, et al. "Laparoscopy for rectal cancer is oncologically adequate: a systematic review and meta-analysis of the literature." Surgical endoscopy 29.2 (2015): 334-348
  17. Hellan, Minia, et al. "Robotic rectal cancer resection: a retrospective multicenter analysis." Annals of surgical oncology 22.7 (2015): 2151-2158
  18. Minig, Lucas, et al. "Robotic surgery in women with ovarian cancer: surgical technique and evidence of clinical outcomes." Journal of minimally invasive gynecology 23.3 (2016): 309-316.
  19. Nevis, Immaculate F., et al. "Robot-assisted hysterectomy for endometrial and cervical cancers: a systematic review." Journal of Robotic Surgery (2016): 1-16.
  20. Pant, Alok, Julian Schink, and John Lurain. "Robotic surgery compared with laparotomy for high-grade endometrial cancer." Journal of Robotic Surgery 8.2 (2014): 163-167.
  21. Ramji, Karim M., et al. "Comparison of clinical and economic outcomes between robotic, laparoscopic, and open rectal cancer surgery: early experience at a tertiary care center." Surgical endoscopy 30.4 (2016): 1337-1343.
  22. Choi, Ji Eun, et al. "Comparison of perioperative outcomes between robotic and laparoscopic partial nephrectomy: a systematic review and meta-analysis." European urology 67.5 (2015): 891-901.
  23. Stolzenburg, Jens Uwe, Iason Kyriazis, and Evangelos Liatsikos. "Re: Comparison of Perioperative Outcomes Between Robotic and Laparoscopic Partial Nephrectomy: A Systematic Review and Meta-analysis." European Urology 69.6 (2016): 1159-1160.
  24. George, Arvin K., Christopher Hartman, and Louis R. Kavoussi. "Robotic partial nephrectomy: the Will Rogers surgical effect." (2016): 7-8.
  25. Covens, Al, et al. "Cost-Efficiency of Robotic Surgery." International Journal of Gynecological Cancer 26.6 (2016): 992-993.
  26. Daskalaki, Despoina, et al. "Financial Impact of the Robotic Approach in Liver Surgery: A Comparative Study of Clinical Outcomes and Costs Between the Robotic and Open Technique in a Single Institution." Journal of Laparoendoscopic & Advanced Surgical Techniques (2017).
  27. Guend, Hamza, et al. "Developing a robotic colorectal cancer surgery program: understanding institutional and individual learning curves." Surgical Endoscopy (2016): 1-9.
  28. Brinkman, S et al. "Training robotic surgery in urology: experience and opinions of robot urologists". Int J Med Robotics Comput Assist Surg, 11, 308–318. (2015)
  29. Friedrich, Daniel T., et al. "Recent advances in robot‐assisted head and neck surgery." The International Journal of Medical Robotics and Computer Assisted Surgery (2016).
  30. Schiavone, Maria B., et al. "The commercialization of robotic surgery: unsubstantiated marketing of gynecologic surgery by hospitals." American journal of obstetrics and gynecology 207.3 (2012): 174-e1.
  31. Boys, Joshua A., et al. "Public perceptions on robotic surgery, hospitals with robots, and surgeons that use them." Surgical endoscopy 30.4 (2016): 1310-1316.
  32. Irani, Mohamad, et al. "Patient Perceptions of Open, Laparoscopic, and Robotic Gynecological Surgeries." BioMed Research International 2016 (2016).
  33. Dixon, Peter R., Robert C. Grant, and David R. Urbach. "The impact of marketing language on patient preference for robot-assisted surgery." Surgical innovation 22.1 (2015): 15-19.
  34. Chan, John K., et al. "The centralization of robotic surgery in high-volume centers for endometrial cancer patients—a study of 6560 cases in the US." Gynecologic oncology 138.1 (2015): 128-132.
  35. "Look Twice, Cut Once". N.p., 2017. Web. 10 Mar. 2017
  36. "Artificial Intelligence Virtual Consultant Helps Deliver Better Patient Care. Ecancer - News". N.p., 2017. Web. 9 Mar. 2017.
  37. Kadurin, Artur, et al. "The cornucopia of meaningful leads: Applying deep adversarial autoencoders for new molecule development in oncology." Oncotarget 8.7 (2016): 10883-10890.
  38. Lobo, Daniel, Maria Lobikin, and Michael Levin. "Discovering novel phenotypes with automatically inferred dynamic models: a partial melanocyte conversion in Xenopus." Scientific Reports 7 (2017).
  39. Nolan, Heather R., M. D. D Benjamin Christie III, and Dennis W. Ashley. "Comparison of Attending and Resident Surgeons' Opinions of Robotic Surgery Training in General Surgery Residency." The American Surgeon 81.8 (2015): E303.





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