[Cidrz] Script for the Demo Video

[Gari Clifford]

Hi Leo,

that's great. Only two thoughts:
1. the term "long pre-clinical phase" sounds like a drug development
trajectory.
How about "extended period of development before serious symptoms are
noticed"?
2. You can say "is likely to" rather than  "may" when you talk about the
possibility of classifying images using AI. We know we can do it, the only
major challenge (I think) is "can we get high enough quality images to train
on, and train care workers to take good photos?" (or provide real time
feedback from the device about when the photo is bad - an essential facility
you would need for the latter wound care example you talk about where a
non-expert [the patient] is taking the photo)?

-Gari

2008/5/3 Leo Anthony Celi <leoanthonyceli at yahoo.com>:

> This is 4 minutes and 56 seconds on rehearsal.
> **
> *Script for the Demonstration Video*
> Around the world, a woman dies of cervical cancer every 2 minutes.  Over
> 80% of the deaths occur in the developing world, with sub-Saharan Africa
> being the worst-affected .  This is likely a consequence of the spread of
> HIV in the region.  Transmission of the human papilloma viruses that cause
> cervical cancer is facilitated by the presence of HIV infection.  In
> addition, progression is accelerated by the immunosuppression that results
> from HIV.
> In Zambia, cervical cancer strikes 63 women in 100,000, affecting women at
> a time of life when they are critical to social and economic stability.  But
> cervical cancer has a long pre-clinical phase, and thus, is highly
> preventable through yearly pap smears that facilitate detection and
> treatment of pre-cancerous lesions.  Such screening, which is routine in
> countries like the US, is not possible in most countries because of the
> resources it requires.
> Visual inspection of the cervix after painting with vinegar, or VIA, to
> detect pre-cancerous lesions has emerged as a cheaper alternative in
> developing countries.  Studies have demonstrated that this cheaper
> prevention program is effective in reducing the incidence of and the death
> rate from cervical cancer.
> Since 2006, through the Center for Infectious Disease Research in Zambia
> or CIDRZ, ??? have undergone cervical cancer screening through VIA performed
> by nurses.  In up to 10% of cases, it is difficult to say whether the
> findings on VIA are precancerous or not.  Currently, the nurses would err
> on the safe side, diagnose these indeterminate cases as precancerous, treat
> them with cryotherapy, and arrange follow-up visits for these women.  A
> significant number of false-positives is thus inevitable in this set-up,
> leading to unnecessary follow-up visits.  This further constrains an
> already severely-constrained labor resources.  Needless to say, input from
> a specialist would be very helpful in these situations.
> The goal of this project is to facilitate, using information and
> communication technology, real-time specialist support for nurses.  This
> is the only way to be able to scale cervical cancer screening using VIA to
> the rest of the country.
> We developed a software application that allows the nurses to take
> photographs of the cervix, and transmit the images accompanied by relevant
> clinical information to a central server using GPRS.  The server then
> alerts a specialist-on-call that a nurse is requesting decision support.  The
> URL of the image and the clinical information is sent to the doctor via MMS.
> The doctor then calls the nurse and reviews the case after accessing the
> data from the server, and a decision is made.  The plan of treatment is
> entered into the central server by the doctor.
> Archiving and information management at a central server is necessary in
> order to be able to track the progress of a patient, including clinical
> outcomes.  It is also crucial for quality assurance and quality
> improvement.  All the images, diagnosis and treatment plans are reviewed
> by the nurses and specialists regularly at a later time.  What we'd like
> to see is a reduction over time of not only misdiagnoses, but also of
> indeterminate cases requiring specialist support.  Finally, once a large
> database of cervical images has accumulated that are linked to both
> diagnoses that have been QA'd and clinical outcomes, it may be possible to
> come up with artificial intelligence tools that can classify images of
> indeterminate cervical lesions, further reducing the need for specialist
> support.
> Although this software application was initially developed to facilitate
> cervical cancer screening, it will be useful for a wide variety of scenarios
> in health care delivery.  Consider this hypothetical case.  A gentleman
> from a far-flung region is brought to Lusaka complaining of abdominal pains.
> A blockage is found in his intestines, requiring an operation to remove a
> portion of his intestines.  He is discharged after the surgery with
> instructions for regular follow-up to monitor the healing of the wound from
> the operation.  A week later, the patient notices some redness around the
> edges of the wound.  But because it is a full-day trip to Lusaka, he
> decides against the trip and he monitors the wound himself. A few days
> later, the patient dies as a result of a massive infection of the surgical
> wound.  This software application can be a tremendous help for follow-up
> of patients who live in remote areas, especially if visual inspection is
> crucial in the clinical examination, such as in dermatology and wound care.
>
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>
>


-- 
G. D. Clifford, PhD, SMIEEE
Principal Research Scientist,
Massachusetts Institute of Technology,
Instructor in Biomedical Engineering, HST,
(Harvard-MIT Division of Health Sciences & Technology)
Engineering Manager for the L.C.P. at M.I.T.
(Laboratory for Computational Physiology),
Rm E25-505DA, 45 Carleton St., Cambridge MA 02142
Tel: +16172537937 / +448444368530
Fax: +16172587859 email: gari at alum.mit.edu
http://alum.mit.edu/www/gari
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