How Does the Gompertz Equation Model Tumor Growth?

In summary: So all is good.In summary, the growth of cancerous tumors can be modeled by the Gompertz equation, where N(t) is proportional to the number of cells in the tumor, and r, K > 0 are parameters. The initial condition for this equation is when N0=K.
  • #1
Jamin2112
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12

Homework Statement



As long as N isn't too small, the growth of cancerous tumors can be modeled by the Gompertz equation,

dN/dt=-rN*ln(N/K),

where N(t) is proportional to the number of cells in the tumor, and r, K > 0 are parameters.

(a) Sketch the graph f(N)=-rn*ln(N/k) verses N, find the critical points, and determine whether each is asymptotically stable or unstable.

(b) For the initial condition N(0)=N0 (N0>0), solve the Gompertz equation for N(t). Does this agree with your results from (a) in the limit as t -->∞?

(c) Sketch N(t) vs. t for initial conditions (i) 0 < N0 < K, (ii) N0=K, and (iii) N0 > K.

Homework Equations





The Attempt at a Solution



(a)

Below is my sketch. I figured, since r,K,N>0 (can't have negative size of tumor), this is just a natural log function upside down and stretched out a little bit.

screen-capture-3.png


I'm not sure how to tell if it's asymptotically stable. I know that on the graph of N(t) versus t, it will start out with a positive slope; decrease in slope until the slope is zero at N(t)=K; then the slope will gradually become more negative.

(b)

dN/dt=-rN*ln(N/K)
==> dN / (N*ln(N/K) = -rdt
==> d/dN (ln(ln(N/K))) = -rdt
==> ln(ln(N/K) = -rt + C
==> ln(N/K) = e-rt+C = ©e-rt (©=ec. I'm going to merge my constant shizzle while I solve)
==>N/K = e©ert
==>N=N(t)= Ke©ert = ®e(-rt) (®=ke©)


... This is where I'm stuck. I've always been told that I can merge constants as I go along; but doing so in this problem screws everything up because I need K to stay with me!
 
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  • #2
Check your derivation : ln(ln(N/K) ) doesn't make sense when N <K. It's better to handle the 3 cases separately.
 
  • #3
Jamin2112 said:
Sketch the graph f(N)=-rn*ln(N/k) that should be f(N)=-rN*ln(N/k) verses N, find the critical points, and determine whether each is asymptotically stable or unstable.


I'm not sure how to tell if it's asymptotically stable. I know that on the graph of N(t) versus t, it will start out with a positive slope; decrease in slope until the slope is zero at N(t)=K; then the slope will gradually become more negative.

(b)

dN/dt=-rN*ln(N/K)
==> dN / (N*ln(N/K) = -rdt
==> d/dN (ln(ln(N/K))) = -rdt
==> ln(ln(N/K) = -rt + C
==> ln(N/K) = e-rt+C = ©e-rt (©=ec. I'm going to merge my constant shizzle while I solve)
==>N/K = e©ert
==>N=N(t)= Ke©ert = ®e(-rt) (®=ke©)


... This is where I'm stuck. I've always been told that I can merge constants as I go along; but doing so in this problem screws everything up because I need K to stay with me!

Your question suggests to me having been copied to here not quite accurately. At any rate a natural reading of the first sentence above seems to be asking for critical points of f. There is one maximum of f but that is an inflection point of N against t. It doesn't come to me to think stability is something you characterise inflection points by.

Confusion between f and N has made your red sentence all wrong but I am sure you will get it right when you realize that.

For the asymptotic stability you do not need to solve the d.e., you just need to look at the sign of f, i.e. of dN/dt, near N=0, and near the top limit N=K (both sides of that one).

For your problem with the arbitrary constant it is a bit fiddly.

You got to ln(N/K) = Ce-rt (I agree with your integration) and you are probably thinking (N/K) = eCe-rt, ah that's N = KeCe-rt my K seems to have been swallowed into a lumped arbitrary constant. But it hasn't - eCe-rt is not eCe-rt but (eC)e-rt, not the same as multiplying K by eC, think about it.
 

Related to How Does the Gompertz Equation Model Tumor Growth?

What is a tumor growth word problem?

A tumor growth word problem is a mathematical scenario that involves the growth of a tumor over time. It typically involves variables such as initial tumor size, growth rate, and time elapsed, and requires the use of equations and calculations to determine the final tumor size.

Why is understanding tumor growth important?

Understanding tumor growth is important for developing treatments and interventions for cancer. By studying the growth patterns of tumors, scientists and doctors can better predict how a tumor may progress and develop more effective ways to slow or stop its growth.

What factors influence tumor growth?

Tumor growth can be influenced by various factors, such as genetics, environmental factors, and lifestyle choices. Additionally, the type and location of the tumor can also play a role in its growth rate.

How do scientists study tumor growth?

Scientists study tumor growth through a combination of experimental methods and mathematical modeling. They may use cell culture experiments, animal models, and clinical trials to gather data on tumor growth, and then use mathematical equations to analyze and interpret this data.

What are some potential applications of tumor growth word problems?

Tumor growth word problems can have various applications, such as helping doctors determine the most effective treatment plan for a patient, predicting the growth and spread of tumors in the body, and evaluating the effectiveness of different cancer treatments.

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