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Summary CASE 5 radiomics and extra in-depth DNA repair
- Instelling
- Maastricht University (UM)
This is case 5 about radiomics, also, I added some extra depth about a previous case, DNA repair.
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Door: mgutta1225 • 1 jaar geleden
Voorbeeld van de inhoud
CASE 5: More than the eyes seesIn the field of medicine, radiomics is a method that extracts a large number of features from
radiographic medical images using data-characterisation algorithms. These features, termed
radiomic features, have the potential to uncover disease characteristics that fail to be
appreciated by the naked eye.[6] The hypothesis of radiomics is that the distinctive imaging
features between disease forms may be useful for predicting prognosis and therapeutic
response for various conditions, thus providing valuable information for personalized
therapy.[1][7][8] Radiomics emerged from the medical field of oncology and is the most
advanced in applications within that field. However, the technique can be applied to any
medical study where a disease or a condition can be imaged.
The goal of radiomics is to be able to use this database for new patients. This means that we
need algorithms that run new input data through the database which return a result with
information about what the course of the patients’ disease might look like. For example,
how fast the tumor will grow or how good the chances are that the patient survives for a
certain time, whether distant metastases are possible and where. This determines how the
further treatment (like surgery, chemotherapy, radiotherapy or targeted drugs etc.) and the
best solution which maximizes survival or improvement is selected. The algorithm has to
recognize correlations between the images and the features, so that it is possible to
extrapolate from the data base material to the input data.
2-How can you use radiomics to discriminate between different cancers?
You use the different characteristics. GLCL: also using different gray levels of tumors
(matrix). To diagnose the cancers, you need there are multiple steps. Different cancers also
have different heterogeneity, densities.
Handmade craft: person explains what you see, with less data
Keep-learning algorithm will learn what is what
Training data sets: give a machine a data set and see if it recognizes it.
1. Data selection. VOI (= box the tumor, not to precise)
2. Medical imaging
3. Feature extraction
4. Analysis
5. modeling
first you need to know where on the axis the cancers belong. Train a model on specific long
cancers. Also for another training data set. You will train them separately.
Radiomics hypoxia signature: can you see differences in microenvironments. Is a tumor
hypoxic yes or no. compare those features with hypoxia PET markers. Then a signature was
made with CT, then combine with radiomics PET ct. push the CT through radiomics toolbox,
then you know if a patient has a hypoxic tumor.
3-Different survivals with cancer
There is disease free survival rate,
progression free survival= disease, which was there, with no progression, at least not
disappears.
Event free rate survival= time that you are free of the disease you are treated for.
, median overall survival=half of people with treatment still living.
Survival= .
metastasis free survival=period until you have metastasis.
Survival rate= time people are alive after diagnosis. 5- and 10-years survival rate.
Overall survival= is patient alive, yes or no.
Fase 1: testing new medications on phase 4 patients. Testing: 2 out of 3 get maximum dose.
Then one step less dose than maximum for fase 2.
Fase 2: testing efficacy
Fase 3: compare to the drug that is now used
Fase 4: test the dose
4-What is prognostic value? Difference between prognostic and predictive value?
Prognostic: 60% in combination with other systems get up to 75%. Measured between
both, both had normal therapy but difference in response.
Predictive: patients who had no therapy and standard.
Single stranded
The basic pathway for repairing damage to DNA involves three basic steps:
1. The damaged DNA is recognized and removed by one of a
variety of mechanisms. These involve nucleases, which cleave
the covalent bonds that join the damaged nucleotides to the
rest of the DNA strand, leaving a small gap on one strand of
the DNA double helix in the region.
2. A repair DNA polymerase binds to the 3’-hydroxyl end of the
cut DNA strand. It then fills in the gap by making a
complementary copy of the information stored in the
undamaged strand. Although different from the DNA
polymerase that replicates DNA, repair DNA polymerases
synthesize DNA strands in the same way. For example, they
elongate chains in the 5’-to-3’ direction and have the same
type of proofreading activity to ensure that the template
strand is copied accurately. In many cells, this is the same
enzyme that fills in the gap left after the RNA primers are
removed during the normal DNA replication process.
3. When the repair DNA polymerase has filled in the gap, a break
remains in the sugar-phosphate backbone of the repaired
strand. This nick in the helix is sealed by DNA ligase, the same
enzyme that joins the Okazaki fragments during replication of the lagging DNA
strand.
Step 1 uses a series of different enzymes, each specialized for removing different types of
DNA damage. Humans produce hundreds of different protein that function in DNA repair.
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