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Imaging-Biomarkers; from discovery to validation

Author: Dror Nir, PhD.

Preface

Recent technology advances such as miniaturization and improvement in electronic-processing components is driving increased introduction of innovative medical-imaging devices into critical nodes of major-diseases’ management pathways. Similarly, medical imaging bears outstanding potential to improve the process of drugs development and regulation (e.g. companion diagnostics and imaging surrogate markers. In; The Role of Medical Imaging in Personalized Medicine I discussed in length the role medical imaging assumes in drugs development.  Integrating imaging into drug development processes, specifically at the early stages of drug discovery, as well as for monitoring drug delivery and the response of targeted processes to the therapy is a growing trend. A nice (and short) review highlighting the processes, opportunities, and challenges of medical imaging in new drug development is: Medical imaging in new drug clinical development. An important aspect of drug development that is largely discussed is facilitating testing of the new drug through clinical studies. A major hurdle in development of many anti-cancer drugs is the long time that is required to determine the efficacy of the new drug through measurement of clinically meaningful endpoints; e.g. overall survival. Imaging is offering the opportunity to determine surrogate markers of clinical outcome (as a substitute for a clinically meaningful endpoints). The need for surrogate outcome markers is especially great with newer agents that may act by tumour stabilization as opposed to shrinkage.

To comply with current trends; e.g. personalized medicine and evidence-based medicine, medical imaging must support quantification of meaningful pathological phenomena; e.g. morphological deformations, enhanced/reduced chemical reactions, presence/absence of biological substances etc….

 

Two examples: 

Molecular imaging (e.g. PET, MRS) allows the visual representation, characterization, and quantification of biological processes at the cellular and subcellular levels within intact living organisms. In oncology, it can be used to depict the abnormal molecules as well as the aberrant interactions of altered molecules on which cancers depend. An established biological process is neoplastic angiogenesis is associated with a number of detectable changes at molecular and microcirculatory levels. In Positron emission tomographic imaging of angiogenesis and vascular function the authors are offering that direct study of angiogenic molecular biology and tumour circulation before during and after treatment may offer useful surrogate markers for vascular-targeted therapies. The paper reviews two main areas: (a) the methodology behind PET imaging of tumour blood supply with 15O-oxygen labelled compounds; and (b) newer tracers in development as markers of angiogenetic biology.

A largely sought-for application for medical imaging is Monitoring quality of surgery: Cancer patients could benefit from a surgical procedure that helps the surgeon to determine adequate tumor resection margins. Variety of applications and work-flows; e.g. Systemic injection of tumor-specific fluorescence agents with subsequent intraoperative optical imaging to guide the surgeon in the process are offered. Recently, in order to overcome the problem of tumor heterogeneity it was proposed to shift the focus of tumor targeting towards the follicle-stimulating hormone receptor (FSHR).

Imaging bio-markers

Being able to discover and clinically validate fundamental finger-prints of cancer which can be detected and quantified through medical-imaging modalities is key to transforming the potential presented by medical imaging into clinical reality. Such specific finger-prints/characteristics are usually referred to as imaging bio-markers.

A critical step in the discovery and validation of imaging bio-markers is the matching of tissue location as depicted by imaging-products (most commonly images) to their histology, as underlined by a pathologist under the microscope.

Since histology requires extraction of organ tissue and some processing, it is impossible to achieve such matching in real time. Therefore, different techniques were developed to support the retrospective matching between histology and imaging. The most prevalent one rely on image registration: i.e. the products of medical imaging are registered to images of pathology slides. The main limitation of such methods has to do with:

  1. The fact that the two images poses largely different image resolution.
  2. The form-factor (shape and dimensions) of Histological tissue-slides are distorted in comparison to their in-vivo state.
  3. Histology-reading is subjective; i.e. the concordance between readings of different pathologist is far from being satisfactory. It gets worse when it comes to staging of the cancer.
  4. There is large variation in the quality of medical imaging products.

A Workflow to Improve the Alignment of Prostate Imaging with Whole-mount Histopathology presents a robust methodology validating imaging biomarkers in the case of prostate cancer. In this paper we describe a workflow for three-dimensional alignment of prostate imaging data against whole-mount prostatectomy reference specimens and assess its performance against a standard workflow. We hypothesized that integration of image registration principles into the histological workflow for radical prostatectomy specimens would increase the alignment accuracy. In this post I will include only few excerpts from this paper which I strongly recommend to read in full.

Materials and Methods

Ethical approval was granted. Patients underwent motorized transrectal ultrasound (Prostate Histoscanning) to generate a three-dimensional image of the prostate before radical prostatectomy. The test workflow incorporated steps for axial alignment between imaging and histology, size adjustments following formalin fixation, and use of custom-made parallel cutters and digital caliper instruments. The control workflow comprised freehand cutting and assumed homogeneous block thicknesses at the same relative angles between pathology and imaging sections. The basic requirements of image registration were incorporated within the pathological protocol.

We demonstrate that the use of a simple, custom-made tissue-planer to slice the formalin-fixed prostate results in more uniform and parallel tissue blocks than conventional freehand techniques, and increases the accuracy of image alignment.  We also show that accounting for dimensional change due to formalin fixation is essential during image alignment.

Figure 1: Suggested workflow for registration of scanned histopathological data with radiological imaging

 fig1

 Figure 3

A sketch of the tissue cutting device is shown (A).  The formalin-fixed prostate was placed on the space marked “X” on the device with its flat posterior surface facing down.  With the probe in the urethra to align the AP axis with the device, the base of the gland was gently pressed onto “Y”.  The probe was then removed, and a mounted microtome blade was lowered along the 4mm raised edge of the device from top to bottom to cut away the block (B).  The sliced block was put aside with its apical face facing down, and the process was repeated by gently pressing the cut surface flush against the device before each cut (C).  The thickness of each block was measured in 5 locations marked (D).

fig3

Results

Thirty radical prostatectomy specimens were histologically and radiologically processed, either by an alignment-optimized workflow (n = 20) or a control workflow (n = 10). The optimized workflow generated tissue blocks of heterogeneous thicknesses but with no significant drifting in the cutting plane. The control workflow resulted in significantly nonparallel blocks, accurately matching only one out of four histology blocks to their respective imaging data. The image-to-histology alignment accuracy was 20% greater in the optimized workflow (P < .0001), with higher sensitivity (85% vs. 69%) and specificity (94% vs. 73%) for margin prediction in a 5 × 5-mm grid analysis.

Figure 5. Assessment of alignment accuracy between radiological images and pathological sections

The method of assessing alignment accuracy between radiological images and pathological slides is shown using an example.  Each square within the grids overlaid onto histology and radiological images were scored either as a “1”, indicating the presence of a histological or radiological margin, respectively, or “0”.  Scored pathology grids were used as the reference, and scored radiology grids were used as the index.  Hence, we determined true positives i.e. grid points score “1” in both histology and radiology (yellow squares, n=25), false positives i.e. grid points on the radiology scores “1” but not on histology (green squares, n=4), false negatives i.e. grid points on the histology scores “0” but not on radiology (red squares, n=3), and true negatives (grey squares, n=38).

 fig5

Conclusions

A significantly better alignment was observed in the optimized workflow. Evaluation of prostate imaging biomarkers using whole-mount histology references should include a test-to-reference spatial alignment workflow.

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Author and curator: Ritu Saxena, Ph.D.

This post attempts to integrate three posts and to embed all comments made to all three papers, allowing the reader a critically thought compilation of evidence-based medicine and scientific discourse.

Dr. Dror Nir authored a post on October 16th titled “Knowing the tumor’s size and location, could we target treatment to THE ROI by applying imaging-guided intervention?” The article attracted over 20 comments from readers including researchers and oncologists debating the following issues:

  • imaging technologies in cancer
  • tumor size, and
  • tumor response to treatment.

The debate lead to several new posts authored by:

This post is a compilation of the views of authors representing different specialties including research and medicine. In medicine: Pathology, Oncology Surgery and Medical Imaging, are represented.

Dr. Nir’s post talked about an advanced technique developed by the researchers at Sunnybrook Health Sciences Centre, University of Toronto, Canada for cancer lesions’ detection and image-guided cancer treatment in the specific Region of Interest (ROI). The group was successfully able to show the feasibility and safety of magnetic resonance imaging (MRI) – controlled transurethral ultrasound therapy for prostate cancer in eight patients.

The dilemma of defining the Region of Interest for imaging-based therapy

Dr. Bernstein, one of the authors at Pharmaceuticalintelligence.com, a Fellow of the American College of Pathology, reiterated the objective of the study stating that “Their study’s objective was to prove that using real-time MRI guidance of HIFU treatment is possible and it guarantees that the location of ablated tissue indeed corresponds to the locations planned for treatment.” He expressed his opinion about the study by bringing into focus a very important issue i.e., given the fact that the part surrounding the cancer tissue is in the transition state, challenge in defining a ROI that could be approached by imaging-based therapy. Regarding the study discussed, he states – “This is a method demonstration, but not a proof of concept by any means.  It adds to the cacophany of approaches, and in a much larger study would prove to be beneficial in treatment, but not a cure for serious prostate cancer because it is unlikely that it can get beyond the margin, and also because there is overtreatment at the cutoff of PSA at 4.0. I think that the pathologist has to see the tissue, and the standard in pathology now is for any result that is cancer, two pathologists or a group sitting together should see it. It’s not an easy diagnosis.”

“The crux of the matter in terms of capability is that the cancer tissue, adjacent tissue, and the fibrous matrix are all in transition to the cancerous state. It is taught to resect leaving “free margin”, which is better aesthetically, and has had success in breast surgery. The dilemma is that the patient may return, but how soon?” concludes Dr. Larry.

Dr. Nir responded, “The philosophy behind lumpectomy is preserving quality of life. It was Prof. Veronesi (IEO) who introduced this method 30 years ago noticing that in the majority of cases; the patient will die from something else before presenting recurrence of breast cancer. It is well established that when the resection margins are declared by a pathologist (as good as he/she could be) as “free of cancer”, the probability of recurrence is much lower than otherwise. He explains further, “The worst enemy of finding solutions is doing nothing while using the excuse of looking for the “ultimate solution.” Personally, I believe in combining methods and improving clinical assessment based on information fusion. Being able to predict, and then timely track the response to treatment is a major issue that affects survival and costs!

In this discussion my view is expressed, below.

  • The paper that discusses imaging technique had the objective of finding out whether real-time MRI guidance of treatment was even possible and if yes, whether the treatment could be performed in accurate location of the ROI? The data reveals they were pretty successful in accomplishing their objective and of course that gives hope to the imaging-based targeted therapies.
  • Whether the ROI is defined properly and if it accounts for the real tumor cure, is a different question. Role of pathologists and the histological analysis and what they bring to the table cannot be ruled out, and the absence of a defined line between the tumor and the stromal region in the vicinity is well documented. However, that cannot rule out the value and scope of imaging-based detection and targeted therapy. After all, it is seminal in guiding minimally invasive surgery.
  • As another arm of personalized medicine-based cure for cancer, molecular biologists at MD Anderson have suggested molecular and genetic profiling of the tumor to determine genetic aberrations on the basis of which matched-therapy could be recommended to patients.
  • When phase I trial was conducted, the results were encouraging and the survival rate was better in matched-therapy patients compared to unmatched patients. Therefore, every time there is more to consider when treating a cancer patient and who knows a combination of views of oncologists, pathologists, molecular biologists, geneticists, surgeons would device improvised protocols for diagnosis and treatment. It is always going to be complicated and generalizations would never give an answer. Smart interpretations of therapies – imaging-based or others would always be required!

To read additional comments, including those from Dr. Williams, Dr. Lev-Ari, refers to:

Knowing the tumor’s size and location, could we target treatment to THE ROI by applying imaging-guided intervention? Author and Reporter: Dror Nir, Ph.D.

Dr. Lev-Ari in her paper linked three fields that bear weight in the determination of Tumor Response to Therapy:

  • Personalized Medicine
  • Cancer Cell Biology, and
  • Minimally Invasive Surgery (MIS)

Her objectives were to address research methodology, the heterogeneity innate to Cancer Cell Biology and Treatment choice in the Operating Room — all are related to the topic at hand: How to deliver optimal care with least invasive intervention course.

Any attempt aimed at approaching this desirable result, called Personalized Medicine,  involves engagement in three strategies:

  • prediction of Patient’s reaction to Drug induction
  • design of Clinical Trials to validate drug efficacy on small subset of patients predicted to react favorable to drug regimen, increasing validity and reliability
  • Genetical identification of patients at no need to have a drug administered if non sensitivity to the drug has been predicted

These method are to be applied to a list of 56 leading Cancer types.

While the executive task of the clinician remains to assess the differentiation in Tumor Response to Treatment, pursuit of  individualized histopathology, as well as tumor molecular, genetic and functional characteristics has to take into consideration the “total” individual patients’ characteristics: age, co-morbidities, secondary risks and allergies to drugs.

In Dr. Lev-Ari’s paper Minimally Invasive Treatment (MIT) is compared with Minimally Invasive Surgery (MIS) applied for tumor resection.  In many cases MIS is not the right surgical decision, yet, it is applied for a corollary of patient-centered care considerations. At present, facing the unknown of the future behavior of the tumor as its response to therapeutics bearing uncertainty related to therapy outcomes.

Forget me not – says the ‘Stroma’

Dr. Brücher, the author of review on tumor response criteria, expressed his views on the topic. He remembers that 10 years ago, every cancer researcher stated – “look at the tumor cells only – forget the stroma”. However, the times have changed, “now, everyone knows that it is a system we are looking at, and viewing and analyzing only tumor cells is really not enough.”

He went on to state “if we would be honest, we would have to declare that all data, which had been produced 8-13 years ago, dealing with laser capture microdissection, would need a rescrutinization, because the influence of the stroma was ‘forgotten’.”

He added, “the surgeon looks at the ‘free margin’ in a kind of reductionable model, the pathologist is more the control instance. I personally see the pathologist as ‘the control instance’ of surgical quality. Therefore, not the wish of the surgeon is important, the objective way of looking into problems or challenges. Can a pathologist always state if a R0-resection had been performed?”

What is the real RO-resection?

There have been many surrogate marker analysis, says Dr. Brücher, and that a substantially well thought through structured analysis has never been done: mm by mm and afterwards analyzing that by a ROC analysis. For information on genetic markers on cancer, refer to the following post by Dr. Lev-Ari’s: Personalized Medicine: Cancer Cell Biology and Minimally Invasive Surgery (MIS)

He also stated that there is no gold standard to compare the statistical ROC analysis to. Often it is just declared and stated but it is still not clear what the real RO-resection is?

He added, “in some organs it is very difficult and we all (surgeons, pathologists, clinicians) that we always get to the limit, if we try interpreting the R-classification within the 3rd dimension.”

Dr. Brücher explains regarding resectability classification, “If lymph nodes are negative it does not mean, lymph nodes are really negative. For example, up to 38% upper GI cancers have histological negative lymph nodes, but immunohistochemical positive lymph nodes. And, Stojadinovic et al have also shown similar observations at el in colorectal cancer. So the 4th dimension of cancer – the lymph nodes / the lymphatic vessel invasion are much more important than just a TNM classification, which unfortunately does often not reflect real tumor biology.”

The discussion regarding the transition state of the tumor surrounding tissue and the ‘free margin’ led to a bigger issue, the heterogeneity of tumors.

Dr. Bernstein quoted a few lines from the review article titled “Tumor response criteria: are they appropriate?, authored by Dr Björn LDM Brücher et al published in Future Oncology in 2012.

  • Tumor heterogeneity is a ubiquitous phemomenon. In particular, there are important differences among the various types of gastrointestinal (GI) cancers in terms of tumor biology, treatment response and prognosis.
  • This forms the principal basis for targeted therapy directed by tumor-specific testing at either the gene or protein level. Despite rapid advances in our understanding of targeted therapy for GI cancers, the impact on cancer survival has been marginal.
  • Can tumor response to therapy be predicted, thereby improving the selection of patients for cancer treatment?
  • In 2000, the NCI with the European Association for Research and Treatment of Cancer, proposed a replacement of 2D measurement with a decrease in the largest tumor diameter by 30% in one dimension. Tumor response as defined would translate into a 50% decrease for a spherical lesion
  • We must rethink how we may better determine treatment response in a reliable, reproducible way that is aimed at individualizing the therapy of cancer patients.
  • We must change the tools we use to assess tumor response. The new modality should be based on empirical evidence that translates into relevant and meaningful clinical outcome data.
  • This becomes a conundrum of sorts in an era of ‘minimally invasive treatment’.
  • Integrated multidisciplinary panel of international experts – not sure that that will do it.

Dr. Bernstein followed up by authoring a separate post on tumor response. His views on tumor response criteria have been quoted in the following paragraphs:

Can tumor response to therapy be predicted?

The goal is not just complete response. Histopathological response seems to be related post-treatment histopathological assessment but it is not free from the challenge of accurately determining treatment response, as this method cannot delineate whether or not there are residual cancer cells. Functional imaging to assess metabolic response by 18-fluorodeoxyglucose PET also has its limits, as the results are impacted significantly by several variables:

• tumor type
• sizing
• doubling time
• anaplasia?
• extent of tumor necrosis
• type of antitumor therapy and the time when response was determined.

The new modality should be based on individualized histopathology as well as tumor molecular, genetic and functional characteristics, and individual patients’ characteristics, a greater challenge in an era of ‘minimally invasive treatment’.

This listing suggests that for every cancer the following data has to be collected (except doubling time). If there were five variables, the classification based on these alone would calculate to be very sizable based on Eugene Rypka’s feature extraction and classification.

But looking forward, time to remission and disease free survival are additionally important. Treatment for cure is not the endpoint, but the best that can be done is to extend the time of survival to a realistic long term goal and retain a quality of life.

For detailed discussion on the topic of tumor response and comments refer to the following posts:

What can we expect of tumor therapeutic response?

Author: Larry H. Bernstein, MD, FCAP

Judging ‘Tumor response’-there is more food for thought

Reporter: Ritu Saxena, Ph.D.

Additional Sources:

Research articles:

Brücher BLDM  et al. Tumor response criteria: are they appropriate? Future Oncol. August Vol. 8, No. 8, Pages 903-906 (2012).

Brücher BLDM, Piso P, Verwaal V et al. Peritoneal carcinomatosis: overview and basics. Cancer Invest.30(3),209–224 (2012).


Brücher BLDM, Swisher S, Königsrainer A et al. Response to preoperative therapy in upper gastrointestinal cancers. Ann. Surg. Oncol.16(4),878–886 (2009).


Miller AB, Hoogstraten B, Staquet M, Winkler A. Reporting results of cancer treatment. Cancer47(1),207–214 (1981).


Therasse P, Arbuck SG, Eisenhauer EA et al. New guidelines to evaluate the response to treatment in solid tumors. European Organization for Research and Treatment of Cancer, National Cancer Institute of the United States, National Cancer Institute of Canada. J. Natl Cancer Inst.92(3),205–216 (2000).


Brücher BLDM, Becker K, Lordick F et al. The clinical impact of histopathological response assessment by residual tumor cell quantification in esophageal squamous cell carcinomas. Cancer106(10),2119–2127 (2006).

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Reporter: Ritu Saxena, Ph.D.

With the number of cancer cases plummeting every year, there is a dire need for finding a cure to wipe the disease out. A number of therapeutic drugs are currently in use, however, due to heterogeneity of the disease targeted therapy is required. An important criteria that needs to be addressed in this context is the –‘tumor response’ and how it could be predicted, thereby improving the selection of patients for cancer treatment. The issue of tumor response has been addressed in a recent editorial titled “Tumor response criteria: are they appropriate?” published recently in Future Oncology.

The article talks about how the early tumor treatment response methods came into practice and how we need to redefine and reassess the tumor response.

Defining ‘tumor response’ has always been a challenge

WHO defines a response to anticancer therapy as 50% or more reduction in the tumor size measured in two perpendicular diameters. It is based on the results of experiments performed by Moertel and Hanley in 1976 and later published by Miller et al in 1981. Twenty years later, in the year 2000, the US National Cancer Institute, with the European Association for Research and Treatment of Cancer, proposed ‘new response criteria’ for solid tumors; a replacement of 2D measurement with measurement of one dimen­sion was made. Tumor response was defined as a decrease in the largest tumor diameter by 30%, which would translate into a 50% decrease for a spherical lesion. However, response criteria have not been updated after that and there a structured standardization of treatment response is still required especially when several studies have revealed that the response of tumors to a therapy via imaging results from conventional approaches such as endoscopy, CT scan, is not reliable. The reason is that evaluating the size of tumor is just one part of the story and to get the complete picture inves­tigating and evaluating the tissue is essential to differentiate between treatment-related scar, fibrosis or micro­scopic residual tumor.

In clinical practice, treatment response is determined on the basis of well-established parameters obtained from diagnostic imaging, both cross-sectional and functional. In general, the response is classified as:

  • Complete remission: If a tumor disappears after a particular therapy,
  • Partial remission: there is residual tumor after therapy.

For a doctor examining the morphology of the tumor, complete remission might seem like good news, however, mission might not be complete yet! For example, in some cases, with regard to prognosis, patients with 0% residual tumor (complete tumor response) had the same prognosis com­pared with those patients with 1–10% residual tumor (subtotal response).

Another example is that in patients demonstrating complete remission of tumor response as observed with clinical, sonographic, functional (PET) and histopathological analysis experience recur­rence within the first 2 years of resection.

Adding complexity to the situation is the fact that the appropriate, clinically relevant timing of assess­ment of tumor response to treatment remains undefined. An example mentioned in the editorial is – for gastrointestinal (GI) malignancies, the assessment timing varies considerably from 3 to 6 weeks after initia­tion of neoadjuvant external beam radiation. Further, time could vary depending upon the type of radiation administered, i.e., if it is external beam, accelerated hyperfractionation, or brachytherapy.

Abovementioned examples remind us of the intricacy and enigma of tumor biol­ogy and subsequent tumor response.

Conclusion

Owing to the extraordinary het­erogeneity of cancers between patients, and pri­mary and metastatic tumors in the same patients, it is important to consider several factors while determining the response of tumors to different therapie in clinical trials. Authors exclaim, “We must change the tools we use to assess tumor response. The new modality should be based on individualized histopathology as well as tumor molecular, genetic and functional characteristics, and individual patients’ charac­teristics.”

Future perspective

Editorial points out that the oncologists, radiotherapists, and immunologists all might have a different opinion and observation as far as tumor response is considered. For example, surgical oncologists might determine a treatment to be effective if the local tumor control is much better after multimodal treatment, and that patients post-therapeutically also reveal an increase of the rate of microscopic and macroscopic R0-resection. Immunologists, on the other hand, might just declare a response if immune-competent cells have been decreased and, possibly, without clinical signs of decrease of tumor size.

What might be the answer to the complexity to reading tumor response is stated in the editorial – “an interdisciplinary initiative with all key stake­holders and disciplines represented is imperative to make predictive and prognostic individualized tumor response assessment a modern-day reality. The integrated multidisciplinary panel of international experts need to define how to leverage existing data, tissue and testing platforms in order to predict individual patient treatment response and prog­nosis.”

Sources:

Editorial : Björn LDM Brücher et al Tumor response criteria: are they appropriate? Future Oncology August 2012, Vol. 8, No. 8, 903-906.

Miller AB, Hoogstraten B, Staquet M, Winkler A. Reporting results of cancer treatment. Cancer 1981, 47(1),207–214.

Related articles to this subject on this Open Access Online Scientific Journal:

See comment written for :

Knowing the tumor’s size and location, could we target treatment to THE ROI by applying

http://pharmaceuticalintelligence.com/2012/10/16/knowing-the-tumors-size-and-location-could-we-target-treatment-to-the-roi-by-applying-imaging-guided-intervention/imaging-guided intervention?

Personalized Medicine: Cancer Cell Biology and Minimally Invasive Surgery (MIS)

http://pharmaceuticalintelligence.com/2012/12/01/personalized-medicine-cancer-cell-biology-and-minimally-invasive-surgery-mis/

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