Noam Nissan

Bio: Noam Nissan is an academic researcher from Sheba Medical Center. The author has contributed to research in topics: Breast MRI & Breast cancer. The author has an hindex of 11, co-authored 31 publications receiving 437 citations. Previous affiliations of Noam Nissan include Tel Aviv University & Weizmann Institute of Science.

Diffusion-weighted breast MRI: Clinical applications and emerging techniques

Abstract: Diffusion-weighted MRI (DWI) holds potential to improve the detection and biological characterization of breast cancer. DWI is increasingly being incorporated into breast MRI protocols to address some of the shortcomings of routine clinical breast MRI. Potential benefits include improved differentiation of benign and malignant breast lesions, assessment and prediction of therapeutic efficacy, and noncontrast detection of breast cancer. The breast presents a unique imaging environment with significant physiologic and inter-subject variations, as well as specific challenges to achieving reliable high quality diffusion-weighted MR images. Technical innovations are helping to overcome many of the image quality issues that have limited widespread use of DWI for breast imaging. Advanced modeling approaches to further characterize tissue perfusion, complexity, and glandular organization may expand knowledge and yield improved diagnostic tools. Level of Evidence: 5 J. Magn. Reson. Imaging 2016

Diffusion-Tensor MR Imaging of the Breast: Hormonal Regulation

Abstract: The breast diffusion-tensor parameters are not sensitive to menstrual cycle changes, whereas lactation and long-term use of hormone replacement therapy do not affect diffusion parameters.

Can diffusion tensor anisotropy indices assist in breast cancer detection

Abstract: PURPOSE To evaluate whether the various anisotropy indices derived from breast diffusion tensor imaging (DTI) can characterize the healthy breast structure and differentiate cancer from normal breast tissue. MATERIALS AND METHODS Six healthy volunteers and retrospectively selected 24 breast cancer patients were imaged at 3T. DTI included two b-values 0 and 700 sec/mm2 with 20-64 gradient directions and TE of 120 or 90 msec. The normalized anisotropy indices: fractional anisotropy (FA), relative anisotropy (RA), and 1-volume ratio (1-VR), as well as the absolute maximal anisotropy index (λ1 -λ3 ) were compared. RESULTS The spatial distribution of the various anisotropy indices in healthy volunteers exhibited a high congruence (Pearson correlation coefficients range: 0.79-1.0). All indices showed a statistically significant reduction (P < 0.001) following shortening of the diffusion time. Significantly lower λ1 -λ3 values were found in cancers as compared to normal breast tissue (P < 6.0 × 10-7 ), while the values of the normalized indices in cancers were not significantly different from those in normal breast tissue (P < 0.65 for FA, P < 0.6 for RA, and P < 0.2 for 1-VR). The contrast-to-noise ratio of λ1 -λ3 was significantly higher (P < 0.001) than those of the normalized anisotropy indices, and the area under the curve in a receiver operating characteristic analysis exhibited the highest value for λ1 -λ3 (0.89 ± 0.04 vs. 0.51-0.54 for the other anisotropy indices). CONCLUSION Water diffusion anisotropy in the healthy breast can be similarly mapped by the normalized indices and by λ1 -λ3 . However, the normalized anisotropy indices fail to differentiate cancer from normal breast tissue, whereas λ1 -λ3 can assist in differentiating cancer from normal breast tissue. J. Magn. Reson. Imaging 2016;44:1624-1632.

Quantitative evaluation of breast cancer response to neoadjuvant chemotherapy by diffusion tensor imaging: Initial results

Abstract: Background Diffusion tensor imaging (DTI) yields several parameters that have not been tested in response evaluation to neoadjuvant chemotherapy (NAC). Purpose To evaluate and compare in reference to histopathology findings the ability of DTI and dynamic contrast-enhanced (DCE) MRI to monitor response to NAC. Study Type Retrospective. Population Twenty patients treated with neoadjuvant chemotherapy. Field Strength/Sequence 1.5T MRI axial, bilateral T2-weighted, DTI, and DCE-MRI. Assessment A standardized blinded image analysis at pixel resolution generated color-coded maps of DTI and DCE parameters Statistical Tests Pearson's correlation analysis and Bland–Altman plots of the DTI and DCE size changes and of the pathological final residual tumor diameter and DCE or DTI final diameter, from pre- to post-NAC. Spearman coefficient of rank correlation between the DTI and DCE size changes from pre- to post-NAC and Miller and Payne (M&P) pathological response grading. Receiver operating characteristic curve analyses to differentiate between responders to nonresponders on the basis of the DTI and DCE percent size changes and the changes in DTI parameters. Results DTI and DCE changes in the cancers' diameter and volume from pre- to post-NAC exhibited high and significant Pearson correlation (r = 0.82 P = 1.2 × 10−5). The DTI volume changes exhibited a significant Spearman coefficient rank correlation (0.68, P = 0.001) with the pathological M&P grading and differentiated between responders and nonresponders with area-under-the-curve (AUC) of 0.83 ± 0.10. A similar AUC for differentiating responders from nonresponders was exhibited by the changes in the highest diffusion coefficient (0.84 ± 0.11) and the mean diffusivity (0.83 ± 0.11). The DTI residual-tumor-diameter showed a high and significant Pearson correlation (r = 0.87 P = 1.2 × 10−6) to pathology tumor diameter. Data Conclusion DTI monitors changes in cancer size and diffusion tensor parameters in response to NAC with an accuracy equivalent to that of DCE, enabling differentiation of responders from nonresponders and assessment of residual tumor size in high congruence with pathology. Level of Evidence: 1 Technical Efficacy: Stage 4 J. Magn. Reson. Imaging 2017.

SF-010-4 Distant metastasis occurs late during the genetic evolution of pancreatic cancer

Abstract: Metastasis, the dissemination and growth of neoplastic cells in an organ distinct from that in which they originated, is the most common cause of death in cancer patients. This is particularly true for pancreatic cancers, where most patients are diagnosed with metastatic disease and few show a sustained response to chemotherapy or radiation therapy. Whether the dismal prognosis of patients with pancreatic cancer compared to patients with other types of cancer is a result of late diagnosis or early dissemination of disease to distant organs is not known. Here we rely on data generated by sequencing the genomes of seven pancreatic cancer metastases to evaluate the clonal relationships among primary and metastatic cancers. We find that clonal populations that give rise to distant metastases are represented within the primary carcinoma, but these clones are genetically evolved from the original parental, non-metastatic clone. Thus, genetic heterogeneity of metastases reflects that within the primary carcinoma. A quantitative analysis of the timing of the genetic evolution of pancreatic cancer was performed, indicating at least a decade between the occurrence of the initiating mutation and the birth of the parental, non-metastatic founder cell. At least five more years are required for the acquisition of metastatic ability and patients die an average of two years thereafter. These data provide novel insights into the genetic features underlying pancreatic cancer progression and define a broad time window of opportunity for early detection to prevent deaths from metastatic disease.

Breast MRI: State of the Art

Abstract: MRI of the breast has the highest sensitivity for breast cancer detection among current clinical imaging modalities and is indispensable for breast imaging practice. While the basis of breast MRI consists of T1-weighted contrast-enhanced imaging, T2-weighted, ultrafast, and diffusion-weighted imaging may be used to improve lesion characterization. Such multiparametric assessment of breast lesions allows for excellent discrimination between benign and malignant breast lesions. Indications for breast MRI are expanding. In preoperative staging, multiple studies confirm the superiority of MRI to other imaging modalities for tumor size estimation and detection of additional tumor foci in the ipsilateral and contralateral breast. Ongoing studies show that in experienced hands this can be used to improve breast cancer surgery, although there is no evidence of improved long-term outcomes. Screening indications are likewise growing as evidence is accumulating that OncologicRI depicts cancers at an earlier stage than mammography in all women. To manage the associated costs for screening, the use of abbreviated protocols may be beneficial. In patients treated with neoadjuvant chemotherapy, MRI is used to document response. It is essential to realize that oncologic and surgical response are different, and evaluation should be adapted to the underlying question.

Diffusion-weighted breast MRI: Clinical applications and emerging techniques

Abstract: Diffusion-weighted MRI (DWI) holds potential to improve the detection and biological characterization of breast cancer. DWI is increasingly being incorporated into breast MRI protocols to address some of the shortcomings of routine clinical breast MRI. Potential benefits include improved differentiation of benign and malignant breast lesions, assessment and prediction of therapeutic efficacy, and noncontrast detection of breast cancer. The breast presents a unique imaging environment with significant physiologic and inter-subject variations, as well as specific challenges to achieving reliable high quality diffusion-weighted MR images. Technical innovations are helping to overcome many of the image quality issues that have limited widespread use of DWI for breast imaging. Advanced modeling approaches to further characterize tissue perfusion, complexity, and glandular organization may expand knowledge and yield improved diagnostic tools. Level of Evidence: 5 J. Magn. Reson. Imaging 2016