Purpose To examine the potential use of BOLD (Blood Oxygenation Level Dependent) and TOLD (Tissue Oxygenation Level Dependent) contrast MRI to assess tumor oxygenation and predict radiation response. Methods BOLD and TOLD MRI were performed on Dunning R3327-AT1 rat prostate tumors during hyperoxic gas breathing challenge at 4.7 T. Animals were divided into two groups. In Group 1 (n=9), subsequent 19F MRI based on spin lattice relaxation of hexafluorobenzene reporter molecule provided quantitative oximetry for comparison. For Group 2 rats (n=13) growth delay following a single dose of 30 Gy was compared with pre-irradiation BOLD and TOLD assessments. Results Oxygen (100%O2) and carbogen (CB; 95%O2/5%CO2) challenge elicited similar BOLD, TOLD and pO2 responses. Strong correlations were observed between BOLD or R2* response and quantitative 19F pO2 measurements. TOLD response showed a general trend with weaker correlation. Irradiation caused a significant tumor growth delay and tumors with larger changes in TOLD and R1 values upon oxygen breathing exhibited significantly increased tumor growth delay. Conclusion These results provide further insight into the relationships between oxygen sensitive (BOLD/TOLD) MRI and tumor pO2. Moreover, a larger increase in R1 response to hyperoxic gas challenge coincided with greater tumor growth delay following irradiation.

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Pathological estimation of tumor necrosis after chemotherapy is essential for patients with osteosarcoma. This study reports the first fully automated tool to assess viable and necrotic tumor in osteosarcoma, employing advances in histopathology digitization and automated learning. We selected 40 digitized whole slide images representing the heterogeneity of osteosarcoma and chemotherapy response. With the goal of labeling the diverse regions of the digitized tissue into viable tumor, necrotic tumor, and non-tumor, we trained 13 machine-learning models and selected the top performing one (a Support Vector Machine) based on reported accuracy. We also developed a deep-learning architecture and trained it on the same data set. We computed the receiver-operator characteristic for discrimination of non-tumor from tumor followed by conditional discrimination of necrotic from viable tumor and found our models performing exceptionally well. We then used the trained models to identify regions of interest on image-tiles generated from test whole slide images. The classification output is visualized as a tumor-prediction map, displaying the extent of viable and necrotic tumor in the slide image. Thus, we lay the foundation for a complete tumor assessment pipeline from original histology images to tumor-prediction map generation. The proposed pipeline can also be adopted for other types of tumor.

There is intense interest in developing non-invasive prognostic biomarkers of tumor response to therapy, particularly with regard to hypoxia. It has been suggested that oxygen sensitive MRI, notably Blood Oxygen Level Dependent (BOLD) and Tissue Oxygen Level Dependent (TOLD) may provide relevant measurements. This study examined the feasibility of interleaved T2*- and T1-weighted oxygen sensitive MRI, as well as R2* and R1 maps of rat tumors to assess the relative sensitivity to changes in oxygenation.Investigations used cohorts of Dunning Prostate R3327-AT1 and -HI tumors, which are reported to exhibit distinct size-dependent levels of hypoxia and response to hyperoxic gas breathing. Proton MRI R1 and R2* maps were obtained for tumors of anesthetized rats (isoflurane/air) at 4.7 T. Then, interleaved gradient echo T2*- and T1-weighted images were acquired during air breathing and a ten minute challenge with carbogen (95% O2/5% CO2). Signals were stable during air breathing and each type of tumor showed distinct signal response to carbogen. T2* (BOLD) response preceded T1 (TOLD) responses, as expected. Smaller HI tumors (reported to be well oxygenated) showed the largest BOLD and TOLD responses. Larger AT1 tumors (reported to be hypoxic and resist modulation by gas breathing) showed the smallest response. There was a strong correlation between BOLD and TOLD signal responses, but ΔR *2 and ΔR1 were only correlated for the HI tumors. The magnitude of BOLD and TOLD signal responses to carbogen breathing reflected expected hypoxic fractions and oxygen dynamics suggesting potential value of this test as a prognostic biomarker of tumor hypoxia.

Hypoxia is reported to be a biomarker for poor prognosis in cervical cancer. However, a practical non-invasive method is needed for routine clinical evaluation of tumor hypoxia. This study examined the potential use of BOLD (Blood Oxygenation Level Dependent) contrast MRI as a non-invasive technique to assess tumor vascular oxygenation at 3 T. Following IRB-approved informed consent and in compliance with HIPAA, successful results were achieved in nine patients with locally advanced cervical cancer (FIGO stage IIA to IVA) and three normal volunteers. In the first four patients, dynamic T2*-weighted MRI was performed in the transaxial plane using a multi-shot EPI sequence while patients breathed room air followed by oxygen (15 dm3/min). Later, a multi-echo gradient echo examination was added to provide quantitative R2* measurements. Baseline T2*-weighted signal intensity was quite stable, but increased to various extents in tumors upon initiation of oxygen breathing. Signal in normal uterus increased significantly, while iliacus muscle did not change. R2* responded significantly in healthy uterus, cervix, and eight cervical tumors. This preliminary study demonstrates that BOLD MRI of cervical cancer at 3 T is feasible. However, more patients must be evaluated and followed clinically before any prognostic value can be determined.