Separation of diffusion and slow flow effects by use of flow rephasing and dephasing

Velocity-compensated intravoxel incoherent motion of the human calf muscle

PURPOSE

To determine whether intravoxel incoherent motion (IVIM) describes the blood perfusion in muscles better, assuming pseudo diffusion (Bihan Model 1) or ballistic motion (Bihan Model 2).

METHODS

IVIM parameters were measured in 18 healthy subjects with three different diffusion gradient time profiles (bipolar with two diffusion times and one with velocity compensation) and 17 b-values (0-600 s/mm2) at rest and after muscle activation. The diffusion coefficient, perfusion fraction, and pseudo-diffusion coefficient were estimated with a segmented fit in the gastrocnemius medialis (GM) and tibialis anterior (TA) muscles.

RESULTS

Velocity-compensated gradients resulted in a decreased perfusion fraction (6.9% ± 1.4% vs. 4.4% ± 1.3% in the GM after activation) and pseudo-diffusion coefficient (0.069 ± 0.046 mm2/s vs. 0.014 ± 0.006 in the GM after activation) compared to the bipolar gradients with the longer diffusion encoding time. Increased diffusion coefficients, perfusion fractions, and pseudo-diffusion coefficients were observed in the GM after activation for all gradient profiles. However, the increase was significantly smaller for the velocity-compensated gradients. A diffusion time dependence was found for the pseudo-diffusion coefficient in the activated muscle.

CONCLUSION

Velocity-compensated diffusion gradients significantly suppress the IVIM effect in the calf muscle, indicating that the ballistic limit is mostly reached, which is supported by the time dependence of the pseudo-diffusion coefficient.

Robust multishot diffusion-weighted imaging of the abdomen with region-based shot rejection

PURPOSE

Diffusion-weighted (DW) imaging provides a useful clinical contrast, but is susceptible to motion-induced dephasing caused by the application of strong diffusion gradients. Phase navigators are commonly used to resolve shot-to-shot motion-induced phase in multishot reconstructions, but poor phase estimates result in signal dropout and Apparent Diffusion Coefficient (ADC) overestimation. These artifacts are prominent in the abdomen, a region prone to involuntary cardiac and respiratory motion. To improve the robustness of DW imaging in the abdomen, region-based shot rejection schemes that selectively weight regions where the shot-to-shot phase is poorly estimated were evaluated.

METHODS

Spatially varying weights for each shot, reflecting both the accuracy of the estimated phase and the degree of subvoxel dephasing, were estimated from the phase navigator magnitude images. The weighting was integrated into a multishot reconstruction using different formulations and phase navigator resolutions and tested with different phase navigator resolutions in multishot DW-echo Planar Imaging acquisitions of the liver and pancreas, using conventional monopolar and velocity-compensated diffusion encoding. Reconstructed images and ADC estimates were compared qualitatively.

RESULTS

The proposed region-based shot rejection reduces banding and signal dropout artifacts caused by physiological motion in the liver and pancreas. Shot rejection allows conventional monopolar diffusion encoding to achieve median ADCs in the pancreas comparable to motion-compensated diffusion encoding, albeit with a greater spread of ADCs.

CONCLUSION

Region-based shot rejection is a linear reconstruction that improves the motion robustness of multi-shot DWI and requires no sequence modifications.

Feature-guided deep learning reduces signal loss and increases lesion CNR in diffusion-weighted imaging of the liver

PURPOSE

This research aims to develop a feature-guided deep learning approach and compare it with an optimized conventional post-processing algorithm in order to enhance the image quality of diffusion-weighted liver images and, in particular, to reduce the pulsation-induced signal loss occurring predominantly in the left liver lobe.

METHODS

Data from 40 patients with liver lesions were used. For the conventional approach, the best-suited out of five examined algorithms was chosen. For the deep learning approach, a U-Net was trained. Instead of learning "gold-standard" target images, the network was trained to optimize four image features (lesion CNR, vessel darkness, data consistency, and pulsation artifact reduction), which could be assessed quantitatively using manually drawn ROIs. A quality score was calculated from these four features. As an additional quality assessment, three radiologists rated different features of the resulting images.

RESULTS

The conventional approach could substantially increase the lesion CNR and reduce the pulsation-induced signal loss. However, the vessel darkness was reduced. The deep learning approach increased the lesion CNR and reduced the signal loss to a slightly lower extent, but it could additionally increase the vessel darkness. According to the image quality score, the quality of the deep-learning images was higher than that of the images obtained using the conventional approach. The radiologist ratings were mostly consistent with the quantitative scores, but the overall quality ratings differed among the readers.

CONCLUSION

Unlike the conventional algorithm, the deep-learning algorithm increased the vessel darkness. Therefore, it may be a viable alternative to conventional algorithms.

Reduction of the cardiac pulsation artifact and improvement of lesion conspicuity in flow‐compensated diffusion images in the liver—A quantitative evaluation of postprocessing algorithms

PURPOSE

To enhance image quality of flow-compensated diffusion-weighted liver MRI data by increasing the lesion conspicuity and reducing the cardiac pulsation artifact using postprocessing algorithms.

METHODS

Diffusion-weighted image data of 40 patients with liver lesions had been acquired at 1.5 T. These data were postprocessed with 5 different algorithms (weighted averaging, p-mean, percentile, outlier exclusion, and exception set). Four image properties of the postprocessed data were evaluated for optimizing the algorithm parameters. These properties were the lesion to tissue contrast-to-noise ratio (CNR), the reduction of the cardiac pulsation artifact, the data consistency, and the vessel darkness. They were combined into a total quality score ( Q total , $$ {Q}_{\mathrm{total}}, $$ set to 1 for the trace-weighted reference image), which was used to rate the image quality objectively.

RESULTS

The weighted averaging algorithm performed best according to the total quality score ( Q total = 1.111 ± 0.067 $$ {Q}_{\mathrm{total}}=1.111\pm 0.067 $$ ). The further ranking was outlier exclusion algorithm ( Q total = 1.086 ± 0.061 $$ {Q}_{\mathrm{total}}=1.086\pm 0.061 $$ ), p-mean algorithm ( Q total = 1.045 ± 0.049 $$ {Q}_{\mathrm{total}}=1.045\pm 0.049 $$ ), percentile algorithm ( Q total = 1.012 ± 0.049 $$ {Q}_{\mathrm{total}}=1.012\pm 0.049 $$ ), and exception set algorithm ( Q total = 0.957 ± 0.027 $$ {Q}_{\mathrm{total}}=0.957\pm 0.027 $$ ). All optimized algorithms except for the exception set algorithm corrected the pulsation artifact and increased the lesion CNR. Changes in Q total $$ {Q}_{\mathrm{total}} $$ were significant for all optimized algorithms except for the percentile algorithm. Liver ADC was significantly reduced (except for the exception set algorithm), particularly in the left lobe.

CONCLUSION

Postprocessing algorithms should be used for flow-compensated liver DWI. The proposed weighted averaging algorithm seems to be suited best to increase the image quality of artifact-corrupted flow-compensated diffusion-weighted liver data.

Flow-compensated diffusion encoding in MRI for improved liver metastasis detection

Magnetic resonance (MR) diffusion-weighted imaging (DWI) is often used to detect focal liver lesions (FLLs), though DWI image quality can be limited in the left liver lobe owing to the pulsatile motion of the nearby heart. Flow-compensated (FloCo) diffusion encoding has been shown to reduce this pulsation artifact. The purpose of this prospective study was to intra-individually compare DWI of the liver acquired with conventional monopolar and FloCo diffusion encoding for assessing metastatic FLLs in non-cirrhotic patients. Forty patients with known or suspected multiple metastatic FLLs were included and measured at 1.5 T field strength with a conventional (monopolar) and a FloCo diffusion encoding EPI sequence (single refocused; b-values, 50 and 800 s/mm²). Two board-certified radiologists analyzed the DWI images independently. They issued Likert-scale ratings (1 = worst, 5 = best) for pulsation artifact severity and counted the difference of lesions visible at b = 800 s/mm² separately for small and large FLLs (i.e., < 1 cm or > 1 cm) and separately for left and right liver lobe. Differences between the two diffusion encodings were assessed with the Wilcoxon signed-rank test. Both readers found a reduction in pulsation artifact in the liver with FloCo encoding (p < 0.001 for both liver lobes). More small lesions were detected with FloCo diffusion encoding in both liver lobes (left lobe: six and seven additional lesions by readers 1 and 2, respectively; right lobe: five and seven additional lesions for readers 1 and 2, respectively). Both readers found one additional large lesion in the left liver lobe. Thus, flow-compensated diffusion encoding appears more effective than monopolar diffusion encoding for the detection of liver metastases.

Combined diffusion-relaxometry microstructure imaging: Current status and future prospects

Microstructure imaging seeks to noninvasively measure and map microscopic tissue features by pairing mathematical modeling with tailored MRI protocols. This article reviews an emerging paradigm that has the potential to provide a more detailed assessment of tissue microstructure-combined diffusion-relaxometry imaging. Combined diffusion-relaxometry acquisitions vary multiple MR contrast encodings-such as b-value, gradient direction, inversion time, and echo time-in a multidimensional acquisition space. When paired with suitable analysis techniques, this enables quantification of correlations and coupling between multiple MR parameters-such as diffusivity, T 1 , T 2 , and T 2 ∗ . This opens the possibility of disentangling multiple tissue compartments (within voxels) that are indistinguishable with single-contrast scans, enabling a new generation of microstructural maps with improved biological sensitivity and specificity.

Imaging brain microstructure with diffusion MRI: practicality and applications

This article gives an overview of microstructure imaging of the brain with diffusion MRI and reviews the state of the art. The microstructure-imaging paradigm aims to estimate and map microscopic properties of tissue using a model that links these properties to the voxel scale MR signal. Imaging techniques of this type are just starting to make the transition from the technical research domain to wide application in biomedical studies. We focus here on the practicalities of both implementing such techniques and using them in applications. Specifically, the article summarizes the relevant aspects of brain microanatomy and the range of diffusion-weighted MR measurements that provide sensitivity to them. It then reviews the evolution of mathematical and computational models that relate the diffusion MR signal to brain tissue microstructure, as well as the expanding areas of application. Next we focus on practicalities of designing a working microstructure imaging technique: model selection, experiment design, parameter estimation, validation, and the pipeline of development of this class of technique. The article concludes with some future perspectives on opportunities in this topic and expectations on how the field will evolve in the short-to-medium term.

Effect of flow-encoding strength on intravoxel incoherent motion in the liver

PURPOSE

To study the impact of variable flow-encoding strength on intravoxel incoherent motion (IVIM) liver imaging of diffusion and perfusion.

THEORY

Signal attenuation in DWI arises from (1) intravoxel microvascular blood flow, which depends on the flow-encoding strength α (first gradient moment) of the diffusion-encoding waveform, and (2) intravoxel spin diffusion, which depends on the b-value of the diffusion-encoding gradient waveforms α and b-value. Both are linked to the diffusion-encoding gradient waveform and conventionally are not independently controlled.

METHODS

In this work a convex optimization framework was used to generate gradient waveforms with independent α and b-value. Thirty-six unique α and b-value sample points from 5 different gradient waveforms were used to reconstruct perfusion fraction (f), coefficient of diffusion (D), and blood velocity standard deviation (V_b ) maps using a recently proposed IVIM model. Faster acquisition strategies were evaluated with 1000 random subsampling strategies of 16, 8, and 4 α and b-value. Among the subsampled reconstructions, the sampling schemes that minimized the difference with the fully sampled reconstruction were reported.

RESULTS

Healthy volunteers (N = 9) were imaged on a 3T scanner. Liver perfusion and diffusion estimates using the fully sampled IVIM method were f = 0.19 ± 0.06, D = 1.15 ± 0.15 × 10^-3 mm² /s, and V_b = 5.22 ± 3.86 mm/s. No statistical differences were found between the fully sampled and 2-times undersampled reconstruction (f = 0.2 ± 0.07, D = 1.19 ± 0.15 × 10^-3 mm² /s, V_b = 5.79 ± 3.43 mm/s); 4-times undersampled (f = 0.2 ± 0.06, D = 1.15 ± 0.17 × 10^-3 mm² /s, V_b = 4.66 ± 3.61 mm/s), or 8-times undersampled ( f = 0.2 ± 0.06, D = 1.23 ± 0.22 × 10^-3 mm² /s, V_b = 4.99 ± 3.82 mm/s) approaches.

CONCLUSION

We demonstrate the IVIM signal's dependence on the b-value, the diffusion-encoding time and the flow-encoding strength and observe in vivo the ballistic regime signature of microperfusion in the liver. This work also demonstrates that using an IVIM model and sampling scheme matched to the ballistic regime, pixel-wise IVIM parameter maps are possible when sampling as few as 4 IVIM signals.

Intravoxel incoherent motion MRI as a means to measure in vivo perfusion: A review of the evidence

The idea that in vivo intravoxel incoherent motion magnetic resonance signal is influenced by blood motion in the microvasculature is exciting, because it suggests that local and quantitative perfusion information can be obtained in a simple and elegant way from a few diffusion-weighted images, without contrast injection. When the method was proposed in the late 1980s some doubts appeared as to its feasibility, and, probably because the signal to noise and image quality at the time was not sufficient, no obvious experimental evidence could be produced to alleviate them. Helped by the tremendous improvements seen in the last three decades in MR hardware, pulse design, and post-processing capabilities, an increasing number of encouraging reports on the value of intravoxel incoherent motion perfusion imaging have emerged. The aim of this article is to review the current published evidence on the feasibility of in vivo perfusion imaging with intravoxel incoherent motion MRI.

Evaluation of antiangiogenic and antiproliferative effects of sorafenib by sequential histology and intravoxel incoherent motion diffusion-weighted imaging in an orthotopic hepatocellular carcinoma xenograft model

PURPOSE

To investigate the effectiveness of intravoxel incoherent motion (IVIM) in the assessment of the therapeutic efficacy of sorafenib in an orthotopic hepatocellular carcinoma (HCC) xenograft model.

MATERIALS AND METHODS

Thirty-five HCC nude mouse models were established. IVIM was performed on a 1.5T MR scanner at baseline (n = 5) and serially at 7, 14, and 21 days after sorafenib treatment. The apparent diffusion coefficient (ADC_total ), true diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) at these timepoints were measured and compared between the treated (n = 15) and control group (n = 15). Differences in measurements among different timepoints were evaluated. Correlations between IVIM parameters and histologic features including necrotic fraction (NF) and microvessel density (MVD) were analyzed.

RESULTS

Compared to the control group, ADC_total and D were significantly higher at each timepoint (P = 0.009), while f significantly decreased at 7 days (P = 0.009) and increased at 21 days (P = 0.028) in the treated group. Serial measurements in the treated group showed that both ADC_total and D increased significantly at 7, 14, and 21 days compared to baseline (P < 0.05), while f significantly declined at 7 days (P = 0.016) and increased at 21 days (P = 0.009). Significant correlations were found between ADC_total and NF (r = 0.811, P < 0.001), D and NF (r = 0.838, P < 0.001), and between f and NF (r = 0.528, P = 0.017) in the treated group.

CONCLUSION

IVIM may provide useful biomarkers for evaluating the therapeutic effects of sorafenib on HCC.

LEVEL OF EVIDENCE

1 J. Magn. Reson. Imaging 2017;45:270-280.

Quantification of microcirculatory parameters by joint analysis of flow-compensated and non-flow-compensated intravoxel incoherent motion (IVIM) data

The aim of this study was to improve the accuracy and precision of perfusion fraction and blood velocity dispersion estimates in intravoxel incoherent motion (IVIM) imaging, using joint analysis of flow-compensated and non-flow-compensated motion-encoded MRI data. A double diffusion encoding sequence capable of switching between flow-compensated and non-flow-compensated encoding modes was implemented. In vivo brain data were collected in eight healthy volunteers and processed using the joint analysis. Simulations were used to compare the performance of the proposed analysis method with conventional IVIM analysis. With flow compensation, strong rephasing was observed for the in vivo data, approximately cancelling the IVIM effect. The joint analysis yielded physiologically reasonable perfusion fraction maps. Estimated perfusion fractions were 2.43 ± 0.81% in gray matter, 1.81 ± 0.90% in deep gray matter, and 1.64 ± 0.72% in white matter (mean ± SD, n = 8). Simulations showed improved accuracy and precision when using joint analysis of flow-compensated and non-flow-compensated data, compared with conventional IVIM analysis. Double diffusion encoding with flow compensation was feasible for in vivo imaging of the perfusion fraction in the brain. The strong rephasing implied that blood flowing through the cerebral microvascular system was closer to the ballistic limit than the diffusive limit.

Quantifying venous flow dynamics by flow-dephased and flow-rephased functional magnetic resonance imaging

By combining flow-dephased and flow-rephased diffusion weighting with blood oxygenation level dependent functional magnetic resonance imaging, it is possible to study flow dynamics in the venous network of the human brain. Thereby, ballistic flow, which conserves direction and velocity during echo time, is separated from diffusive flow with many changes in direction and velocity. By using this technique with very low diffusion/flow weighting, the mean velocity of ballistic flow was quantified in this study. The result of 10.9+/-3.2 cm/s strongly indicates that large venous vessels are the source of ballistic flow.

Quantifying the intra- and extravascular contributions to spin-echo fMRI at 3 T

Functional MRI (fMRI) by means of spin-echo (SE) techniques provides an interesting alternative to gradient-echo methods because the contrast is based primarily on dynamic averaging associated with the blood oxygenation level-dependent (BOLD) effect. In this article the contributions from different brain compartments to BOLD signal changes in SE echo planar imaging (EPI) are investigated. To gain a better understanding of the underlying mechanisms that cause the fMRI contrast, two experiments are presented: First, the intravascular contribution is decomposed into two fractions with different regimes of flow by means of diffusion-weighting gradient schemes which are either flow-compensated, or will maximally dephase moving spins. Second, contributions from the intra- and extravascular space are selectively suppressed by combining flow-weighting with additional refocusing pulses. The results indicate two qualitatively different components of flowing blood which contribute to the BOLD contrast and a nearly equal share in functional signal from the intra- and extravascular compartments at TE approximately 80 ms and 3 T. Combining these results, there is evidence that at least one-half of the functional signal originates from the parenchyma in SE fMRI at 3 T. The authors suggest the use of flow-compensated diffusion weighting for SE fMRI to improve the sensitivity to the parenchyma.

Effect of vasodilator hydralazine on tumor microvascular random flow and blood volume as measured by intravoxel incoherent motion (IVIM) weighted MRI in conjunction with Gd-DTPA-Albumin enhanced MRI

We studied the effect of hydralazine on tumor blood volume fraction and microvascular random flow velocity magnitude by IVIM weighted MRI in conjunction with dynamic Gd-DTPA-Albumin enhanced MRI. Blood volume fraction maps were obtained from the dynamic Gd-DTPA-Albumin enhanced MRI measurements. The average blood volume fraction of R3230 AC adenocarcinoma decreased from 0.125 +/- 0.022 (s.d.) ml/g to 0.105 +/- 0.018 (s.d.) ml/g (p < 0.001) after the administration of hydralazine at a dose of 5 mg/kg. The microvascular random flow velocity magnitude maps were obtained from the IVIM weighted MRI signals by utilizing the Gd-DTPA-Albumin measured blood volume fractions as an input in the compartmental modeling analysis of the IVIM weighted MRI signal. The random-directional microvascular flow induced MRI signal attenuation was separated from the molecular diffusion induced signal attenuation. Flow induced attenuation was more significant after the administration of hydralazine. The mean microvascular random flow velocity magnitude increased from 0.52 +/- 0.15 (s.d.) mm/sec to 0.73 +/- 0.23 (s.d.) mm/sec (p < 0.05) in the presence of the above blood volume fraction change.

Assessment of borderzone ischemia with a combined MR imaging-MR angiography-MR spectroscopy protocol

We attempted to assess whether magnetic resonance imaging (MRI)-MR angiography (MRA)-MR spectroscopy (MRS) measurements can be used in the differentiation of patients in whom severe carotid lesions result in chronically hypoperfused regions and in whom the collateral capacity is sufficient to maintain a normal cerebral blood flow. Sixty-six patients with severe stenosis of the internal carotid artery (ICA) and 19 control subjects underwent MRI, 1H MRS, and MRA. Anaerobic metabolic changes in the middle cerebral artery (MCA) territory were studied by assessing N-acetyl-L-aspartate (NAA)/choline and lactate/ NAA ratios. Quantitative flow was measured in the ICA, in the basilar artery, and in the MCA. Thirty-four patients had borderzone infarcts, 16 patients had territory infarcts, and 16 patients had no infarcts on MRI. Patients with border-zone infarcts had significantly reduced flow in the ICA (P < 0.001) and in the MCA (P < 0.05) and decreased NAA/ choline ratios (P < 0.001) in non-infarcted regions compared with control subjects (P < 0.001) but also compared with patients with territory infarcts (P < 0.05) and patients without infarcts (P < 0.05). Flow measurements in the ICA and MCA and metabolic measurements in the MCA territory can be applied to select patients in whom cerebral perfusion pressure is insufficient to maintain normal cellular integrity.

Measurement of tumor vascular volume and mean microvascular random flow velocity magnitude by dynamic Gd-DTPA-albumin enhanced and diffusion-weighted MRI

Tumor vascular volume fraction and the magnitude of the mean microvascular random flow velocity were measured in an animal tumor model by combining dynamic Gd-DTPA-albumin enhanced MRI and diffusion-weighted MRI in conjunction with a compartmental modeling analysis. The vascular volume fraction maps were obtained from the dynamic Gd-DTPA-albumin enhanced MRI measurement. It was found that the vascular volume fraction for Walker 256 tumor was higher within the outgrowing rim and decreased towards the central region. The average value obtained from five animals was 0.062 +/- 0.009 ml/g. By using the vascular volume fraction from the Gd-DTPA-albumin enhanced MRI measurement, maps of the magnitude of the mean microvascular random flow velocity were obtained from the diffusion-weighted MRI measurements with the compartmental modeling analysis. The relative extravascular and intravascular contributions to the diffusion-weighted MRI signal were determined for three tissue groups with different Gd-DTPA-albumin enhancement characteristics, and the flow and molecular diffusion-induced attenuation factors for the intravascular compartment were also compared. The mean microvascular random flow velocity magnitude maps were obtained with an average value of 0.67 +/- 0.06 mm/s.

Diffusion MRI: precision, accuracy and flow effects

After a decade of evolution and application of diffusion imaging, a large body of literature has been accumulated. It is in this context that the accuracy and precision of diffusion-weighted and quantitative diffusion MRI are reviewed. The emphasis of the review is on practical methods for clinical human imaging, particularly in the brain. The requirements for accuracy and precision are reviewed for various clinical and basic science applications. The methods of measuring and calculating diffusion effects with MRI are reviewed. The pulse gradient spin echo (PGSE) methods are emphasized as these methods are used most commonly in the clinical setting. Processing of PGSE data is reviewed. Various PGSE encoding schemes are also reviewed in terms of the accuracy and precision of isotropic and anisotropic diffusion measurements. The broad range of factors impacting the accuracy of the PGSE methods and other encoding schemes is then considered. Firstly, system inaccuracies such as background imaging gradients, gradient linearity, refocusing RF pulses, eddy currents, image misregistration, noise and dynamic range are considered. A second class of inaccuracies is contributed by the bulk effects of the imaged object, and include sample background gradients, subject motion of cerebrospinal fluid and organs, and aperiodic organ motion. A final category of potential inaccuracies is classified as being contributed by microscopic, biophysical tissue properties and include partial volume effects, anisotropy, restriction, diffusion distance, compartmentation, exchange, multiexponential diffusion decay, T2 weighting and microvascular perfusion. Finally, the application of diffusion methods to studies of blood flow in the microvasculature (i.e. the arterioles, capillaries and venules) are reviewed in detail, particularly in terms of feasibility and the stringent accuracy and precision requirements. Recent provocative studies examining the use of PGSE approaches to suppress microvascular signals in brain functional MRI (fMRI) are also reviewed.

Quantitative MRI of Gd-DTPA uptake in tumors: response to photodynamic therapy

A partial saturation method is described for obtaining rapid images of tissue 1H spin-lattice relaxation rates following administration of the paramagnetic contrast agent gadolinium-diethylenetriaminepentaacetate. The paramagnetic contribution to the relaxation rates is proportional to the concentration of contrast agent, making possible quantitative studies of paramagnetic contrast agent uptake or vessel leakage. Snapshot imaging capabilities are not required. Maps of contrast agent uptake rates are made in rat borne tumors before and following photodynamic therapy, which is known to cause vascular damage. Uptake efficiency is spatially heterogeneous before and after therapy. Decreases in uptake rate are observed after two photo-irradiation protocols, which differ by a factor of four in fluence rate but deliver the same total fluence. There is no apparent fluence rate dependence for changes in the uptake rates within 5 h after therapy. Whole tumor measurements of nucleotide triphosphates, inorganic phosphate, pH, and lactate made with NMR spectroscopy indicate that, while net ATP production is inhibited, lactate concentrations are not strongly affected by photodynamic therapy. The ratio of nucleotide triphosphates to inorganic phosphate falls to 0.21 +/- 0.02 of initial values 5 h after tumors are treated with the lower fluence rate protocol, and falls to 0.40 +/- 0.06 in tumors treated with the higher fluence rate.